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121	Computer Science	ABS-171
Weakness of Active Contour Algorithm in Finding Wound Perimeter on Image Dataset and Its Solution Muhammad Eka Suryana, Muhamad Rizki, Med Irzal Universitas Negeri Jakarta Abstract Active Contour Model is the most original algorithm among the class of Contour Finding methods. Here, we are testing its capability against detecting wound parameter given an image data. The performance is less satisfying, but through some tuning by adding an extra pre-processing step with image interpolation technique the result can be improved. This paper is reporting the details of how we find the weakness of Active Contour and its improvement through the solution proposed. Keywords: Active Contour, Wound Imaging, Medical Imaging Share Link | Plain Format | Corresponding Author (Muhammad Eka Suryana)

122	Computer Science	ABS-174
Online Design Thinking with Multicultural Diversity: Advantages and Challenges Fauzan Khairi Che Harun1, a), Shizuyo Asai2, Tula Jutarosaga3, Yuli Rahmawati4, Alin Mardiah4, and Arifah Salsabil4 1Universiti Teknologi Malaysia, Malaysia 2Ritsumeikan University, Japan 3King Mongkut^s University of Technology Thonburi, Thailand 4Universitas Negeri Jakarta, Indonesia a)Corresponding author: fauzan[at]fke.utm.my Abstract Collaborative online learning has become the new norm during this pandemic era. There are many challenges when moving from offline face to face program towards online program especially in terms of tools that can be used for learning. Design thinking is a method for innovation that is widely used during design process. But the question is, how effective the design thinking process is when conducted online. What are the opportunities that can we take advantages of when conducting online? What are the tools suitable to conduct an online Design Thinking session? These are the questions that this project is trying to address. In between 2016 and 2022, the researchers have conducted more than 6 courses utilizing design thinking in a multicultural environment where students from Japan, Malaysia, Thailand and Indonesia and gathered together to solve real problem in the community. In the initial years, this program was conducted offline in between those countries but since 2020, this program has been conducted online. The online session comes with its own opportunities and challenges. A total of 7 program with more than 230 students has gone through the design thinking courses, both in an online and offline settings. Our research conclude that both session does indeed improve the 21st century skills amongst the students involves. But more interestingly, these program has shown that online design thinking courses among multicultural background can be conducted successfully with some challenges. Keywords: design thinking, multicultural, project-based learning Share Link | Plain Format | Corresponding Author (Fauzan Khairi Che Harun)

123	Computer Science	ABS-175
SHARIA PEER TO PEER LENDING INFORMATION SYSTEM FOR WEB-BASED MSMEs: AMINAH Med Irzal(a), Ari Hendarno(b*), Arimbi Mega Ningrum(c), Razka Agniatara(d) a,b,c,d) Jakarta State University, Indonesia *arihendarno[at]unj.ac.id Abstract Based on the results of the MSME needs questionnaire analysis, 37% of the 30 MSME owners chose to use personal funds to develop their businesses. There are 90% of the 30 MSME owners have problems with high interest rates, heavy collateral requirements when applying for a loan from a conventional bank. There are 33% of 30 MSME owners who need easy administration of loan applications because those at the bank are quite difficult. All these things certainly make it difficult for them to get capital assistance to develop their business, considering that there are 53% of the 30 MSMEs that need additional business capital. It takes an information system that implements Financial Technology using the concept of sharia-based peer to peer lending which aims to help micro, small and medium business owners, especially micro businesses, in overcoming capital shortages without the need to use complicated requirements and no interest rates. high as in conventional banks. This information system has a role as a liaison between business owners who need additional capital and capital owners who want to help others in advancing MSMEs with funds that are not too large but useful because one MSME will be funded by several lenders (capital owners). Based on testing using black box testing, this sharia peer to peer lending (Aminah) information system shows an average value of 92% in the very good category, so this information system can be used. Keywords: MSMEs, Sharia, Peer to Peer Lending Sharia, Financial Technology Share Link | Plain Format | Corresponding Author (Ari Hendarno)

124	Computer Science	ABS-182
Prediction of Learning Progress Using Naive Bayes for The Course Failure Early Warning System Design Ria Arafiyah(a), Meiliasari(a), Ellis Salsabila(a), (b)Alimuddin, Octarina Salsabila(a) (a) Faculty of Mathematics and Natural Sciences Universitas Negeri Jakarta (b) Department of Electrical Engeneering Universitas Sultan Ageng Tirtayasa Abstract Almost in every course, there are some successful learners and unsuccessful learners. There are many methods to reduce the number of unsuccessful learners. One of the methods is to monitor learning progress which can use to recognize whether a learner will pass or not. Monitoring based on modeling learning progress prediction can use in alternative ways. The modeling of learning progress prediction can use as an early warning system (EWS) that can warn the learners throughout the learning process. This study aims to design the Early Warning System (EWS) to monitor learning progress. Decision-making in EWS is a Naive Bayes classification model which develops from the dataset. EWS will detect learner progress according to monitoring and suggest responding to the learner to repair the learning way. Keywords: Early Warning System (EWS), learning progress, Naive Bayes Share Link | Plain Format | Corresponding Author (Ria Arafiyah)

