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91	Mathematics and Statistics	ABS-43
Confidence Interval for Curve of Spline Truncated Nonparametric Regression for Longitudinal Data Hasri Rahmawati*, I Nyoman Budiantara, Jerry Dwi Trijoyo Purnomo Department of Statistics, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember Abstract Regression is one of the analytical methods used to determine the pattern of relationship between response variables and predictor variables. One of the main objectives of regression analysis is to obtain point estimates and confidence intervals for parameters or regression curves. The confidence interval of the regression curve is able to describe the upper limit and lower limit of the resulting regression curve. When the data used is not known the shape of the regression curve pattern, a nonparametric regression approach is used. Truncated splines are able to handle data that have changing behavior at certain sub-intervals and tend to find their own data estimates wherever the data pattern moves, truncated splines provide smoother and more flexible curves that are limited within an interval. Longitudinal data can provide an interpretation of the model over time because it is carried out at a certain period of time, thus the conclusions obtained will be more complete. The purpose of this study is to obtain confidence intervals for nonparametric regression curves on longitudinal data. For parameter estimation using Weighted Least Square (WLS) optimization, in constructing the shortest interval for the spline truncated nonparametric regression curve using pivotal quantity for the case of known population variance and unknown population variance. Confidence intervals provide information about the uncertainty in the estimation of regression curves, so the results of this study can be useful in decision making related to longitudinal data and related regression analysis. Keywords: Nonparametric Regression- Confidence Interval- Longitudinal Data. Share Link | Plain Format | Corresponding Author (Hasri Rahmawati)

92	Mathematics and Statistics	ABS-44
Application of Least Absolute Deviation Regression Using the EM Algorithm on Outlier Data (Case Study: Modeling the Open Unemployment Rate in Java Island in 2021) Rizki Ayu Fitrian Sari, Setiawan, Santi Puteri Rahayu Department of Statistics, Institut Teknologi Sepuluh Nopember, Kampus ITS-Sukolilo, Surabaya 60111, Indonesia Abstract Estimation of linear regression parameters is known by using the Ordinary Least Square (OLS) method. The OLS method is very sensitive to deviations from assumptions in the data, especially the residual normality assumption in the data, which is caused by outliers. To reduce the influence of outliers is to use robust estimates. One such estimator is the Least Absolute Deviation (LAD). The LAD method is a method that minimizes the absolute number of errors (the sum of the absolute values of the vertical residuals between the points generated by the function and the corresponding points in the data). The advantage of LAD is that it is resistant to outliers in the data. LAD generally uses IRLS (Iteratively Reweighted Least Square) iterations, the nature of this iteration makes the algorithm for the LAD method more complex and requires a long time to compute, so this study considers using the EM algorithm to solve computational problems. This study aims to estimate the LAD regression parameter with the EM algorithm that is applied to the Open Unemployment Rate in Java Island in 2021. The results of this study by looking at the largest r-square value indicate that the LAD method gives better results than the OLS method for cases of outlier data . Keywords: Regression- OLS- Outlier- LAD- EM Algorithm Share Link | Plain Format | Corresponding Author (RIZKI AYU FITRIAN SARI)

93	Mathematics and Statistics	ABS-46
Properties of The Algebraic Structure of Real Number Sequences Bagus Aqil Saputra (a*), Ikrar Pramudya (a), Mardiyana(a), Ponco Sujatmiko (a), Dyah Ratri Aryuana (a) a) Department of Mathematics Education, Universitas Sebelas Maret, Jl. Ir. Sutami No.36, Kentingan, Jebres, Surakarta, Jawa Tengah 57126, Indonesia, Telp/Fax: 0271-648939 *bagusaqilsaputra[at]student.uns.ac.id Abstract The real number sequence has practical value for studying various topics in real analysis. This study aimed to characterize the algebraic structure of the set of real number sequences with addition and function multiplication as its binary operation. Therefore, the discussion of problems in this study utilized properties from group theory and real analysis to derive properties of the elements and subsets. The investigated problems included the properties of the set of real number sequences based on convergence, the existence of subgroups, normal subgroups, and group homomorphisms. The methods utilized in this research involved literature review and deductive mathematical proofs to obtain relevant theorems. Based on the problem, the concepts and theories used for analysis were those related to group theory and properties of real number sequences in real analysis. Therefore, the concepts and theories relevant to the topic needed to be reconsidered in order to obtain relevant concepts and theories to solve the research problem. Keywords: sequence- convergence- normal subgroup- homomorphism Share Link | Plain Format | Corresponding Author (Bagus Aqil Saputra)

94	Mathematics and Statistics	ABS-48
Analysis Of Unemployed Youth In Indonesia By Panel Data Regression with Moderating Variable Sri Subanti (a*), Nabila Tri Amanda (b) a) Study program of Statistics, Universitas Sebelas Maret, Surakarta, Central Java, Indonesia *sri_subanti[at]yahoo.co.id b) Study program of Statistics, Universitas Sebelas Maret, Surakarta, Central Java, Indonesia Abstract Indonesia is entering the era of demographic bonus with the productive age dominating the population. Productive age is the main focus of the government in maximizing the demographic dividend, but Indonesia has the highest percentage of NEET in Asia. Not in employment, education or training (NEET) are young people with ages 15 - 24 years old who do other activities outside of school, work or training. This study aims to analyze young NEET in Indonesia using panel data analysis with moderate regression analysis. The research data used were obtained from the employment book and the website of Badan Pusat Statistik Indonesia, in the form of 34 cross section data with a span of 5 years as time series data. The dependent variable is NEET with 5 independent variables including Human development index (HDI), the open unemployment rate, labor force participation rate, proportion of individuals who own mobile phone, and proportion of informal employment. The moderating variable in this study is the proportion of youth aged 15-24 years old with information technology and computer skills (ICT) skills. The selected model in regression analysis panel data is fixed effect model (FEM) with R-square of 92.75% with 4 significant dependent variables. Moderating variables the proportion of adolescents and adults with ICT skills moderates the relationship of NEET with its independent variables. Moderate Regression Analysis increased the R-square value of the model to 94.19%. Keywords: Not In Employment Education Or Training- Moderating- Panel Data Regression Share Link | Plain Format | Corresponding Author (Nabila Tri Amanda)

