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ARRUS Journal of Mathematics and Applied Science
ISSN : 27767922     EISSN : 28073037     DOI : https://doi.org/10.35877/mathscience.v1i1
Core Subject : Science, Education,
Aim: To drive forward the fields related to Applied Sciences, Mathematics, and Its Education by providing a high-quality evidence base for academicians, researchers, scholars, scientists, managers, policymakers, and students. Scope: The focus is to publish papers that are authentic, original, and plagiarism free and should in interest of society and the world.
Arjuna Subject : Umum - Umum
Articles 73 Documents
Description of Students' Critical Thinking Skills in Solving Open Ended Problems Based on Their Learning Style Rosidah; Sabri; Nur Ilmi
ARRUS Journal of Mathematics and Applied Science Vol. 1 No. 2 (2021)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience641

Abstract

This study aims to know the description of students' critical thinking skills in solving mathematical problems through open-ended questions investigated on the base of learning styles. The study is descriptive research employing a qualitative approach. There were six research subjects, namely, two students with visual learning styles, two students with auditory learning styles, and two students with kinesthetic learning styles. The instruments used were written tests, a questionnaire, and an interview guide. The results showed that the students with a visual learning style were able to fulfil indicators at the stages of providing simple explanations, building basic skills, arranging strategies and tactics, and drawing conclusions. Further, the students with an auditory learning style were less able to fulfil indicators at the stages of providing simple explanations. They were not able to fulfil indicators at the stage of managing strategies and tactics, as well as drawing conclusions; yet, they were able to fulfil indicators at the stage of building basic skills. And, the students with a kinesthetic learning style were less able to fulfil indicators at the stage of providing simple explanations; moreover, they were not yet able to fulfil indicators at the stages of building basic skills, managing strategies and tactics, as well as drawing conclusions.
Effectiveness of Jigsaw Type II Cooperative Learning Model in Improving Self-Efficacy, Activities, and Learning Outcomes of STKIP Pembangunan Indonesia Makassar Students Nur Indah Sari; Fandi Ahmad
ARRUS Journal of Mathematics and Applied Science Vol. 2 No. 1 (2022)
Publisher : Lembaga Penelitian dan Pengembangan Teknologi dan Rekayasa, Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience714

Abstract

The main purpose of this study was to determine whether the Jigsaw II Cooperative learning model was effective in increasing the self-efficacy of Indonesian Development STKIP students, in the Learning Assessment course. This research is a quasi-experimental research. The population in this study were all students of Biology Education Study Program Semester IV (four) academic year 2020/2021 Even Semester STKIP Indonesian Development Makassar. The samples used are two classes that have the same initial ability, namely classes IVA and IVC. The reason for choosing the IVA class as the control class and the IVC class as the experiment. The data collection technique in this study used a pretest-posttest control group design model. Data analysis was carried out using description analysis, N-Gain test, prerequisite test and hypothesis testing with the help of SPSS 17. Based on the test results, it was found that the application of the Jigsaw Cooperative Learning Model Type II was quite effective in increasing self-efficacy with the percentage of Ngain 61%, student learning activities of 90% which means very effective and learning outcomes obtained by the percentage of Ngain 56% which means quite effective.
Development of R Package for Regression Analysis with User Friendly Interface Arfan Shalihin Amir; Muhammad Arif Tiro; Ruliana
ARRUS Journal of Mathematics and Applied Science Vol. 2 No. 1 (2022)
Publisher : Lembaga Penelitian dan Pengembangan Teknologi dan Rekayasa, Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience728

Abstract

The use of pirated software in Indonesia is quite high compared to other countries in the world. One of the efforts made to reduce the level of software piracy is to develop publicly licensed software such as R software which is open source software. The preparation of this package uses the R software and other additional packages, especially packages for regression analysis. Making this package can make it easier for users to perform regression analysis easily and legally. This package is named SLR App (Simple Linear Regression App) and MLR App (Multiple Linear Regression) which are regression analysis packages that have a user friendly interface. From the tests carried out that this package has similarities from the results of the analysis between the SLR App and MLR App.
Numerical Solution of the Mathematical Model of DHF Spread using the Runge-Kutta Fourth Order Method Syafruddin Side; Ahmad Zaki; Miswar
ARRUS Journal of Mathematics and Applied Science Vol. 2 No. 2 (2022)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience745