125	Computer Science	ABS-189
Analysis of Public Sentiment Against PPKM Policy on social media Twitter Using Naive Bayes Classifier (NBC) Method Naufal Zhafran Albaqi, Suyono, Dania Siregar Statistics Department, FMIPA Universitas Negeri Jakarta, Indonesia Abstract The implementation of Community Restrictions (PPKM) is one of the policies of the Indonesian government in preventing the spread of Covid-19. The implementation of the PPKM policy that has been going on for a long time has generated many responses in the community. Twitter is one of the social media used by the public to respond to the implementation of the PPKM policy. In this study, an analysis of public sentiment will be carried out on the PPKM policy on Twitter social media using the Naive Bayes Classifier (NBC) method. In addition, an overview of topics that are often discussed on positive, negative, and neutral sentiments in the implementation of PPKM policies will also be seen. The NBC method is a classification method based on the application of Bayes^ theorem, this method was chosen because it is faster and very good for text classification. The results showed that the NBC method was able to obtain accuracy on training data ranging from 68% to 71%. Meanwhile, the accuracy rate on the test data is 71%. These results indicate that the Naive Bayes Classifier algorithm has a fairly good performance. On negative sentiment, topics that are often discussed are the extension of PPKM, naming leveled PPKM, road closures, limiting meal times, and implementation of a work from home system. Meanwhile, on positive sentiment, topics that are often discussed are the implementation of better health protocols, and vaccinations, as well as decreasing PPKM levels and decreasing Covid-19 confirmation cases Keywords: naive bayes classifier (NBC), twitter, ppkm, sentiment analysis, Share Link | Plain Format | Corresponding Author (Naufal Zhafran Albaqi)

126	Computer Science	ABS-191
Prediction of Traffic Congestion Based on Time Series Dataset Number of Vehicles Using Neural Network Algorithm Prasetyo Wibowo Yunanto (a,b*), Rahmat Gernowo (a,c), Oky Dwi Nurhayati (d) a) Doctoral Program of Information System, Diponegoro University, Jalan Imam Bardjo, SH. No.5, Semarang 50241, Indonesia *prasetyo.wy[at]unj.ac.id b) Information Systems and Technology, Universitas Negeri Jakarta, Jalan Rawamangun Muka, Jakarta 13220, Indonesia c) Department of Physics, Faculty of Science and Mathematics, Diponegoro University, Jalan Prof. Soedarto, SH, Semarang 50275, Indonesia d) Computer Engineering Department, Engineering Faculty, Diponegoro University, Jalan Prof. Soedarto, SH, Semarang 50275, Indonesia Abstract The increase in the number of vehicles that is not proportional to the increase in road infrastructure results in high traffic congestion. Traffic congestion basically repeats itself, especially at certain hours due to high mobility at those hours, for example at the time of leaving and returning from work. Repeated traffic congestion can also occur by day for example at the beginning of the week or the end of the week. Based on this fact, traffic congestion can actually be predicted for certain roads at certain hours and days if the history data is known. In this study, a traffic congestion prediction model is proposed based on a traffic congestion dataset obtained within one week for 24 hours. The results show that the Neural Network algorithm has succeeded in predicting traffic congestion with a value of RMSE 13,188 in a 94 learning cycle. Keywords: prediction- traffic congestion- Neural Network- repetitive traffic congestion Share Link | Plain Format | Corresponding Author (Prasetyo Wibowo Yunanto)

127	Mathematics	ABS-13
Finite Difference for Stock Option Simulation based on Black Scholes Models Viska Noviantri (a*), Rinda Nariswari (b), Siti Komsiyah (a) a)Mathematics Departement Bina Nusantara University Jakarta 11480, Indonesia b) Statistics Departement Bina Nusantara University Jakarta 11480, Indonesia Abstract A stock option as a derivative is a financial instrument which expected to be involved in the associated risk. Currently, options trading in Indonesia is being stopped. IDX is initiating the developments (revitalizations) of option products, in terms of infrastructure and the latest contract specifications by general practice. This study aims to provide some simulations of option price fluctuations based on stock prices. The simulation derives based on the Black Scholes Equation, which is a mathematical model that can represent the call option and put options prices of European options. This model is solved numerically using the Forward Time Center Space finite difference method. At the end of the study, it will show that the simulation results can be use to analyze the leverage parameters such as interest rates, volatility, and strike prices on option prices. Thus, if the options market reopens later, this simulation model can be used as a consideration for investors in making decisions. Keywords: Option price, Black Scholes Model, finite difference method Share Link | Plain Format | Corresponding Author (Viska Noviantri)

128	Mathematics	ABS-14
Asymptotic Properties of Alternating Renewal Process with Instantaneous Rewards Suyono- Ibnu Hadi Depertment of Mathematics, Universitas Negeri Jakarta, Indonesia Abstract Consider an alternating renewal process starting at time 0 at up state where to each its uptime and downtime, including the incomplete uptime or downtime, we associate rewards which depend on the uptime and downtime lengths. The total reward earned in the time interval [0,t] is called an alternating renewal process with instantaneous rewards. The distributional properties of this process in the bounded time interval [0,t] is known in the literature. In this paper we derive asymptotic properties of the process. Firstly, we obtain the limit in probability of the process, and secondly, we get the limiting behaviour of the mean of the process. In a special case, when the Laplace transform of the mean of the process is a rational function, we get a finer result of its asymptotic mean. Keywords: Alternating renewal process, asymptotic property, instantaneous reward, Laplace transform Share Link | Plain Format | Corresponding Author (Suyono Suyono)