95	Mathematics and Statistics	ABS-54
Machine Learning-Based Classification of COVID-19 and Influenza Variants Using Nucleotide Frequency Analysis Thaliah Fauz Ardamayanti (a*), Mohammad Isa Irawan (a), Ridho Nur Rohman Wijaya (a) a) Department of Mathematics, Institut Teknologi Sepuluh Nopember Jalan Raya ITS Sukolilo, Surabaya 60111, Indonesia *thaliahfauz[at]gmail.com Abstract This research aims to classify COVID-19 and influenza variants using machine learning based on nucleotide frequency analysis. The dataset consists of COVID-19 and influenza DNA sequences. We calculate the nucleotide frequencies in each sequence, then we train the features using machine learning algorithms. The experimental results show that using nucleotide frequencies as a feature provides good results in classifying COVID-19 and influenza variants, achieving the highest accuracy score of 89.99%. This discovery has significant implications for developing diagnostic tools and the epidemiological monitoring of COVID-19. The classification results enable quick and accurate identification, facilitating timely clinical decision-making and aiding in the control of disease spread. The research emphasizes the essential function of machine learning in genomic analysis and the detection of viral variants, with nucleotide frequency proving to be an informative feature for distinguishing between different variants. Keywords: Classification, COVID-19, DNA Sequences, Influenza, Machine Learning, Nucleotide Frequency Share Link | Plain Format | Corresponding Author (Thaliah Fauz Ardamayanti)

96	Mathematics and Statistics	ABS-55
Optimizing Capsule Network Methods with Norm-based Compression for Image Classification Problems Ridho Nur Rohman Wijaya (a*) Budi Setiyono (a), Mahmud Yunus (a) a) Departement of Mathematics, Faculty of Scientics, Institut Teknologi Sepuluh Nopember Surabaya, Indonesia *ridhonurrohmanwijaya[at]gmail.com Abstract Capsule Network is a powerful deep learning technique for image classification problems. However, the Capsule Network^s ability to handle images with intricate backgrounds is limited due to difficulty extracting features. In addition, forming capsule forces results in longer computation time and increased training parameters. We propose a mathematical technique by introducing a Norm-based Compression to enhance the performance of the Capsule Network method. The Norm-based Compression, constructed using Euclidean norms, aims to reduce dimensions and accelerate the translation equivariance process within capsules. Our proposed Capsule Network demonstrates significant improvements through extensive experiments on MNIST, Fashion MNIST, and Kuzushiji MNIST datasets, achieving up to 2.61% higher accuracy with the computation speed is 2.73 times faster than the original Capsule Network, and the total parameters utilized during training are reduced by 15%. Our research contributes to expanding the understanding of efficient image classification methods by offering new insights to overcome the limitations of feature extraction. Keywords: Capsule Network, Deep Learning, Euclidean Norm, Feature Extraction Share Link | Plain Format | Corresponding Author (Ridho Nur Rohman Wijaya)

97	Mathematics and Statistics	ABS-67
METRIC DIMENSION OF A GRAPH: AN APPROACH TO OBTAIN THE MINIMUM NUMBER AND LOCATION OF THE PLACEMENT OF FIRE SENSORS IN A BUILDING Desrianti L. Susanti (a), Rapmaida M. Pangaribuan (b), Farly O. Haning (c*) a,b) Mathematics Department, Universitas Nusa Cendana, Jalan Adisucipto-Penfui, Kupang 85000, Indonesia c) Mathematics Department, Universitas Nusa Cendana, Jalan Adisucipto-Penfui, Kupang 85000, Indonesia *farly_haning[at]staf.undana.ac.id Abstract A fire disaster is a small or large flame that occurs in an unwanted place. The damage caused by a disastrous fire in a public buildings or facilities will increase if it is not addressed promptly. The installation of fire sensors is one of the solutions needed. Fire sensors will detect the location of the fire and send a warning so that everyone immediately leaves the site or extinguishes the flames that appear around the fire site. The study aims to obtain the minimum number of fire sensors installed on a building using the metric dimension concept on the graph. This concept allows fire sensors to accurately detect the location of a fire so that it can be dealt with immediately. The research method used is the study of literature. Initially, the building was depicted in the form of a graph. Literary studies are conducted to find the metric dimensions of graphs that are similar to the graphs of a building. Graph G is formed with its set of vertex -(V(G))- indicating the rooms in the building and the set of sides -(E(G))- that connect two points on the graph if a door connects the two rooms. The graph image obtained on each floor of the Universitas Nusa Cendana Postgraduate Building forms the Bridge graph that connects the Star graphs -K_(1,s)- and -K_(1,t)-. This graph is a simple connected graph. A metric dimension is the cardinality of a metric base on a connected and simple graph. The metric base is the resolving set -W \subseteq V(G)- with the smallest cardinality. A set W is called a resolving set if it can make each vertex on the graph -G- have a different representation or coordinate. The representation of a vertex -v\in V- on the graph G notated by -\( r(v|W)=(d(v,w_1),d (v,w_2),d( v,w_k ))\)- which -d(v,w_i ), 1&#8804-i&#8804-k - is the shortest path length that connects vertex -v \in V- and -w_i \in W-. The vertex on -W-, which are the metric base, are the reference vertex for the placement of the fire sensor. Then the metric dimension of the graph is the minimum number of fire sensors needed on each floor. The study^s results found the bridge graph^s metric dimensions that connect the star graphs -K_(1,s)- and -K_(1,t)- is -s+t-2-. By applying this result obtained on the 1st floor, 2nd floor, and 3rd floor of the graduate building, respectively, as many as 14,12, and 8 fire sensors can be installed. It means that 15 rooms out of 49 do not need fire sensors. Keywords: Fire sensors, Graph of a building, Metric Dimension Share Link | Plain Format | Corresponding Author (Farly Oktriany Haning)

