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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Abdimas Talenta : Jurnal Pengabdian Kepada Masyarakat BAREKENG: Jurnal Ilmu Matematika dan Terapan Justek : Jurnal Sains Dan Teknologi Saintifik : Jurnal Matematika, Sains, dan Pembelajarannya M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika Math Educa Journal Imajiner: Jurnal Matematika dan Pendidikan Matematika JURNAL PEMBELAJARAN DAN MATEMATIKA SIGMA (JPMS) Proximal: Jurnal Penelitian Matematika dan Pendidikan Matematika Journal of Computer Networks, Architecture and High Performance Computing Journal of Research in Mathematics Trends and Technology Asimetris: Pendidikan Matematika dan Sains FARABI: Jurnal Matematika dan Pendidikan Matematika Leibniz: Jurnal Matematika Humantech : Jurnal Ilmiah Multidisiplin Indonesia Journal of Mathematics and Scientific Computing With Applications Jurnal Pijar MIPA Quadratic: Journal of Innovation and Technology in Mathematics and Mathematics Education Journal of Technology and Computer (JOTECHCOM) Jurnal Pengabdian Mitra Masyarakat Jurnal Jendela Matematika
Widyasari, Rina
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APPLICATION OF THE MONTE CARLO METHOD IN PREDICTING THE NUMBER OF BUDGET PROPOSALS ACCEPTED IN NORTH SUMATRA PROVINCIAL HEALTH OFFICE Harahap, Riska; Siahaan, Maharani Putri Adam; Widyasari, Rina
Journal of Mathematics and Scientific Computing With Applications Vol. 5 No. 1 (2024)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v5i1.873

Abstract

A budget is a planning tool regarding future expenditure and revenues, generally prepared for one year. The prediction simulation for approved budget proposals is an estimate of the calculation of the approval rate for approved proposals in the following year. This research uses the Monte Carlo method in solving problems. This method can be used in problems with nonlinear boundary conditions, namely prediction limits.the author uses a quantitative descriptive method, which is a form of research that focuses on the facts and characteristics of the research object by combining related variables. This research uses the Monte Carlo method uses random numbers and probability statistics to solve problems.The data used to predict the approved proposal budget is the budget proposal data that is approved each year. The following is one of the approved proposal data, namely the approved budget proposal data from 2021, 2022 and 2023 budget proposals received using the Monte Carlo Method which has been implemented at the North Sumatra Provincial Health Service with the simulation namely with an average percentage in 2022 of 84% and in 2023 by 76%. So with the successful application of the Monte Carlo Method to predict the number of budget proposals received at the North Sumatra Provincial Health Service for 2024 it will provide convenience for the North Sumatra Provincial Health Service to find out what the predicted number of budget .
Pengklasifikasian Variabel-Variabel Yang Mempengaruhi Terjadinya Stunting di Kota Medan dengan Metode Chi-Square Automatic Interaction Detection (CHAID) Rakhmawati, Fibri; Arianti, Mei Yunina; Widyasari, Rina; Cipta, Hendra
Asimetris: Jurnal Pendidikan Matematika dan Sains Vol. 4 No. 2 (2023): Asimetris: Jurnal Pendidikan Matematika dan Sains
Publisher : Pendidikan Matematika Universitas Almuslim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51179/asimetris.v4i2.2303

Abstract

Tujuan penelitian ini adalah pengklasifikasian dan menganalisis faktor mana yang sangat berepengaruh terhadap kejadian stunting di Kota Medan menggunakan metode CHAID. Metode CHAID ini bekerja dengan mengidentifikasi hubungan antara variabel dependen dan independen lalu menggunakan hubungan ini untuk mengklasifikasikan sampel. Hasil penelitian menunjukkan bahwa faktor-faktor yang berpengaruh pada kejadian stunting terhadap bayi usia 24-59 bulan di Kota Medan berdasarkan hasil analisis metode CHAID adalah Riwayat Pemerian ASI Eksklusif dan Sanitasi. Dari hasil analisis metode CHAID diperoleh tiga pengklasifikasian berbeda yaitu: (1) Bayi usia 24-59 bulan yang mengalami stunting sangat pendek adalah bayi dengan keadaan Riwayat Pemberian ASI Eksklusif tidak diberikan sebesar 54% dan sanitasi tidak layak sebesar 66,7%. (2) Bayi usia 24-59 bulan yang mengalami stunting adalah bayi dengan keadaan Riwayat Pemberian ASI Eksklusif tidak diberikan sebesar 54% dan sanitasi layak sebesar 25% dan (3) Bayi usia 24-59 bulan yang tidak mengalami stunting sangat pendek adalah bayi dengan keadaan Riwayat Pemberian ASI Eksklusif diberikan 23%. Sehingga hasil temuan penelitian ini diharapkan memberikan masukan kepada pihak terkait dalam mengantisipasi terjadinya kasus stunting dengan mengklasifikasi factor-faktor mana saja yang sangat mempengaruhi kasus stunting ini.  
SIMULASI PENGENDALIAN PERSEDIAAN ALAT TULIS KANTOR PADA DINAS PERKEBUNAN DAN PETERNAKAN PROVINSI SUMATERA UTARA DENGAN METODE MONTE CARLO Sari, Rina Filia; Aprilia, Rima; Widyasari, Rina; Afnaria, Afnaria; Suhaimi, Syech; Putri, Chindy Aulia
Jurnal Pengabdian Mitra Masyarakat Vol 3, No 2 (2024): Edisi Maret
Publisher : Universitas Islam Sumatear Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/jurpammas.v3i2.9284

