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All Journal Jurnal Ilmu Dasar Jurnal Gaussian BERKALA SAINSTEK AKSIOMA: Jurnal Program Studi Pendidikan Matematika UNEJ e-Proceeding Indonesian Journal of Applied Statistics BAREKENG: Jurnal Ilmu Matematika dan Terapan Vygotsky: Jurnal Pendidikan Matematika dan Matematika Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) ESTIMASI: Journal of Statistics and Its Application Majalah Ilmiah Matematika dan Statistika (MIMS) Jurnal Riset Statistika Jurnal Statistika dan Komputasi (STATKOM) Edumaspul: Jurnal Pendidikan
Mohamad Fatekurohman
Fakultas Matematika Dan Ilmu Pengetahuan Alam (FMIPA),Universitas Jember
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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NONPARAMETRIC REGRESSION MODELING USING THE SPLINE APPROACH TO STUNTING CASES IN INDONESIA Fatekurohman, Mohamat; Nur Khasanah, Siti; Setia Dewi, Yuliani
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp697-708

Abstract

Indonesia is the fourth ranked country in the world and second in Southeast Asia with the highest stunting cases of 21.6%. According to the provisions of the World Health Organization (WHO), the maximum tolerance standard for stunted toddlers is 20 percent or one-fifth of the total number of toddlers, so the stunting rate in Indonesia is still relatively high. The high stunting rate in Indonesia can affect the quality of Indonesia's human resources, so early detection and immediate management of stunted toddlers are needed. Stunting is a condition of failure to grow due to chronic malnutrition which is caused by inadequate nutritional intake for a long time, resulting in being shorter than standard. This research aims to determine several factors that influence stunting in toddlers in Indonesia using the nonparametric spline regression method with one knot, two knots, three knots and the best model is found to be the one knot model. The results of regression nonparametric spline modeling with one knot are GCV of 14.32605 and of 81.1%. From the five variables, namely toddlers receiving complete basic immunization babies receiving exclusive breast milk for 6 months , babies born receiving IMD children aged 6-23 months consuming five of the eight food groups and drink throughout the day , households having access to proper sanitation , the following results were obtained: the variable that don’t have a significant effect was toddlers receiving complete basic immunization , while the other four has a significant effect.
Model CPH untuk Menganalisis Lama Pengobatan dan Tingkat Kesembuhan Pengguna Narkoba Firdausiah, Lailatul Firdausiah; Mohamad Fatekurohman
Jurnal Riset Statistika Volume 5, No. 1, Juli 2025, Jurnal Riset Statistika (JRS)
Publisher : UPT Publikasi Ilmiah Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jrs.v5i1.6379

Abstract

Abstract. The Cox Proportional Hazards model, in the context of drug abuse, can be used to study the time required for drug users to achieve recovery and overcome addiction. Based on data from the National Narcotics Agency (BNN), the prevalence of drug abuse in Indonesia continues to increase by 24% to 28% annually. This study aims to evaluate the relationship between the duration of treatment and various factors influencing the recovery rate of drug users, such as age, gender, duration of drug use, mental condition, education level, and type of drug used. The data for this study were obtained from Yayasan Pelita Jiwa Insani for the period between 2023 and 2024, and were analyzed using the RStudio software.The results show that the mental condition of drug users has a significant effect on both the duration of treatment and the recovery rate. Users who receive support from close relatives or loved ones have a 33.66% lower risk of relapse compared to those who do not receive such support. Abstrak. Model Cox Proportional Hazards dalam konteks penyalahgunaan narkoba, dapat digunakan untuk mempelajari waktu yang dibutuhkan pengguna narkoba untuk mencapai kesembuhan dan mengatasi ketergantungan. Berdasarkan data Badan Narkotika Nasional (BNN), prevalensi penyalahgunaan narkoba di Indonesia terus meningkat antara 24% hingga 28% setiap tahunnya. Penelitian yang dilakukan bertujuan untuk mengevaluasi hubungan antara lama pengobatan, dan faktor-faktor yang mempengaruhi tingkat kesembuhan pengguna narkoba, seperti usia, jenis kelamin, durasi penggunaan narkoba, kondisi mental, tingkat pendidikan, dan jenis narkoba yang digunakan. Data dalam penelitihan diperoleh dari Yayasan Pelita Jiwa Insani dengan periode data antara tahun 2023 hingga 2024, data diolah dengan bantuan Software Rstudio. Hasil penelitian menunjukkan bahwa faktor kondisi mental pengguna narkoba memiliki pengaruh signifikan terhadap lama pengobatan dan tingkat kesembuhan. Kondisi mental yang mendapat dukungan dari orang terdekat mengurangi risiko relaps sebesar 33,66% dibandingkan dengan kondisi mental yang tidak mendapat dukungan dari orang terdekat.
GAMLSS application for modeling the level of open unemployment in East Java Maulidani, Noor Dyah; Tirta, I Made; Fatekurohman, Mohamat
Majalah Ilmiah Matematika dan Statistika Vol. 25 No. 1 (2025): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v25i1.51548