98	Mathematics and Statistics	ABS-68
Bivariate Recursive Semiparametric Probit Regression Model with Random Effects Nabilla Rida Tri Nisa (a*), Purhadi (a), Achmad Choiruddin (a) a) Department of Statistics, Institut Teknologi Sepuluh Nopember Kampus ITS - Sukolilo, Surabaya 60111, Indonesia *6003212015[at]mhs.its.ac.id Abstract The utilization of healthcare services is the effort to utilize healthcare facilities to improve health, prevent and treat diseases, and restore health. One of the factors that influences individuals to utilize healthcare facilities is health insurance ownership. The utilization of healthcare facilities and health insurance ownership can lead to endogeneity, resulting in inconsistent or biased parameter estimation results. Therefore, we apply a semiparametric recursive bivariate probit model with random effects to examine the relationship between healthcare utilization and health insurance ownership in Probolinggo City in 2021. The data used in this study is from the National Socio-Economic Survey (SUSENAS) of Probolinggo City in 2021. Parameter estimation in the RPBRS-RE model is conducted using the Maximum Likelihood Estimation (MLE) and Fisher Scoring Algorithm. The resulting information shows that gender, employment status, smoking status, and marital status significantly influence health insurance ownership. Health insurance ownership and employment status significantly affect healthcare utilization. The bivariate mass points generated are (12.07, 69) and (-22.72, 102.53) with respective probabilities of 0.126 and 0.874. Keywords: Penalized Likelihood, Probit, Semiparametric Share Link | Plain Format | Corresponding Author (Nabilla Rida Tri Nisa)

99	Mathematics and Statistics	ABS-70
Development of Model Predictive Control (MPC) on F-16 Longitudinal Motion Using Polynomial Chaos Kristian Dwi Ratna Dewi(a), Subchan(a), Kistosil Fahim(a) (a) Mathematics Department, Sepuluh Nopember Institute of Technology Arief Rahman Hakim Street, Surabaya 60111, Indonesia Abstract A dynamic system is a system that changes or experiences dynamics from time to time. In real terms, dynamical systems are not always deterministic. Dynamical systems can be stochastic because of some assumptions or distractions that limit the problem. The uncertainty in the parameters arises when the system parameters are uncertain. This occurs when the system is obtained from data using system identifiers with various uncertainties. One of the methods used to approximate linear dynamic systems with parameter uncertainty is the Polynomial Chaos method. The Polynomial Chaos method transforms the stochastic dynamic system into a deterministic dynamic system with larger state space dimensions. In this study, the control model of the longitudinal motion of the F-16 aircraft was applied using the Model Predictive Control (MPC) method. The F-16 model of longitudinal motion contains uncertain stochastic parameters. Before applying the control method using MPC, the Polynomial Chaos method was applied to the state space model of the longitudinal motion of the F 16 aircraft to obtain the deterministic model. The simulation is implemented using different prediction horizon and polynomial orders. Based on the simulation results, it was found that the pitch angle rate output can approach the given pitch angle rate reference. Keywords: Longitudinal motion, Polynomial Chaos method, Model Predictive Control (MPC) method, F-16 aircraft motion model Share Link | Plain Format | Corresponding Author (Kristian Dwi Ratna Dewi)

100	Mathematics and Statistics	ABS-83
Identifying Diabetes Mellitus through Deep Learning-Based DNA Sequences Devindha Permatasari, M. Isa Irawan Sepuluh Nopember Institute of Technology Abstract Diabetes mellitus is a chronic disease that cannot be cured and is caused by a deficiency or absence of the hormone insulin. It is the leading cause of death worldwide, with an estimated 2-5 million lives lost to diabetes every year. Detecting and treating diabetes early is critical to preventing complications and reducing the risk of serious health problems. We propose a deep learning method to identify diabetes based on biomarkers found in DNA sequences. This method uses sequences of DNA data that are represented as spectrogram images. DNA sequences are converted into numerical values using an entropy-based mapping technique which is a fractional derivative of Shannon Entropy. We use the specgram function from the Matplotlib library which uses the Short-Time Fourier Transform (STFT) to generate a spectrogram image which is a three-dimensional plot with time, frequency and amplitude represented by a color scale. Spectrogram images of DNA sequences were then extracted and classified using deep learning methods. The results reveal that the deep learning method using the ResNet module achieves an accuracy of 91.3% in identifying diabetes. Keywords: Diabetes Mellitus, Deep Learning, DNA Sequences Share Link | Plain Format | Corresponding Author (Devindha Permatasari)

101	Mathematics and Statistics	ABS-95
Performance of Gravitational Emulation Local Search Algorithm with Genetic Algorithm on VRP Variants and Its Implementation for Distribution Optimization Sapti Wahyuningsih, Lucky Tri Oktoviana, Azis Wisnu Wardana, Sinta Ayu Saputri Universitas Negeri Malang Abstract Distribution is one of the important factors in the business sector. Selection of the optimal route in the distribution process can minimize distribution costs and time. The mathematical model that can be used to solve distribution optimization problems is the application of graph theory to the study of the Vehicle Routing Problem (VRP). In this article, we will examine the performance of the Gravitational Emulation Local Search with Genetic Algorithm (GELS-GA) algorithm for VRP variants and its implementation in distribution optimization problems. The focus of discussion on the VRP variant is the Multiple Depot Vehicle Routing Problem With Time Windows (MDVRPTW) and Multiple Trip Vehicle Routing Problems With Time Windows (MTVRPTW). The performance steps of the GELS-GA algorithm are initialization, evaluation, first local search, chromosome selection, crossover, mutation and second local search. Implementation of the GELS-GA algorithm on the VRP variant using Borland Delphi programming. The program was tested at several points and compared with a standardized dataset. Input to the program is in the form of points (depots and customers), requests for each customer, service time, distance, parameters in the form of vehicle capacity, vehicle speed, time windows, population size, crossover probability (Pc), mutation probability (Pm) and number of generations. The output of the program is the result of the route formed with the total distance and travel time and graph visualization. An example of the results of the implementation of the VRP variant and its interpretation for distribution optimization problems is given. Keywords: Distribution, GELS-GA, VRP variants, MTVRPTW and MDVRPTW Share Link | Plain Format | Corresponding Author (Sapti Wahyuningsih)