Abstract

In a Government Agency, office stationery supplies are an absolute necessity. The provision of adequate office stationery will facilitate performance. This study aims to predict the demand for office stationery using Monte Carlo Simulation. Monte Carlo is a numerical analysis method that uses random number samples. The data used in this study are primary data in the form of the number of stock items and the number of requests for goods from January to December 2023. The accuracy result using the Monte Carlo method for Year 2024 is 91.78%. This shows that the Monte Carlo method simulation can be used to predict the demand for stationery for the following year.
Penerapan Regresi Logistik Biner Pada Faktor-Faktor Perceraian di Kota Medan Fitriani, Fitriani; Cipta, Hendra; Widyasari, Rina
FARABI: Jurnal Matematika dan Pendidikan Matematika Vol 8 No 2 (2025): FARABI: Jurnal Matematika dan Pendidikan Matematika
Publisher : Program Studi Pendidikan Matematika FKIP UNIVA Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47662/farabi.v8i2.1243

Abstract

Divorce is a court decision on the termination of a marriage. Divorce brings with it a negative impact, especially on the children of the couple's marriage. Children who are victims of divorce tend to be prone to feeling afraid, sad, guilty to trigger stress and depression in children which then has a bad impact on relationships during the child's growth and development. Therefore, it is necessary to conduct an analysis to find out the factors of divorce. In this research, the analysis used is binary logistic regression with the response variables in the binary category of divorce, namely “cerai talak” and “cerai gugat”. While the stimulus variables in this study were 13 objects obtained based on secondary data documentation of Courts. The results of this research are obtained five factors that have a significant effect, namely age at marriage and profession of who filing for divorce and divorce defendant, as well as the education of who filing for divorce. The interpretation of the results of binary logistic regression analysis shows that, the age of divorced defendant at the time of marriage has a 1,15 times greater effect on the cerai gugat, while the age of who filed for divorce has a 0.68 times greater effect on the cerai talak. Keywords: Divorce, Factors, Binary Logistics Regression
Peramalan Pertambahan Pasien Rawat Inap dengan Menggunakan Model Support Vector Regression (SVR) Wati, Ririn Indah; Sari, Rina Filia; Widyasari, Rina
Imajiner: Jurnal Matematika dan Pendidikan Matematika Vol 8, No 3 (2026): Imajiner: Jurnal Matematika dan Pendidikan Matematika
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/imajiner.v8i3.26830

Abstract

This research aims to see the prediction of the number of patients at the Medan Haji General Hospital in 2022-2023. A hospital is a health service institution that provides complete individual health services, providing inpatient, outpatient and emergency services. In implementing health services, hospitals must maintain medical records to support services and process patient information. This hospital serves all types of groups around North Sumatra. Prediction is the process of forecasting future demand which will include demand in terms of quantity, quality, time and location to meet demand for goods, services or the environment. This research uses the Support Vector Regression (SVR) method. Support Vector Regression (SVR) is a learning system that applies linear functions to a hypothetical feature space with high dimensions. The SVR algorithm concept can produce good forecasting values because SVR has the ability to solve overfitting problems. Overfitting is data behavior during the training phase that results in almost perfect prediction accuracy. Based on the results of data processing using the Support Vector Regression (SVR) method, it can be concluded that the application of the forecasting method in predicting the number of inpatient visits at RSU Haji Medan using the SVR method is carried out by determining predictions using three kernels, namely the RBF, linear and polynomial, then determine the best MSE and RMSE values to then be used as the best kernel. The results of forecasting inpatient visits using the SVR method show that the predicted results have decreased from the previous actual data which is not much different, but the predicted number of inpatients is almost the same every month and experiences insignificant decreases and increases.Keywords: Prediction; Support Vector Regression (SVR).
Co-Authors Afnaria, Afnaria Afrina Sinaga, Serly Andayani Arianti, Mei Yunina Batubara, Fikri Husin Dongoran, Raisha zuhiara Dongoran, Rodiani Fairuz, Ersya Nurul Fitriani Fitriani Giawa, Freddy Ginting, Iren Salsalina Br Harahap, Riska Hendra Cipta Hsb, Sumawiyah Ismail Husein, Ismail Jonathan Liviera Marpaung Kartika , Dinda Kinanti, Tri Maisarah Maisarah, Maisarah Marlina, Wenni Melati, Melati Puspita Sari Lubis Muhammad Alfi Syahri Harahap Nasution, Dafa Al Qifti Nasution, Mutiah Novi Ardila Novia, Ayu Novianti Nurainun, Umi Sarah NURUL QOMARIYAH Parapat Gultom Pertiwi, Fina Nur Pratiwi, Ria Widiya Purbowati, Septi Putri, Chindy Aulia Rakhmawati, Fibri Rambe, Feby Mayori Rima Aprilia Rina Filia Sari, Rina Filia Riningsih, Novia Riri Syafitri Lubis Rizkina, Ayu Sajaratud Dur, Sajaratud Salasa Riana, Dwi Sarah, Henny May Sari, Elviana Sembiring, Tesya Yunita Siahaan, Maharani Putri Adam Siregar, Agung Lesmana Siregar, Anggi Ramadany Siregar, Machrani Adi Putri Suhaimi, Syech Sunanda, Bona Dea Susilowati, Rahmi Suyanto Syafitriani Syahfitri Lubis, Riri Wati, Ririn Indah Yuda, Muhammad Wira