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All Journal Journal of Mathematics Instruction, Social Research and Opinion Journal of General Education and Humanities
Kosim
Sekolah Tinggi Ilmu Komputer Poltek Cirebon
Humanities Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Application Ability of Students in Integrated Computer-Aided Numerical Analysis Learning Kosim Kosim
Journal of Mathematics Instruction, Social Research and Opinion Vol. 1 No. 1 (2022): March
Publisher : MASI Mandiri Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (347.6 KB) | DOI: 10.58421/misro.v1i1.11

Abstract

The low ability of students to apply in numerical analysis courses is a problem in this research. Integrated learning is one solution to this problem. The aim is to determine the differences in student application abilities between integrated and conventional learning. One of the computer science colleges in the Cirebon area was sampled in this study. Two groups were formed, consisting of 1 integrated study group with a total of 36 students and one conventional study group with a total of 32 students. Both groups contracted numerical analysis courses. What carried out the type of quasi-experimental research and the static group comparison randomized control group only design became the design in this study. The result is that the average value of the application ability of students who study conventionally is 80.31, while the average application ability of students who study in an integrated manner is 84.58. The application ability of students who study integrated is higher than students who study conventionally, and the ability to apply of students who study integrated is more uniform than students who study conventionally. The results of the Mann-Whitney test found that the application ability of students who studied in an integrated manner was better than those who studied conventionally.
Application of Additive Ratio Assessment (ARAS) Method for the Selection of Youth Red Cross Chairperson at SMA Negeri 1 Lebakwangi Kuningan Bayu Pangestu; Kosim; Asep Kosasih
Journal of General Education and Humanities Vol. 1 No. 2 (2022): May
Publisher : MASI Mandiri Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (419.302 KB) | DOI: 10.58421/gehu.v1i2.18

Abstract

This study aims to build a decision support system that can choose the chairman of the Youth Red Cross using the Additive Ratio Assessment (ARAS) method and to overcome the problems faced by the selection committee for the chairman of the Youth Red Cross at SMA Negeri 1 Lebakwangi Kuningan, West Java. The ARAS (Additive Ratio Assessment) method is a multi-criteria decision-making method based on ranking using the utility degree by comparing each alternative's overall index value to the optimal alternative's overall index value. The results of the research obtained are the existence of a decision support system for the election of the candidate for the chairman of the Youth Red Cross, assisting the election committee in assessing and selecting candidates for the PMR board according to the criteria. The design of a decision support system for selecting the chairman of the Youth Red Cross at SMA Negeri 1 Lebakwangi is implemented using a web-based programming language, for the predetermined assessment criteria and sub-criteria can be stored systemized, thus enabling relatively faster processing. By using this decision support system application that has been designed, the assessment and selection of candidates for the chairman of the Youth Red Cross become more accurate and more accessible because it uses computerized media so that the selection of candidates for chairman can be more neat and systematic.
Application of the Promethee II Method for Determining Road Improvement Priorities Mayang Sari; Kosim Kosim; Andika Saputra
Journal of Mathematics Instruction, Social Research and Opinion Vol. 2 No. 1 (2023): March
Publisher : MASI Mandiri Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58421/misro.v2i1.56

Abstract

The road is an infrastructure that is often passed by the community. If there is damage, it will significantly disrupt community activities; for example, road conditions become jammed. This is necessary for the Public Works and Spatial Planning Office of the City of Cirebon to handle the road repairs, but in carrying out repair planning, there are obstacles, one of which is the difficulty in determining priority for road repairs with limited funds from the center. This research decision support system using the Promethee II method aims to find accurate results that are useful in determining priority road repairs that will be selected for repair. The criteria used in this study are Section Length, Road Width, Damage Condition, Traffic Volume (LHR), and Road Access. The results of this study selected Jalan A1 as an alternative that had the highest rating level of 0.613333333, and this indicated that this road was a road that had to be prioritized for repair. The test results show that the Promethee II method can produce priority recommendations for road improvements based on the required criteria.
Recommendation System Algorithm Content-Based Filtering Method to Provide Drink Menu Recommendations Kosim Kosim; Reza Prihandi
Journal of Mathematics Instruction, Social Research and Opinion Vol. 2 No. 2 (2023): July
Publisher : MASI Mandiri Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58421/misro.v2i2.130