102	Mathematics and Statistics	ABS-105
The Strong Rainbow Connection Numbers of Corona and Comb Product of Sandat and Path Graph Desi Rahmadani, Ainin Yusri Saputri, Purwanto Universitas Negeri Malang Abstract The strong rainbow connection number is an extension of the rainbow connection numbers where it refers to the shortest path, commonly known as the geodesic path. If G is a connected graph and every pair of vertices in G has a geodesic path whose edges do not have the same color, then G is strongly rainbow connected. The fewest colors used so that G is strongly rainbow connected is called the strong rainbow connection number. In this paper, we will determine the strong rainbow connection numbers of graphs obtained from the corona and comb product of the sandat and path graph. In particular, we will prove that the graphs are strongly rainbow connected graphs. Keywords: Strong Rainbow Connection, Sandat graph, Path, corona product, comb product Share Link | Plain Format | Corresponding Author (Desi Rahmadani)

103	Mathematics and Statistics	ABS-126
Green Probabilistic Inventory Model with Shortage Backodering, Carbon Emission Cost, and Imperfect Quality Items : A Newton - Raphson Method Approach using Python Rubono Setiawan Mathematics Education Department Universitas Sebelas Maret Abstract In this paper, a green inventory model has been developed to explain the relationship between a single manufacturer and many retailers in a multiplayer supply chain system. It is assumed that there exist some imperfect items in a quantity lot. In green inventory, one of the important issues is carbon emission with its cost to inventory management. Some troubles in the transportation process yield imperfect quality items. This trouble is the potential to increase the amount of carbon emission and some imperfect quality items. It also affects the cost of the inventory. Therefore, these two aspects will be analyzed under the shortage backorder policy. The classical optimum techniques have been used to obtain the optimum solution. Due to the complexity of the model, the formulation optimization is predominantly conducted using a numerical approach for finding partial derivatives and Newton Raphson^s method for finding the optimal solution. These methods are assisted by the Python programming language, operated within the Google Colab environment and Spyder (Python 3.8) using Anaconda environment. Keywords: manufacturer, carbon emission, inventory, imperfect quality, Python Share Link | Plain Format | Corresponding Author (Rubono Setiawan)

104	Mathematics and Statistics	ABS-130
SIGNAL PROCESSING OF THE ONE-FACTOR MEAN-REVERTING MODEL IN ENERGY SYSTEM Getut Pramesti and Ristu Saptono Universitas Sebelas Maret Abstract One of the models that can be considered in the energy system is the one-factor mean-reverting process. We propose the one-factor mean-reverting model with sinusoidal signal processing involved. The frequency component of the model can be estimated with a high-frequency scheme. The estimation of the frequency component is believed to produce a precise estimate. This is because the high-frequency scheme has the potential to handle possible non-linear coefficient cases in a unified way, that is, -nh\to \infty-, and -nh^{2}\to 0-- which is mentioned in \cite{pramesti2022parameter}. This paper shows that the frequency component estimator in the one-factor mean-reverting strong model is strongly consistent with the rate convergence, namely -\sqrt{(nh)^3}-. It is also can be shown that the estimator has a normal approximation with a mean of 0 and variance -\frac{1}{6}(1+\theta^{2})-. We applied the proposed model to the energy systems data. Keywords: one-factor, mean-reverting, frequency, signals, high-frequency Share Link | Plain Format | Corresponding Author (Getut Pramesti)

105	Physics and Physics Education	ABS-50
Extended Large Eddy Turbulent Model to Rayleigh-Benard Convection in Cavity of Various Aspect Ratio Gunarjo S Budi Physics Education of Palangka Raya University Abstract This paper presents a study of developing numerical turbulent model in cavity using Large Eddy Simulation combined with algebraic approach. The model uses set of differential equations, namely kinetic energy k, the kinetic energy dissipation &#949- and temperature variance &#952-2 which are solved numerically with finite-volume and Navier-Stokes solver. The unresolved stress tensors and heat flux vectors which appeared in the averaging process are modelled with algebraic formula. The discretization of the diffusive terms and convective terms is done using the second order differencing scheme and the second order linear upwind scheme respectively. The model is applied in natural convection heating from below, known as Rayleigh-Benard convection in three-dimensional cavity with height to length aspect ratio 1 : 1.5, 1 : 4, and 1 : 8. Validation of the model has been conducted by numerical data of Direct Numerical Simulation of turbulent flow heating from below enclosure and experimental data. The model demonstrated a good agreement with both numerical and experimental data. It was also shown that the model is able to capture quite well the main feature of turbulent convective flow in the cavity and it has a potential application for wider range of turbulence in more complex cavity. Keywords: : turbulence, algebraic model, large eddy, Rayleigh-Benard convection Share Link | Plain Format | Corresponding Author (Gunarjo Suryanto Budi)

106	Physics and Physics Education	ABS-57
Synthesis of Activated Carbon From Cassava Peel Biomass With KOH Activator as Supercapacitor Abdul Ngalimus Salam (a), Wahyudi Nandana Munte (c), Mira Ayu Rahmawati (a), Nidya Chitraningrum (b), Anif Jamaluddin (a), Lita Rahmasari (a*) a) Faculty of Teacher Training and Education, Universitas Sebelas Maret, Jl. Insinyur Sutami No.36 A, Surakarta 57126, Indonesia *lita[at]staff.uns.ac.id b) Research Center for Biomass and Bioproducts, National Research and Innovation Agency, Bogor 16911, Indonesia c) Department of Physics, University of Riau, Simpang Baru, Pekanbaru 28293, Indonesia Abstract Supercapasitors are a very promising in energy storage technology and it can be synthesized from biomass. Organic biomass is one alternative that can be used for innovation from supercapacitors, therefore the purpose of this study is to synthesize activated carbon from cassava skin biomass so that it can be applied as a supercapacitor. In this study, cassava skin biomass was used as the main ingredient in making activated carbon. The activated carbon produced is made in three stages, namely the material preparation stage, chemical activation and then physical activation. Potassium Hydroxide (KOH) is used as an activator in the chemical activation process, then in the physical activation process the method used is the pyrolysis method in a tube furnace with a temperature of 800C for 1 hour. Field Emission Scanning Electron Microscope with Energy Dispersive X-ray (FESEM-EDX), and the porosity calculation of activated carbon is used to determine the morphology, chemical composition, and pore volume size of the carbon material. The results of the analysis that have been obtained are then used as a basis for making supercapacitors from activated carbon. From the calculation results obtained a porosity value of 0.69 in activated carbon with a KOH activator of 40%. With this large porosity value, it is expected that activated carbon can be applied to supercapacitor electrodes with optimal results. Keywords: Activated Carbon, Cassava Peel, Carbonization, Supercapacitor Share Link | Plain Format | Corresponding Author (Abdul Ngalimus Salam)