129	Mathematics	ABS-17
Algorithm For Finding The Smallest Mean Square Error In Exponential Smoothing Method For Time Series Forecasting Alfian (1), Muh. Kabil Djafar (1), Nerru Pranuta Murnaka (2), Sulistiawati (2), Rinda Nariswari (3), and Samsul Arifin (3) 1) Mathematics Department, Halu Oleo University, Kendari Indonesia 93232 2) Mathematics Education Department, STKIP Surya, Tangerang, Indonesia 15115 3) Statistics Department, School of Computer Science, Bina Nusantara University, Jakarta, Indonesia 11480 Abstract One of the measurements for evaluating time series forecasting performances is the mean square error (MSE). This paper proposes the algorithm to find the smallest MSE. To capture four components of time series data (that are seasonal variations, trend variations, cyclical variations, random variations), exponential smoothing method is used. This method uses three factors for smoothing where apha is the data smoothing factor, 0 < apha < 1, betha is the trend smoothing factor, 0 < betha < 1, and gamma is the seasonal change smoothing factor, 0 < gamma < 1. All possible combinations values of smoothing factors will be generated to three decimal digits. After that, the smallest MSE of those combinations will be determined with using an algorithm and then to observe the convergence pattern of them. Keywords: Algorithm, Smallest Mean Square Error, Exponential Smoothing Method Share Link | Plain Format | Corresponding Author (Samsul Arifin)

130	Mathematics	ABS-23
ANALYSIS AND APPLICATION DEVELOPMENT OF DECISION SUPPORT SYSTEM OF BOND INVESTMENT RECOMMENDATIONS WITH FUZZY ANALYTICAL HIERARCHY PROCESS (FUZZY AHP) METHOD Amalia Sharfina Sulwan (a), Siti Komsiyah (b) , Viska Noviantri (c) (a),(b),(c) Mathematics Department School of Computer Science, Bina Nusantara University Jakarta, Indonesia 11480 Abstract This research applies Fuzzy-Analytical Hierarchy Process (AHP) method in determining the best government bond to be invested and make a web application which is easy to be accessed by various circles. By Fuzzy-AHP method, the criteria and sub-criteria that can influence decision making in bond investments will be calculated the weight of each criterion and sub-criteria to find the most important criteria and sub-criteria to be considered in choosing bonds and to support the best decision in the selection of bond series of products for investment. The purpose of this application and research is to facilitate customers in choosing bond products with various criteria and conditions and also encouraging customers to actively engage in bond transactions in case at BCA that will impact on the increase in fee-based income. The result is the criteria in bond investment are currencies, investment returns, and investor capability. It can be concluded from this research that customers pay more attention to investment yield criteria than currency and investor^s ability with 58.8% weight and the most considered sub-criteria are hold time (40.582%) and Yield/YTM (23.226%). Keywords: Decision Support System - investment -Fuzzy AHP - recommendation of bonds Share Link | Plain Format | Corresponding Author (Siti Komsiyah)

131	Mathematics	ABS-27
Linear Mixed Models to Analyze Indonesia^s PISA Reading Literacy Score Vera Maya Santi (a*), Irsyad Hasari (a), Dian Handayani (a) a) Program Studi Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Negeri Jakarta, Jl. Rawamangun Muka, Kota Jakarta Timur, DKI Jakarta, 13220, Indonesia *vmsanti[at]unj.ac.id Abstract The Programme for International Students Assessment (PISA) is a periodic survey program to evaluate the quality of education of a country based on the development of student literacy. The results of the 2018 PISA survey showed that Indonesia occupied the position of 72 out of 79 countries. This shows that the quality of education in Indonesia is still low. This study aims to analyze the factors that affect the reading literacy score of PISA Indonesia quantitatively, which until now is still very rarely done. The model used to analyze PISA reading literacy scores as well as schools as a random effect is linear mixed models (LMM). The feasibility of the model is reviewed based on the model^s goodness criteria, namely the estimation of random effect variance, parameter significance tests and model diagnostics. The results showed that the significant factors that influenced PISA reading literacy scores included education level, father^s education, internet access at home, dictionary at home, number of (TVs, cellphones, computers, ebook tabs, and books at home), behavior skipping school and late in coming to school, not listening to teacher explanation, the age of entering kindergarten and elementary school, and having stayed in class during elementary school Keywords: Linear Mixed Models- model Diagnostics- parameter significance tests- random effect- reading literacy score of PISA Indonesia Share Link | Plain Format | Corresponding Author (Vera Maya Santi)