Abstract

This research was conducted to find a numerical solution to the mathematical model of DHF in Makassar using the Runge-Kutta fourth order method. The mathematical model of DHF is in the form of a system of differential equations that includes variables S (Susceptible), E (Exposed), I (Infected), and R (Recovery) simplified into classes of vulnerable (S), exposed (E), infected (I) and cured (R) as initial value. Parameters value that is solved numerically using the Runge-Kutta fourth order method with time intervals h = 0.01 months using data from South Sulawesi Provincial Health Service in 2017. Based on the initial value of each class, namely: obtained (Sh1) =10910.4, (E) = 0, (Ih1) = 177.9 , (Sv1) = 5018685.6, (Iv1) = 135.4, and R = -981612.3. The initial values ​​and parameter values ​​are substituted into numerical solutions to the model simulated using maple as a tool.
Analysis of Stock Portfolio Optimization in the Telecommunications Sector Using the Single Index Model Irwan Irwan; Muhammad Abdy; Nurul Khofifah Salsabila; Ansari Saleh Ahmar
ARRUS Journal of Mathematics and Applied Science Vol. 3 No. 1 (2023)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience1734

Abstract

The purpose of this study was to determine the optimal portfolio in the telecommunications sector listed on the Indonesia Stock Exchange based on the Jakarta Composite Index for the period January 2018–December 2020 using the Single Index Model. This type of research is an applied research. This type of research is applied research with secondary data obtained from the Indonesia Stock Exchange, Yahoo Finance, and Bank Indonesia. The number of samples taken is 5 stocks, namely TLKM, ISAT, EXCL, BTEL, and FREN. Based on the results of the analysis of the 5 stocks that are members of the JCI, the combination of 2 stocks that make up the optimal portfolio, namely ISAT and FREN, produces an expected return of 5.08% with a risk of 8.02%.
Cluster Analysis of New Students at STKIP Pembangunan Indonesia during the COVID-19 Pandemic Based on Regional Origin Sutamrin; Khadijah; Isma Muthahharah
ARRUS Journal of Mathematics and Applied Science Vol. 3 No. 1 (2023)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience1740

Abstract

This study aims to determine the distribution of origins of prospective new STKIP Pembangunan Indonesia students during the COVID-19 pandemic based on the student's name, religion adopted, chosen study program, and sources of information on new student admissions. The method used is clustering with a total sample of 27 regions in Indonesia. In this study, 3 clusters were formed, namely cluster 1 which had the most students with members namely East Jakarta, East Kalimantan, Gowa, Maros, Takalar, Bantaeng, Manggarai, West Manggarai, East Flores, West Sumba. Cluster 2 has not too many (moderate) prospective students with members namely Makassar, Barru, SInjai, Bulukumba, Soppeng, Enrekang, Jeneponto, Selayar, Polewali Mandar, East Maggarai. Cluster 3 has the fewest prospective students with members namely Makassar, Barru, Sinjai, Bulukumba, Soppeng, Enrekang, Jeneponto, Selayar, Polewali Mandar, East Maggarai
Cluster Analysis Using Ensemble ROCK Method in District/City Grouping in South Sulawesi Province based on People's Welfare Indicators Taufiq Hidayat; Ruliana Ruliana; Zulkifli Rais; Miguel Botto-Tobar
ARRUS Journal of Mathematics and Applied Science Vol. 3 No. 1 (2023)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience1761

Abstract

Cluster analysis is a data mining technique used to group data based on the similarity of attributes of object data. One of the problems that are often encountered in cluster analysis is data with a mixed categorical and numerical scale. The clustering stage for mixed data using the ensemble ROCK (Robust Clustering using links) method is carried out by combining clustering outputs from categorical and numeric scale data. The method used for categorical data is the ROCK method and the method used for numerical data is the Hierarchical Agglomerative method. The best clustering method is determined based on the criteria for the ratio between the standard deviations within the group (SW) and the smallest standard deviation between groups (SB). Based on 24 observation objects in the regencies and cities of the Province of South Sulawesi, the ROCK ensemble method with a value of 0.1 produces three clusters with a ratio value of 2,27 x10-16 based on the combination of the output results of the ROCK method and the Hierarchical Agglomerative method
K-Prototype Algorithm in Grouping Regency/City in South Sulawesi Province Based on 2020 People's Welfare Muhammad Refaldy; Suwardi Annas; Zulkifli Rais
ARRUS Journal of Mathematics and Applied Science Vol. 3 No. 1 (2023)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience1763