107	Physics and Physics Education	ABS-82
The Role of Problem-Based Learning Model in Enhancing Students^ Motivation and Physics Learning Outcomes Een Irawati1, Mustika Wati2*, Maria Ulfah3, Yasmine Khairunnisa4 1Teacher Professional Education Study Program, Faculty of Teacher Training and Education, Lambung Mangkurat University, Indonesia 2Departement of Physics Education, Faculty of Teacher Training and Education, Lambung Mangkurat University, Indonesia 3Physics teacher of SMAN 11 Banjarmasin, Indonesia 4 Departement of Science Education, Faculty of Teacher Training and Education, Lambung Mangkurat University, Indonesia *Correspondence: mustika_pfis[at]ulm.ac.id Abstract The teacher^s role in guiding and directing students to achieve desired learning outcomes is crucial. By designing an engaging learning activities, teachers optimize student involvement and presence, leading to the increased motivation and improved learning outcomes. At senior high school in Banjarmasin, a research study using the Problem-Based Learning model was conducted to enhance motivation and learning outcomes for tenth grade students. The study focused on three areas: (1) lesson plan implementation, (2) students^ learning motivation, (3) students^ learning outcomes, and (4) Students^ responses to Problem-Based Learning. Collaborative classroom action research was conducted in two cycles involving planning, implementation, observation, and reflection. Data were collected from 34 students through tests, observation, and documentation. The study findings indicated that: (1) Lesson plan implementation was improved from an average score of 3.34 (good) in cycle I to 3.84 (very good) in cycle II, (2) Students^ learning motivation increased from an average score of 2.28675 (moderate) in the pre-cycle to 3.47975 (very high) after the learning cycle. The N-gain score was 0.6880 (moderate), (3) Students learning outcomes were significantly improved, with the average pre-cycle score of 42.60 increasing to 83.44 after the learning cycle. The N-gain score was 0.7042 (high). (4) Students^ responses to Problem-Based Learning was positive, with an average rating of 3.2375, indicating a good category. In conclusion, the implementation of Problem-Based Learning model effectively enhanced students^ motivation and improved learning outcomes of the tenth grade students at senior high school. Keywords: Problem-Based Learning, Physics, Motivation, Learning Outcome Share Link | Plain Format | Corresponding Author (Mustika Wati)

108	Physics and Physics Education	ABS-110
The Effectiveness of Discovery Learning Model on the Cognitive Abilities of Tsanawiyah Islamic Students in The Global Warming Material Nurul Lathifatul Hakimah, I Gusti Made Sanjaya, Prabowo, Eko Hariyono Postgraduate, Faculty of Mathematics and Natural Science, State University of Surabaya, Surabaya, Indonesia Abstract The purpose of this study was to determine the effectiveness of discovery learning model, the cognitive abilities of students on global warming material, the implementation of learning and the responses of students to the discovery learning model. This study used a quasy experimental design method, namely a one group pretest-posttest control design with three replications carried out in Tsanawiyah Islamic School. The sampling technique used purposive sampling using two classes (VII-F and VII-H). The data collection used is a test instrument, observation, interviews and response questionnaires. The results of the expert validation show that all the test instruments are very valid, because the test instruments have a moderate level of difficulty category, even though there is one number of difficult category questions in class VII-F and three difficult category questions in class VII-H. Correlation scores show significant and very significant categories, although the three questions are less categorical with a correlation value range of 0,491-0,800. The effectiveness of discovery learning model at Tsanawiyah Islamic School shows a good category in expert validation and student responses. Further research must be better and can be used in other learning materials. Keywords: Effectiveness of learning model, Discovery Learning, Cognitive Abilities, Validation, Global Warming, Student Responses Share Link | Plain Format | Corresponding Author (Nurul Lathifatul Hakimah)

109	Physics and Physics Education	ABS-135
Experimental Discovery Learning Model and TPACK-based Problem-Based Learning Supported Media Moodle Reviewed from Student Process Science Skills Destriana Kurniawati (a), Ahmad Fauzi (a), Rini Budiharti (a), Fairusy Fitria Haryani (a*), Desi Arinda (b) (a) Universitas Sebelas Maret, Jalan Ir. Sutami 36 A Surakarta, Indonesia (b) Monash University, Wellington Rd, Clayton VIC 3800, Australia Abstract The research aims to find out whether or not there are: 1) differences in the impact of the use of learning models discovery learning and problem-based learning supported by media Moodle on cognitive abilities- 2) differences in the influence of students with high and low science process skills on cognitional capabilities- and 3) interactions between learning models discovery learning and problem-based learning with the level of skills of science processes against cognitives on sound wave materials with the research subject being students of class XI SMAN 1 Surakarta teaching 2022-2023. The method used is the experimental method with a 2x2 factorial design. The data collection techniques used are the science process skills lift and the cognitive ability test of the learners. The data obtained was then analyzed using a two-way ANAVA test with cell frequencies not equal to the conclusion. It can be concluded that 1) there are differences in the impact of the use of discovery learning and problem-based learning supported by Moodle on cognitive abilities (Fobs = 18,606 > F0,05-1-67 = 3,98), 2) There is a difference in the influence of learners who have high science process skills and low science process abilities on cognition abilities (Fobs = 15,65 > F0,05-1-67 = 3,98), and 3) There is no interaction between the influences of learning models using discovery learning and problem-based learning in cognition (Fobs = 3,514 < F0,05-1-67 = 3,98). Keywords: science process skills, cognitive ability, discovery learning, problem-based learning, Moodle Share Link | Plain Format | Corresponding Author (Fairusy Fitria Haryani)