132	Mathematics	ABS-28
The Group Selection of Variables that Effected to Science Scores of Indonesia^s PISA using Group LASSO Vera Maya Santi (a*), Rizkha Hayati (a), Bagus Sumargo(a) a) Program Studi Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Negeri Jakarta, Jl. Rawamangun Muka, Kota Jakarta Timur, DKI Jakarta, 13220, Indonesia *vmsanti[at]unj.ac.id Abstract Scientific literacy is a person^s ability to apply knowledge and develop a reflective mindset so that they can participate in overcoming issues and ideas related to science. The quality of Indonesian scientific literacy based on the results of the Program for International Students Assessment (PISA) which was followed from 2000 to 2018 is still relatively low. In 2018, Indonesia^s PISA science score average is still well below the Organization for Economic Cooperation and Development (OECD) average. PISA data has a high data complexity and has multicollinearity, so it requires appropriate statistical methods in conducting analysis. Unfortunately, it is still very rare to conduct research quantitatively. The group LASSO method is one of methods that can be used to select groups of variables that affect science literacy in Indonesian PISA while overcoming multicolliearity. The results of the analysis showed that there were 11 groups of explanatory variables that affect the Indonesia^s PISA science score with an RMSE value of 25.00 and an R2 value of 0.31. This means that only 31% of the variance of the average science score can be explained by the explanatory variables, while the rest is explained by other factors outside the study. Keywords: Group lasso- Multicollinearity- Scientific literacy Share Link | Plain Format | Corresponding Author (Vera Maya Santi)

133	Mathematics	ABS-34
Multivariate Linear Mixed Models with Maximum Likelihood Method in Analyzing Indonesian PISA Data Vera Maya Santi (a*), Irsyad Hasari (a), Dian Handayani (a), Widyanti Rahayu (a) a) Program Studi Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Negeri Jakarta, Jl. Rawamangun Muka, Kota Jakarta Timur, DKI Jakarta, 13220, Indonesia *vmsanti[at]unj.ac.id Abstract Multiple linear regression is usually used to analyze data with a normal distribution response variable. The results of the PISA survey have several numerical responses so as to form a multivariate data structure. The complexity of PISA data increases when it involves random effect within the model. Multivariate mixed linear models is a model that can be used in multivariate data structures with random effects. Quantitative analysis of PISA data, especially multivariate analysis, is still very rarely studied. This article proposes to analyze the data from the PISA survey using the Maximum Likelihood parameter estimation method with the Newthon Raphson algorithm within the framework of a multivariate mixed linear models. The results of the analysis show that the level of education, parental education, internet access, cellphones, books and e-books, student behavior, kindergarten entry age, and class stay during elementary school are factors that affect the scores of mathematical literacy, reading literacy and science literacy simultaneously. Random effect also exert significant effect based on model diagnostic criteria including multivariate normal residual and heteroscedasticity Keywords: Diagnostic model- PISA score- Multivariate Linear Mixed Models- Newthon-Raphson- random effect Share Link | Plain Format | Corresponding Author (Vera Maya Santi)

134	Mathematics	ABS-41
Rough Rings, Rough Subrings, and Rough Ideals Fakhry Asad Agusfrianto Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Universitas Negeri Jakarta Abstract The basic concept in algebra which is set theory can be expanded into rough sets. Basic operations on the set such as intersection, union, differences, and complements can still apply to rough sets. Furthermore, one of the applications of rough sets is the use of rough matrices in decision-making. Furthermore, researchers of mathematics or informatics who work on rough sets connect the concept of rough sets with algebraic structures (groups, rings, and modules) so that a concept called rough algebraic structures is obtained. Because research related to rough sets is mostly carried out at the same time, different concepts related to rough sets and rough algebraic structures are obtained. In this paper, another definition of the rough ring and rough subring will be given. Furthermore, examples and theorems related to rough rings and rough subrings will be given. Furthermore, based on the definition of the rough ring and rough subring that has been previously defined, the definition of the left ideal and the right ideal of the rough ring will be given. Furthermore, an example will be given regarding rough ideals. Finally, will be shown the rough ideal-related theorem. Keywords: Rough Sets, Rough Rings, Rough Subrings, Rough Ideals Share Link | Plain Format | Corresponding Author (Fakhry Asad Agusfrianto)

135	Mathematics	ABS-46
Estimating the Resultant Efficacy of the Rollout of Multiple Vaccines in a Population Hanna Rhae Lyssa Improso (a), Rachelle Sambayan (a), Ma. Cristina Bargo (a), Jose Ernie Lope (a) (a) Institute of Mathematics, University of the Philippines Diliman Abstract A modified SEIR model with vaccination is employed to model the scenario when different vaccine brands with different efficacy rates were administered to the subsets of the population. The resultant efficacy rate of the different vaccines is determined and then used to estimate the fraction of the population that needs to be vaccinated to attain herd immunity. The population is compartmentalized based on the administered vaccine brand and the SEIR model with vaccination is implemented on each of the compartments under the assumption that members of the different compartments can freely interact with each other. To obtain an estimate of the resultant vaccine efficacy, the total infected individuals of the different compartments are compared to that of an uncompartmentalized population with a single vaccine whose efficacy is yet to be estimated. Various scenarios are explored by varying the number of compartments, initial conditions, and vaccine rollout rates, and the resultant efficacy is computed by minimizing the residual sum of squares of the number of infected individuals over a certain period. The results suggest a formula for the resultant vaccine efficacy in terms of the population of the compartments but independent of the vaccine rollout rates. Keywords: COVID-19 pandemic, SEIR model with vaccination, vaccine efficacy Share Link | Plain Format | Corresponding Author (Hanna Rhae Lyssa Dugang Improso)