Abstract

Overchoice is a cognitive disorder in which people have difficulty making decisions when faced with many choices, that make the problem in this study. This over-choice phenomenon often occurs in choosing drinks in cafes and restaurants. This research aims to create a Recommendation System (RS) to assist in choosing the drink you want to order. Making a non-personalized hospital at the Mubtada Kopi cafe uses the best-rated and content-based filtering methods. The content-based filtering method tries to retrieve user preferences explicitly, asking the user to choose the preferences the user wants from the six content made before calculating the match between the user's preferences and the six contents in each item using the dot matrix formula. The results will be converted into a rating to match the best-rated hospital approach, which is made on a non-personalized basis. This rating matches the user's preferences and the Mubtada Kopi menu list items. The higher the rating, the better it matches the user's preferences. The order RS recommends with the Content-based filtering method is rosella tea, chocolate, lemon tea, blossom tea, and spice tea.
Decision Tree Methodology (C4.5) for Predicting Students' Reading Interest in the Library SMK Negeri 1 Kota Cirebon Erwanto, Muhammad; Kosim, Kosim; Riyanto, Nur Bambang; Jogo, Sukmo Banyu
Journal of Mathematics Instruction, Social Research and Opinion Vol. 4 No. 1 (2025): March
Publisher : MASI Mandiri Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58421/misro.v4i1.359

Abstract

Reading is one aspect of language skills that is actively receptive. The media used in reading is written language media. Reading is seeing and understanding the content of what is written, either spelling or pronouncing what is written. Reading activities are often socialised in education because reading is a very important activity to support teaching and learning activities at school. The facility provided by the school as a support in socialising reading activities for students is the library. Many students often utilise the SMK Negeri 1 Kota Cirebon library to carry out the borrowing process and read books there. Reading activities are an obligation that students must carry out, but students who carry out reading activities cannot be categorised as students with an interest in reading. The problem faced by the SMK Negeri 1 Cirebon City library is that it has not been able to predict or know the reading interests of students in the school library. This study uses data mining techniques with the C4.5 algorithm to predict student reading interest. This research produces rules to help SMK N 1 Cirebon City predict student reading interest in the school library. This step is done by designing a system model that uses the C4.5 algorithm to form a decision tree to produce a rule for predicting student reading interest. This research will produce valuable information about predicting student reading interest in the SMK Negeri 1 Cirebon City library using the C4.5 algorithm method.
Monte Carlo Method for Predicting Educational Service Revenue at Each Level of Education at PT. Kanaka Belajar Baratasena, Raden Radian; Mukidin, Mukidin; Kosim, Kosim; Ariatin, Adinda Rainah Lova
Journal of Mathematics Instruction, Social Research and Opinion Vol. 4 No. 3 (2025): September
Publisher : MASI Mandiri Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58421/misro.v4i3.497

Abstract

The increasing demand for education services in Indonesia has significantly influenced the growth of private tutoring businesses. PT Kanaka Belajar is a company that provides private tutoring services, yet it continues to face challenges related to revenue uncertainty and fluctuating student enrollment, which can affect financial management and increase the risk of business bankruptcy. Therefore, a reliable and accurate revenue prediction system is necessary at each level of education to estimate income for the coming year. The Monte Carlo method is a computational algorithm that uses repeated random sampling to obtain numerical results. This study applied the Monte Carlo method to forecast revenue based on historical data from 2021 to 2023. This research aims to develop a web-based revenue prediction system for educational services at different levels by implementing the Monte Carlo simulation. The results demonstrated that the model provided high prediction accuracy for private tutoring income at the elementary school level in 2023, with an MAPE value of 1.57%. The system predicted 314 tutoring sessions, while the data showed 319 sessions, resulting in a minimal difference of 5 sessions. These findings suggest that the Monte Carlo method effectively forecasts educational service revenue, where smaller percentage error values indicate higher accuracy, while larger errors suggest lower forecast reliability.
Co-Authors Andika Saputra Ariatin, Adinda Rainah Lova Asep Kosasih Baratasena, Raden Radian Bayu Pangestu Jogo, Sukmo Banyu Mayang Sari Muhammad Erwanto Mukidin, Mukidin Reza Prihandi Riyanto, Nur Bambang