110	Physics, Chemistry, and Biology	ABS-14
The Influence of Variation Concentrations of C-4-Methoxyphenyl-calix[4]resorcinarene in Inhibiting Calcium Sulphate (CaSO4) Scale Formation Suryadi Budi Utomoa and Indah Wahyuni Chem Edu Universitas Sebelas Maret Abstract The research has been conducted to determine the ability of C-4-carboxymethoxyphenyl-calix[4]resocinarene as This study aims to: (1) determine whether the compound C-4-methoxyphenylkalix[4]resorcinarene is able to inhibit the growth of calcium sulphate (CaSO4) crust- (2) determine the effect of variations in the concentration of the addition of inhibitor compounds on the growth of crust (CaSO4)- (3) knowing the FTIR characterization of the inhibitor compounds before and after being used to inhibit the formation of crust (CaSO4)- (4) knowing the SEM morphology of the inhibitor compounds before and after being used in inhibiting the formation of crust (CaSO4)- and (5) determine the crystal size and degree of crystallinity based on the XRD test of the inhibitor compound before and after it is used to inhibit the formation of calcium sulfate (CaSO4) crust. The results showed that: (1) c-4-methoxyphenylkalix[4]resorcinarene inhibitors can inhibit the growth rate of CaSO4 crust- (2) the growth rate of CaSO4 crust was most inhibited by the inhibitor variation of 40 ppm in the 60th minute, namely 538 mg- (3) the results of FTIR analysis of C-4-methoxyphenylkalix[4]resorcinarene before and after it was used as a CaSO4 inhibitor underwent changes, with the functional group that interacted the most with Ca2+ was the methoxy group- (4) the morphology of the C-4-methoxyphenylkalix[4]resorcinarene compound after being used as an inhibitor has a more porous surface and larger clumps when compared to the results before being used as an inhibitor- and (5) through XRD results obtained the degree of crystallinity of C-4-methoxyphenylkalix[4]resorcinarene before and after being used as a CaSO4 crust inhibitor were respectively 80.77% and 45.37% and a crystal size of 27.53944 nm and 31.44179 nm Keywords: C-4-methoxyphenylcalix[4]resorcinarene- inhibitor, CaSO4- Scale Formation Share Link | Plain Format | Corresponding Author (Suryadi Budi Utomo)

111	STEM and STEAM Education	ABS-34
Implementation of Letter Learning Media Using Solar Cell Power for Special Needs Students Nia Wahyu Damayanti, As^ad Shidqy Aziz, Dian Utami Ikhawaningrum Universitas Wisnuwardhana Abstract The application of letter learning media using solar cell power for special needs students can be an innovative and effective approach to enhance their reading and writing skills. The objective of this research is to implement solar cell-based letter learning media for special needs students. The research subjects for this activity include students with autism, hearing impairment, and intellectual disabilities. At the beginning of the activity, it is necessary to identify the specific needs of each student. This may encompass various spectrums such as learning disorders, hearing impairments, or visual impairments. Understanding the individual needs of each student will help in designing appropriate learning solutions. Once the students^ needs have been identified, we can select suitable learning media. In this case, using media that utilizes solar cell power can provide additional benefits such as portability, independent charging capabilities, and the use of renewable resources. Keywords: learning media, solar cells, student with special need Share Link | Plain Format | Corresponding Author (Nia Wahyu Damayanti)

112	STEM and STEAM Education	ABS-81
The Autonomy-based STEM Learning Model in Improving Students^ Digital Literacy Mustika Wati(1), Artoni Yahya(2*), Margaritta(3), Yasmine Khairunnisa(4) 1 Departement of Physics Education, Faculty of Teacher Training and Education, Lambung Mangkurat University, Indonesia 2Teacher Professional Education Study Program, Faculty of Teacher Training and Education, Lambung Mangkurat University, Indonesia 3Physics teacher of SMAN 11 Banjarmasin, Indonesia 4 Departement of Science Education, Faculty of Teacher Training and Education, Lambung Mangkurat University, Indonesia *Correspondence: artoni.yh017[at]gmail.com Abstract In today^s era of technology and information, digital literacy is a key factor for success in life and work, albeit it has received less attention in schools. School is a forum for students to learn and add information about the outside world through digital media, so the role of teachers is needed to solve this problem. Teachers are expected to be able to plan learning activities for students to be active in digital literacy which then increases students^ digital literacy. Therefore, research was conducted by applying the Autonomy-based STEM Learning model to physics learning to improve students^ digital literacy. This study used a mixed method aiming to describe: (1) the lesson plan implementation, and (2) students^ digital literacy. The subjects of this study were students of grade XI senior high school in Banjarmasin. Data collection techniques were tests, observations, and documentation. The results showed that: (1) the average lesson plan implementation score is respectively 3,38 (good), 3,54 (excellent), and 3,84 (excellent), and (2) students^ digital literacy has improved as seen through the change of pretest score 49,45 (moderate) to 85,81 (excellent), with the N-gain score of 0,72 (high). So, it can be concluded that students^ digital literacy can be increased by the Autonomy-based STEM Learning model. Keywords: Digital literacy, physics learning, Autonomy-based STEM Learning Share Link | Plain Format | Corresponding Author (Mustika Wati)