136	Mathematics	ABS-72
Fine-Grained Sentiment Analysis on PeduliLindungi Application Users with Multinomial Naive Bayes-SMOTE Imam Suyuti (a*), Dewi Retno Sari S. (b) a) Sebelas Maret University, Indonesia b) Sebelas Maret University, Indonesia Abstract The Key Social Disability Policy (PSBB) requires highly mobile people to use the PeduliLindungi application. One application has several reviews from positive and negative users. Review data can be labeled with two types of emotions: negative sentiment and positive sentiment. Fine-grained sentiment analysis is a type of sentiment analysis that can be used to identify user reactions. One method of sentiment analysis is Multinomial Naive Bayes. In this research, we used Multinomial Naive Bayes to perform fine-grained sentiment analysis for users of the PeduliLindungi application. The data used is from the Google Play store. The sentiment class labeling results for the PeduliLindungi review data resulted in 9021 reviews, including a total of 6244 negative reviews and 2777 positive reviews. This research uses a data-sharing model that divides 80% of training data and 20% of test data. Many data imbalances for the two sentiment classes can be overcome by using the SMOTE method. SMOTE has been shown to improve classification accuracy more effectively than non-SMOTE, as applying SMOTE has been shown to improve the performance of imbalanced data. The proper classification method used to classify PeduliLindungi^s user ratings is Multinomial Naive Bayes-SMOTE, which has the highest AUC value. Keywords: Data Reviews, Fine-Grained Sentiment Analysis, Multinomial Naive Bayes, SMOTE. Share Link | Plain Format | Corresponding Author (Imam Suyuti)

137	Mathematics	ABS-103
Analysis of the Qanda Mathpresso Question Queuing System Model Using^s Max-Plus Interval Algebra Ardhan Arbyantono ^1)*, Siswanto ^2) Departement of Mathematics, Faculty of Mathematics and Natural Sciences, Sebelas Maret University, Surakarta, Indonesia. ^1) Corresponding author: ardhanchocho[at]student.uns.ac.id. ^2) Electronic mail: sis.mipa[at]staff.uns.ac.id. Abstract The problem of eigenvalues and eigenvectors is an important component associated with a square matrix. In max-plus algebra, a square matrix can be expressed in the form of a graph called a communication graph. Qanda mathpresso is a global education platform that provides data and connects education with equal educational opportunity. In this study, we discuss the analysis of the qanda mathpresso question queuing system model using max-plus interval algebra. This research is based on the expansion of the concept of max-plus algebra into interval max-plus algebra. The discussion includes how to determine the eigenvalues and eigenvectors for the max-plus interval algebra of a matrix in general, how to build a matrix based on field study data, how to apply the eigenvalue and eigenvector problems for interval max-plus algebra in the Qanda mathpresso question queue system. . At the end, it is explained about the periodic analysis of questions that appear in the Qanda Mathpresso application. From this analysis, it is hoped that it will make it easier for questioners who are queuing to know when it is time to get answers to the questions asked and can provide time efficiency. Keywords: Communication Graph, Eigenvalues and Eigenvectors, Qanda Mathpresso. Share Link | Plain Format | Corresponding Author (Ardhan Arbyantono)

138	Mathematics	ABS-116
THE EXISTENCE OF SOLVING SYSTEM OF LINEAR EQUATIONS IN MIN-PLUS ALGEBRA Hanifa Fauziah Nurrahma1*, Siswanto2 1,2 Department of Mathematics, Faculty of Mathematics and Natural Sciences, Sebelas Maret University, Surakarta, 57126, Indonesia *Email address: hanifafauziahnurrahma[at]student.uns.ac.id Abstract Max-plus algebra was first written in Kleene about neural networks and automata. Max-plus algebra is the set R&#8746-{-&#8734-}, where R is the set of all real numbers denoted by the operations &#8853- and &#8855- defined as maximum and addition. Max-plus algebra can be used to model and analyze simple production systems, with a focus on the analysis of system input-output problems. Modeling and analyzing a network with the max-plus algebra approach can provide analytical results and is easier to compute. In addition to max-plus algebra, have mentioned several algebraic variants that are similar to max-plus algebra, one of which is min-plus algebra. As in max-plus algebra by approaching, min-plus algebra is also expected to solve related problems and can be modeled and related calculations can be done more analytically. In this study, we will discuss the min-plus algebra linear equation system which will be carried out by analyzing and conducting experiments on the equations already contained in max-plus algebra when implemented into min-plus algebra. Keywords: Min-Plus Algebra, Min-Plus Algebra Linear Equation System Share Link | Plain Format | Corresponding Author (Hanifa Fauziah Nurrahma)