Abstract

Clustering is something that is used to analyze data in machine learning, data mining, pattern engineering, image analysis, and bioinformatics. To produce the information needed for a data analysis using the clustering process, this is because the data has a large variety and amount. Researchers will use the K-Prototype method where this method becomes an efficient and effective algorithm in processing mixed-type data. The K-Prototype algorithm has problems in finding the best number of clusters. So, in this paper, researchers will conduct research by finding the best number of clusters in the K-Prototype method. There are many ways to determine this, one of which is the Elbow method. The determination of this method is seen from the SSE (Sum Square Error) graph of several number of clusters. The results of the clustering formed 2 clusters which were considered optimal based on the value of k that experienced the greatest decrease. The results showed that Cluster 1 is a cluster that has characteristics of people's welfare which is better than Cluster 2
Analysis of Learning Difficulties for Students of MAN 2 Makassar Nadya Maharani Vega; Annisa Anugrah Damaiyanti; A. S. Muhammad Arhamar; Agung Wijaya Ami; Saparuddin Saparuddin
ARRUS Journal of Mathematics and Applied Science Vol. 3 No. 1 (2023)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience1768

Abstract

One of the causes of the decline in the quality of education is the large number of students who experience learning difficulties. The purpose of this study was to determine the learning difficulties experienced by students in class XI MAN 2 Makassar. The aspects observed in learning difficulties at MAN 2 Makassar include learning motivation, learning media, learning processes, use of learning tools, as well as learning support facilities and facilities. This study uses a quantitative approach using a survey method research type. The population in this study were students from class XI MIPA at MAN 2 Makassar and the sample in this study were students from MAN 2 Makassar class XI MIPA 1 and MIPA 2 with a total of 53 participants. The data collection technique uses a survey which contains 30 questions developed based on aspects of learning difficulties and distributed via the Google form. The results showed that the learning difficulties of students in class XI MIPA at MAN 2 Makassar in the aspect of learning motivation had a moderate categorization with an index of 55.07%, low learning media with an index of 79.4%, a low learning process with an index of 74%, the use of learning tools low with an index of 66.7% and learning support facilities and facilities which are classified as low with an index of 66.1%.
Analysis of Students' Self-Confidence in Class XI MIPA Learning at UPT SMAN 1 Gowa Herman, Magfira; Asfiana, Asfiana; Fadillah, Nurfatin; Ayuningtyas, Herlianty Tri Dimas; Saparuddin, Saparuddin
ARRUS Journal of Mathematics and Applied Science Vol. 3 No. 1 (2023)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience1776

Abstract

This study uses a descriptive research approach with quantitative methods. It was carried out at UPT SMAN 1 Gowa with a population of XI MIPA student consisting of 8 classes. The research sample consisted of 36 people who were randomly selected. The instrument used was a student self-confidence questionnaire with 30 items, which measured indicators of self-confidence, assertiveness, responsibility, and positive thinking. Attitude data that was originally ordinal in nature was processed using Microsoft Excel with the Successive Interval (MSI) method, turning it into interval data. After processing the data, analysis and classification are carried out based on the percentage of the attitude scale. The results showed that the level of self-confidence of class XI MIPA students at UPT SMAN 1 Gowa as a whole was low. The percentage of the indicator of self-confidence is 66% in the low category, the percentage of the indicator of assertiveness is 67.33% which is also low, the percentage of the indicator of responsibility is 70% which is in the medium category, and the percentage of the indicator of positive thinking is 69% which is also low. Although the indicator of being responsible has the highest percentage, overall all indicators of student self-confidence are in the low category, especially the indicator of self-confidence.