113	STEM and STEAM Education	ABS-114
Batik Colek and Batik Celup through Community : A prospect of introducing the STEAM strategy to the Community Ganung Anggraeni, Laela Sagita Universitas PGRI Yogyakarta Abstract This training and mentoring program is an effort to introduce the Creation for making of Batik Colek and Batik Celup Shibori to the Padukuhan Kalipucang Community, Desa Bangunjiwo, Kasihan, Bantul, DI. Yogyakarta, especially through women who are members of the PKK/Dasa Wisma Group. The objectives of this activity include: 1) disseminating knowledge to the community, especially among women of the Dasa Wisma group about Batik Colek / Batik Celup Shibori, 2) improving the abilities and skills of the community, especially women who are members of the Dasa Wisma group to make Batik Colek / Batik Celup Shibori, 3) bringing out the spirit of entrepreneurship among community, which in turn is expected to improve family welfare. From the participants questionnaire of perception in training and mentoring, results were obtained: overall participants^ perceptions of training and mentoring activities were obtained on average of 3.23 with high categories. In addition, participants felt motivated in participating in the activities with an average of 3.38. Through the response of the participants, the service and research team believes that the activity of making batik colek and batik celup has good prospects to introduce the STEAM strategy among the community, because the making of Batik Colek and Batik celup Shibori has aspects: science, technology, engineering, art and mathematics Keywords: Batik Colek, Batik Celup Shibori, Dasawisma, STEAM Share Link | Plain Format | Corresponding Author (Ganung Anggraeni)

114	Technology in Education	ABS-15
Understanding Virtual Laboratories in Engineering Education: A Systematic Literature Review Muhamad Nur Azmi Wahyudi, Cucuk Wawan Budiyanto, Puspanda Hatta Bachelor of Informatics Education Departement, Faculty of Teacher Training and Education, Universitas Sebelas Maret, Indonesia Abstract Engineering education is considered one of the fields of interest in this 21st century because it incorporates the vital technological literacy required in today^s constantly evolving world. In engineering education, laboratories play a crucial role in providing students need to learn to apply what they have learned before. Conventional laboratories that require students to be in direct contact with their equipment have been widely used, but lately, virtual laboratories have emerged as one of the innovations in education, including engineering education. This research reviewed 41 Scopus-indexed peer-reviewed articles published between 2018 and 2023 with topics on the application of virtual laboratories in engineering education. This research was conducted according to the systematic literature review framework and used PRISMA as the article selection method. The research shows that virtual laboratories^ application in engineering education has many advantages, especially in cost-effectiveness, flexibility, safety, and accessibility. In contrast to the many advantages obtained from virtual laboratories^ applications, there are challenges, such as lack of interactivity, limited content, and being prone to technical issues. This research is expected to contribute to introducing virtual laboratories in more depth, especially in engineering education, so that virtual laboratories can be more widely applied in learning as an innovation that has a positive impact. Keywords: engineering education- virtual laboratory- systematic literature review- Share Link | Plain Format | Corresponding Author (Cucuk Wawan Budiyanto)

115	Technology in Education	ABS-27
Roblox-assisted Metaverse Learning: Review of the Literature Muhammad Ilyas, Cucuk Wawan Budiyanto, Rosihan Ari Yuana Bachelor Informatics Education, Faculty Of Teacher Training and Education, Universitas Sebelas Maret Abstract As a form of three-dimensional technological advancement, Metaverse^s users can play, collaborate, and interact in a virtual world. This concept results from multiple technologies, including virtual reality (VR) and augmented reality (AR). The Metaverse uses Roblox as one of its platforms to support learning. This platform offers a variety of entertaining games. Despite the sheer enthusiasm to adopt Metaverse in learning, only some studies address Roblox^s role in the Metaverse^s educational sphere. This research adopted the Systematic Literature Review (SLR) to investigate published articles in Scopus-indexed publication outlets ranging between 2020-2023. The search returned 463 articles, later filtered using inclusion and exclusion criteria, including publication year, level of education, research class, demography, journal indexer, analysed material, insight, and reasoning ability type. The results of SLR^s research indicate that in 2022 and 2023, there will be an abundance of publications concerning the use of Roblox in education. Suggestions for future educators or researchers to conduct additional research on Roblox in the field of education, beginning at the elementary school level and continuing through the university level. Keywords: education, Metaverse, Roblox, Systematic Literature Review Share Link | Plain Format | Corresponding Author (Cucuk Wawan Budiyanto)

116	Technology in Education	ABS-53
COMMUNITY OF PRACTICE AS A COMMUNITY DEVELOPMENT AND MAINTENANCE FRAMEWORK IN WORKPLACE ENVIRONMENT OF SOFTWARE DEVELOPER Wiku Sidik Dananjaya- Yusfia Hafid Aristyagama,S.T.,M.T.-Cucuk Wawan Budiyanto,S.T.,Ph.D. Informatics & Computer Engineering Education, Sebelas Maret University Abstract The usage of Community of Practice (CoP) has been widely spread and has been progressed over time. The progressing of CoP need to be able to align with the rapidly progressive social, culture, and knowledge, especially in Information and Communication Technology (ICT) fields. This paper discuss about the example of CoP implementation in workplace environment, Community of Practice implementation in ICT related environment, advantages and disadvantages of CoP, and summarize the CoP success factors as a community development and maintenance framework. This paper will conduct a Systematic Literature Review on Community of Practice related articles and literatures published between 2012 to 2023 and followed the PRISMA approach. This paper summarize the CoP advantages: capability to share knowledge, friendly and supportive environment, and responsive toward customers^ demand, collaboration and discussion, facilitate multi diciplinary learning, encourage observing, understanding, analyzing, and evaluating, potential link to workplace environment, easier to communicate. Meanwhile, CoP disadvantages are various barriers among members, narcissism and selfishness, individual beliefs, knowledge monopolies, the feeling of exclusivity. CoP success factors are gathered and summarized from various literatures. This paper conclude that CoP can be developed more further along with the development of social and knowledge, and success factors as framework for maintain the continuity of CoP need to align with community background, community goals, and community focus of diciplines. Keywords: Community of Practice, Software Developer, Workplace Environment Share Link | Plain Format | Corresponding Author (Wiku Sidik Dananjaya)