139	Mathematics	ABS-117
The Group Lasso-Ridge Hybrid Method to Selection of Variables for Smoker in Jambi Province Rini Warti (a*), Khairil Anwar Notodiputro (b), Bagus Sartono (b) a) Mathematics Education Department, UIN Sulthan Thaha Saifuddin, Jambi, 36363, Indonesia * riniwarti[at]uinjambi.ac.id b) Statistics Department, IPB University, Bogor, 16680, Indonesia Abstract The 2018 RISKESDAS report by the Health Research and Development Agency at the Indonesian Ministry of Health states that the number of smokers in Indonesia tends to increase yearly. Even the prevalence of smokers over the age of 15 is relatively high, with the number of smokers at 33.8%. Many factors influence people to smoke. The factors observed consisted of 14 groups and 30 variables. One method used to select variables in group form is the Group Lasso. This study aimed to determine a predictor variable from a binary response variable using the Group Lasso-ridge hybrid method for smokers in Jambi Province. The data was taken from the 2017 Indonesian Demographic and Health Survey (IDHS), classifying smokers into two categories (smoking or not). Data analysis consists of two stages. The results showed that of the 30 predictor variables used in the first stage, 18 variables were selected that affected people^s smoking, with a predictive performance score of 68.09. All variables selected in step one will use in the second stage. In stage two, there are five variables were set that influenced people to smoke from the 18 variables used, with a predicted performance score of 74.99 Keywords: Group Lasso, Group Lasso-ridge hybrid, Smoker, Variable selection Share Link | Plain Format | Corresponding Author (Rini Warti)

140	Mathematics	ABS-125
Weakly Linear Independent and Gondran-Minoux in Semiring Min-plus Interval Izmah Ashfayel Hikmah Department of Mathematics, Faculty of Mathematics and Natural Science, University of Sebelas Maret Surakarta, Indonesia Abstract In linear algebra it is known semiring min-plus or R_min, with R is the set of all real numbers with the minimum operation and the addition operation. Research related to min-plus algebra and its application has been developed by several researchers. The development of min-plus algebra, is also known as interval min-plus algebra. The purpose of this research is to determine the concept of linearly dependent and weakly linear independent, Gondran-Minoux, tropical, and the relationship between them in the semiring min-plus interval. Based on Rosenmann^s research, max-plus algebra and min-plus algebra are isomorphic. Using the appropriate analogy in the semiring max-plus interval we will define the concepts of Gondran-Minoux linear independent and tropical linear independent in the semiring min-plus interval. The results show that if a set of P is tropical linearly independent, then P also linearly independent in Gondran-Minoux, if a set P is linearly independent in Gondran-Minoux, then P is also weakly linearly independent, and if a set P is tropically independent, then P is also weakly linearly independent. Keywords: Min-plus interval algebra- linear freedom- Gondran-Minoux- tropical Share Link | Plain Format | Corresponding Author (Izmah Ashfayel Hikmah)

141	Mathematics	ABS-126
Important variables in the classification of divorce cases of married couples in Central Jakarta using the Random Forest Method Dania Siregar (a*), Bintang Mahesa (b), Ahmad Syauqi Baihaqy (c), Liswatun Naimah (d), Qorry Meidianingsih (e) Statistics Study Program, Universitas Negeri Jakarta *dania-siregar[at]unj.ac.id Abstract The Central Jakarta is located in the heart of the capital which is very strategic. It is the center of the city, government, history, tourism, elite malls and close access to various buffer areas of Jakarta. With this variety of facilities in the Central Jakarta, it does not guarantee perpetuity in domestic life. The divorce rate in the region since 2017 has been steadily increasing. The interesting thing is that the divorce lawsuit filed also comes more from the wife than from the husband^s divorce lawsuit. There are various factors that trigger this divorce lawsuit. These factors include continuous disputes and quarrels, economic factors and domestic violence. However, this factor certainly cannot be separated from the individual background of the married couple such as age, occupation, level of education, and length of marriage. The purpose of this study is to determine the level of importance of the variables used to classify the divorce of married couples in the Central Jakarta area using the Random Forest method. This method is able to classify with high accuracy. Random Forest is a development of the CART (Clasification and Regression Tree) method by applying bootstrap aggregating (bagging) and random feature selection methods. The results of this study obtained that the independent variables such as the age of the plaintiff, are the most important variables, followed by the defendant^s work, the age of the defendant and the work of the plaintiff. The accuracy of the classification of divorce for wife lawsuits reaches 89% and divorced husband lawsuits 77%. Keywords: Divorce, Variables importance, Random Forest Share Link | Plain Format | Corresponding Author (Dania Siregar)

142	Mathematics	ABS-136
Jump Diffusion Model for Stock Market price of Small and Medium-Size Enterprises Hasna Afifah Rusyda (a*), Lienda Novianty (a), Fajar Indrayatna (a) a) Department of Statistics, Padjadjaran University Jl. Raya Sumedang Km. 21 *hasna.afifah[at]unpad.ac.id Abstract The challenging process in modelling asset prices is dealing with the characteristic data that are dynamics and non-Gaussian. Especially, some data of certain stocks have jump. Therefore, a model that can handle such fluctuating data is needed. This study aims to predict and market the market^s prices accurately using Jump-Diffusion Model that can capture sudden, extreme changes during the research period. Keywords: Jump Diffusion, Merton Model, Risk, Expected Shortfall Share Link | Plain Format | Corresponding Author (Hasna Afifah Rusyda)