117	Technology in Education	ABS-59
AUDIO-VISUAL MEDIA BASED ON CANVA TO SUPPORT ONLINE LEARNING IN SD 3 WERGU WETAN Fina Fakhriyah, Siti Masfuah, Muhammad Malik Hakim Primary Educational Teacher Department, Universitas Muria Kudus Primary Educational Teacher Department, Universitas Muria Kudus Department of Informatics, Diponegoro University, Central Java, Indonesia Abstract Learning during the Covid-19 pandemic requires special and more intense attention for an educator, especially variations in the use of learning technology. The purpose of this activity is to assist teachers in the development of learning media based on the Canva application. The stages of this activity include the initial analysis stage (field conditions), introduction to the Canva application, identification of materials, and product preparation. The data obtained were then analyzed descriptively qualitatively. The product that has been developed by SD 3 Wergu Wetan teacher is validated by an expert to see the suitability of the material content, level suitability, design completeness, media design feasibility, and attractiveness. Based on the results of expert validation, a score of 87.9 percent was obtained with a very suitable category for use. From the results of this validation, it is used as a basis by the teacher to then carry out the recording stages of learning with the help of this Canva application and upload it to the youtube platform as a means of explaining material to support online learning to students at SD 3 Wergu Wetan. Keywords: Learning Technology- Learning Media, Canva Share Link | Plain Format | Corresponding Author (Fina Fakhriyah)

118	Technology in Education	ABS-106
Implemented Problem-Based Learning with Digital Argumentation (PBL-DA) Model to Cultivate Computational Thinking (CT) and High Order Thinking Skills (HOTs) Marheny Lukitasari, Agita Risma Nurhikmawati, Akhmad Sukri, Rusdi Hasan, Jomar M. Urbano, Alfredo M. Esteban Jr., Analiza B. Tanghal 1, 2. Universitas PGRI Madiun 3. Universitas Pendidikan Mandalika 4. Universitas Padjadjaran 5. Phinma Education, Philippines 6,7. Nueva Ecija University of Science and Technology, Philippines Abstract The learning ecosystem has shifted to improve CT and HOTs through the implementation of PBL-DA. The study used a quasi-experimental design. The participants were students of two universities from Indonesia and Philippines. The students^ CT skills were measured through three aspects: skills (decomposition, algorithm design, evaluation), attitudes (confidence, communication, flexibility), and approach (tinkering, creating, and collaborating indicators). HOTs were measured through critical thinking, argumentation skills, problem-solving, problem-identifying, understanding concepts, analyzing, making decisions, and creative thinking indicators. The CT and HOTS scores were analyzed with Hoteling^s T2 test to determine the influence of the PBL-DA model on CT and HOTs followed by Tukey test. The Hoteling^s T2 analysis showed that there was a significant difference in both students^ CT skill and HOTs between the experimental and control classes. Furthermore, the result Tukey test of students^ HOTs showed a significant effect of PBL-DA on the aspects of critical thinking, argumentation, problem-identifying, and analyzing. The result of the Tukey test of students^ CT showed a significant effect of PBL-DA on the skill and attitude aspects. The CT and HOT skills of the students showed strong correlation with the value 0.651. Keywords: Problem-based learning Digital argumentation, Computational thinking, HOTs Share Link | Plain Format | Corresponding Author (Marheny Lukitasari)

119	Technology in Education	ABS-108
Comparison of Apriori vs. FP-Growth Algorithm with Partitioned Data, A Case Study: Recommendations for Selection of Specialization Courses Ianatush Sholihah, Rosihan Ari Yuana, Nurcahya Pradana Taufik Prakisya Informatics and Computer Engineering Education, Faculty of Teacher Training and Education, Sebelas Maret University Indonesia Abstract Association Rule Mining (ARM) is a research topic in data mining that aims to find interesting correlations or patterns in databases. The ARM method has two algorithms that are populer in searching for item patterns in a transaction data, namely Apriori and FP-Growth. The Apriori algorithm is often used because the process is simple but takes a long time to process if the data used is large enough. The FP-Growth algorithm is here to provide an alternative way to overcome the shortcomings of the Apriori algorithm. But in some cases, FP-Growth takes longer than Apriori. To overcome this problem the data to be processed is partitioned first. A comparative analysis of the Apriori and FP-Growth algorithms was carried out by partitioning processed data in case studies of recommendation specialization courses using the Knowledge Discovery in Database (KDD) method. The analysis is carried out based on the length of execution time, memory usage, and the Lift Ratio value of each algorithm. Based on the test results, the best algorithm for recommendation for specialization courses is the FP-Growth algorithm because the required execution time is 25.4% faster. The FP-Growth algorithm is also able to produce more rules with 3.14% less memory consumption and produces a higher support, confidence, and lift values than the Apriori algorithm. Keywords: Apriori, Association Rule, Data Mining, FP-Growth, Study Plan Share Link | Plain Format | Corresponding Author (Ianatush Sholihah)

120	Technology in Education	ABS-111
The Implementation of the Zahrawain Method in Qur^anic Memorization for Kindergarten Teachers and Principles in Surakarta Sri Slamet1, Fitri Suraya Mohamad2, Mahasri Shobahiya3, Muwakhidah4, Ambarwati5, Junita Dwi Wardhani6, Universitas Muhammadiyah Surakarta. Universiti Malaysia Sarawak (UNIMAS) Abstract The Qur^an, especially the short letters, might be difficult to memorize for many principles and kindergarten teachers. The aim of this study is to investigate the effectiveness of an instructional method called the Zahrawain Method, in the learning to memorise the Holy Quran, with a group of Surakarta^s kindergarten principals and teachers. The research design employs a quasi-experimental method, to capture the before and after effects of using the selected instructional method. Findings have shown that the participants from the experimental group were more able to memorise the assigned Surah from the Holy book, after seven instructional sessions. The instrument used to measure the effectiveness is by using documentation and it was validated by the experts of psychology, Early Childhood Education, and Arabic teacher. The study concludes that the Zahrawain method is an available instructional method in the teaching of The Holy Quran, to meet the local expectations at Surakarta district. Keywords: Kindergarten, memorizing, Principal and Teacher, Zahrawain Share Link | Plain Format | Corresponding Author (Sri Slamet)

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