143	Mathematics	ABS-149
Sentiment Analysis of JakLingko Public Transportation Program Using Support Vector Machine Faroh Ladayya, Dania Siregar, Hilmy D. Muchtar, Wiligis E. Pranoto Universitas Negeri Jakarta, Jakarta Timur, 13220, Indonesia Abstract As a metropolitan city with high mobility, public transportation plays an important role in facilitating economic, business and government activities in DKI Jakarta. DKI Jakarta provincial government launched the JakLingko program to create an integrated, convenient, efficient, and affordable public transportation system. Knowledge of public opinion can help improve the service quality of the JakLingko program. The use of social media is becoming very popular nowadays. Through social media, anyone can easily express their opinion about an issue. It is used to obtain objective and latest public opinion. Sentiment analysis is a method that can be used to analyze public opinion. Through sentiment analysis whose data was collected from Twitter, it can be seen how the public opinion toward JakLingko program. In this study, public sentiment will be classified into positive sentiment or negative sentiment. As for the classification, the Support Vector Machine (SVM) algorithm is used. The results of the classification of public sentiment about the JakLingko program using SVM show good accuracy performance. In addition, a visualization in the form of a word cloud is also displayed for each positive and negative sentiment. Keywords: Jaklingko- Sentiment Analysis- Support Vector Machine Share Link | Plain Format | Corresponding Author (Faroh Ladayya)

144	Mathematics	ABS-159
SELECTION OF VARIABLES BASED ON NONCONCAVE PENALIZED LIKELIHOOD USING LASSO, ELASTIC NET, AND SCAD METHOD Femmy Diwidian (1*), Khairil A Notodiputro (2), Bagus Sartono (2) (1) UIN Syarif Hidayatullah Jakarta (2) IPB University *Corresponding author: femmy.diwidian[at]uinjkt.ac.id Abstract Variable selection is an essential topic in linear regression analysis to improve predictability and to select significant variables. Estimating the regression coefficient on high-dimensional data cannot be done using the least squares method, so it requires specific analytical techniques. Approaches that can take on high-dimensional data include SCAD, LASSO, and Elastic Net. This research will analyze the most crucial method between SCAD, LASSO, and Elastic Net on Low Birth Weight (LBW) data in East Nusa Tenggara (NTT). Two methods are used in this study, first, comparing the SCAD, LASSO, and Elastic Net methods using simulation data, and the second applying the logistic regression method to actual data. The data used in this study is the LBW data by fertile women in NTT from the 2017 IDHS (Indonesian Demographic and Health Survey) data. The analysis shows that the results obtained through simulation and data reveal that SCAD is better than the other methods. Keywords: Variable Selection, Nonconcave penalized likelihood, LASSO, Elastic net, Share Link | Plain Format | Corresponding Author (Femmy Diwidian)

145	Mathematics	ABS-160
Transpose of a Module Relative to its Nonzero Submodule Yudi Mahatma (a*), Ibnu Hadi (a), Sudarwanto (a) a) Program Studi Matematika, FMIPA, Universitas Negeri Jakarta Jalan Rawamangun Muka Raya RT 11/RW 14, Pulo Gadung, Jakarta Timur 13220, Indonesia *yudi_mahatma[at]unj.ac.id Abstract Let K be algebraically closed field and A be finite dimensional K-algebra. It has been shown that any right A-module M admits projective cover and thus admits a minimal projective presentation that induces the transpose of M. In 2017, Mahatma and Muchtadi-Alamsyah introduced the notion of the U-projective resolution which is the generalization of the concept of projective resolution. Let M be right A-module and U be nonzero submodule of M. Using the idea of U-projective resolution, we define the minimal U-projective presentation of M that induces the transpose of M relative to U. We investigate some properties of the modified transpose. Keywords: algebraically closed field- algebra- minimal projective presentation- transpose Share Link | Plain Format | Corresponding Author (Yudi Mahatma)

146	Mathematics	ABS-164
Evaluation of Naive and Covariance Algorithms in Generalized Linear Models (GLMs) Khalilah Nurfadilah (a*), Khairil Anwar Notodiputro (b), Bagus Sartono (b) a) UIN Alauddin Makassar JL. HM Yasin Limpo No. 36 Makasar, Indonesia * khalilahnurfadilah1202[at]gmail.com b) Departemen Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Institut Pertanian Bogor Institut Pertanian Bogor, Jalan Raya Dramaga, Bogor, 16680, Indonesia Abstract One of the important aspect in modeling is the simplicity of the model itself. Simplification of the model can be done by several methods, including the Ridge regression, LASSO and Elastic Net. In selecting the variables in these models an algorithm is developed, namely Naive and Covariance. Previous research revealed that the Covariance algorithm is superior in terms of time compared to the Naive algorithm. This is then evaluated by applying models and algorithms to male sex behavior data with the criteria of goodness, namely the simplicity of the model and the minimum AIC value. Based on the results of the study, it was found that the Covariance algorithm still outperformed the Naive algorithm in all three models. Keywords: Covariance- Elastic Net- LASSO- Naive, Ridge Regression1 Share Link | Plain Format | Corresponding Author (Khalilah Nurfadilah)

147	Mathematics	ABS-165
Evaluation of Naive and Covariance Algorithms in Generalized Linear Models (GLMs) Khalilah Nurfadilah (a*), Khairil Anwar Notodiputro (b), Bagus Sartono (b), Vera Maya Santi (c), Rini Warti (d) a) UIN Alauddin Makassar JL. HM Yasin Limpo No. 36 Makasar * khalilahnurfadilah1202[at]gmail.com b) Departemen Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Institut Pertanian Bogor Institut Pertanian Bogor, Jalan Raya Dramaga, Bogor, 16680, Indonesia c) Departemen Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Negeri Jakarta Jalan Rawamangun Muka, Kec. Pulo Gadung, Daerah Khusus Ibukota Jakarta, 13220, Indonesia d)Program Studi Tadris Matematika UIN Sulthan Taha Syaifuddin Jambi Jalan Jambi-MA Bulian KM. 16 Muaro Jambi, Indonesia Abstract One of the important aspect in modeling is the simplicity of the model itself. Simplification of the model can be done by several methods, including the Ridge regression, LASSO and Elastic Net. In selecting the variables in these models an algorithm is developed, namely Naive and Covariance. Previous research revealed that the Covariance algorithm is superior in terms of time compared to the Naive algorithm. This is then evaluated by applying models and algorithms to male sex behavior data with the criteria of goodness, namely the simplicity of the model and the minimum AIC value. Based on the results of the study, it was found that the Covariance algorithm still outperformed the Naive algorithm in all three models Keywords: Covariance- Elastic Net- LASSO- Naive, Ridge Regression1 Share Link | Plain Format | Corresponding Author (Vera Maya Santi)

148	Mathematics	ABS-178
GRAPH REPRESENTATION ON GROUP OF MATRICES INTEGERS MODULO PRIME Ibnu Hadi (a*), Devi Eka Wardani Meganingtyas (a**), Yudi Mahatma (a***) a) Program Studi Matematika, FMIPA, Universitas Negeri Jakarta *) ibnu_hadi[at]unj.ac.id **) deviekawm[at]unj.ac.id ***) yudi_mahatma[at]unj.ac.id Abstract Given a group of matrices integers modulo. This group has many properties in group theory. In this paper, we will investigate on matrices using prime number start with 2 and 3. Here we show some properties in group theory related with graph concept Keywords: matrices integers modulo prime, group theory, graph theory Share Link | Plain Format | Corresponding Author (Ibnu Hadi)

149	Mathematics	ABS-183
Application of the Vector Error Correction Model in Analyzing the Relationship of Macroeconomic Indicators in Indonesia Widyanti Rahayu, Amalia Syafira, Bagus Sumargo Universitas Negeri Jakarta, Jakarta 13220 Abstract National economic growth is a benchmark in an effort to achieve public welfare. In practice, national economic growth can be measured by several macroeconomic indicators, such as the JCI, Inflation, BI Rate, Exchange Rate, and Export Value. In analyzing the short-term and long-term relationship of these economic indicators, it can be done by using the Vector Error Correction Model (VECM). VECM can also be used to see the dynamic impact or response of a variable to shocks from other variables in the model by using the Impulse Response Function (IRF). Then the Variance Decomposition (VD) can be used to describe the contribution of each variable in the long-term relationship. VECM is used when there is cointegration among the variables in the model. From the analysis of the JCI, export value, exchange rate, inflation, and BI rate, there are 4 cointegration relationships that occur in the model. After performing the optimal lag test, the appropriate model is the VECM(1) &#8203-&#8203-model. The results of the IRF analysis are 25 graphs, where each graph describes the response of a variable to shocks from other variables. With the analysis of Variance Decomposition, the result is that the BI rate is the most dominant variable that affects the exchange rate. Keywords: BI Rate, JCI, export value, inflation, exchange rate, cointegration, VECM Share Link | Plain Format | Corresponding Author (Widyanti Rahayu)

150	Mathematics	ABS-187
Local Antimagic Vertex Coloring of Amalgamation of Path Graph Devi Eka Wardani Meganingtyas*, Ibnu Hadi, Yudi Mahatma, Nadilla Okta Permitasari, Mulyana State University of Jakarta *deviekawm[at]unj.ac.id, ibnu_hadi[at]unj.ac.id, Yudi_Mahatma[at]unj.ac.id Abstract Graph labeling and coloring is one of the research developments in the field of graphs. The local antimagic labeling on graph G with |V| vertices and |E| edges is defined to be an assignment f: E -> {1,2,...,|E|} so that weights of any two adjacent vertices u and v are distinct. Therefore, any local antimagic labeling induces a proper vertex coloring of G whthe vertex u is assigned the color w(u). The local antimagic chromatic number is the minimum number of colors taken over all colorings induced by local antimagic labelings of G. In this paper, we present the local antimagic chromatic number of path graph operation, especially the type of graph operation is amalgamation. Keywords: local antimagic coloring, vertex coloring, path, graph operation Share Link | Plain Format | Corresponding Author (Devi Eka Wardani Meganingtyas)

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