Abstract

This research analyzes the application of Generalized Additive Model for Location, Scale, and Shape (GAMLSS) using penalized spline smoothing and Rigby-Stasinopoulos (RS) algorithm for modeling open unemployment rate in East Java Province in 2022. Predictor variables in this research are labor force participation rate, average years of schooling, average wages, economic growth, and registered job vacancies. GAMLSS allows the estimation of several distribution parameters (location, scale, and shape) thereby providing a broader and more flexible approximation model. The number of parameters that can be estimated depends on the type of distribution that is suitable for the data. This research uses a penalized spline as a smoothing predictor variable for the nonparametric part. The RS algorithm is an iterative procedure developed for GAMLSS models and used to estimate model parameters efficiently. Several distributions were evaluated and Normal distribution was obtained as the most suitable with two parameters (𝜇,𝜎). The Normal distribution is chosen based on model evaluation standards Generalized Akaike Information Criterion (GAIC). The effectiveness of this model was further verified through significance test and stepwise procedure. The estimation results of the location parameter (𝜇) are modeled by economic growth, average years of schooling, and registered job vacancies with the identity link function, while the scale parameter (𝜎) is modeled by economic growth and average wage with the log link function.
FINANCIAL DISTRESS PREDICTION OF FINANCIAL SECTOR SERVICE COMPANIES ON INDONESIAN STOCK EXCHANGE USING COX PROPORTIONAL HAZARD Dwi Putra, Candra Yanuar; Fatekurohman, Mohamat; Anggraeni, Dian
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 3 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (481.275 KB) | DOI: 10.30598/barekengvol16iss3pp1105-1114

Abstract

A company that cannot compete with its competitors is likely to experience financial difficulties or commonly referred to as financial distress. Financial distress is a stage of a decline in the company's financial condition or a situation of financial difficulty that occurred before the company went bankrupt. This study aims to determine the factors that can predict a company experiencing financial distress. The factors suspected in this study include leverage, profitability, company size, free cash flow and sales growth. The method used is the Cox Proportional Hazard model. The research data is data on financial sector service companies listed on the Indonesia Stock Exchange (IDX) for 5 years of observation, namely from 2016 to 2020. Based on the results of the analysis of financial distress predictions using the Cox Proportional Hazard model, it is found that the factors that have a significant effect on predicting companies experiencing financial distress are: financial distress, namely profitability and company size.
Comparison of Arima Method and Artificial Neural Network Method to Predict Productivity Rice In Panti District Fendi Setiawan; Yuliani Setia Dewi; Mohamad Fatekurohman
Edumaspul: Jurnal Pendidikan Vol 6 No 2 (2022): Edumaspul: Jurnal Pendidikan
Publisher : Universitas Muhammadiyah Enrekang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33487/edumaspul.v6i2.4681

Abstract

Rice production is a community activity to produce rice, it is intended to maintain food security in the future. The aim of this research is to develop the best model for forecasting rice production based on ARIMA (Autoregressive Integrated Moving Averages) and ANN (Artificial Neural Network) approaches. The results will be compared with the error rate values of the ARIMA and ANN methods with the available data. The data used in this study is data on rice production in Panti District, Jember Regency. The level of forecasting accuracy produced by each forecasting method is measured by the criteria of MAPE (Mean Absolute Percentage Error), MSE (Mean Square Error) and RMSE (Root Mean Square Error). The results showed that from the forecasting method used in this study, the ARIMA (1,0,1) (1,0,2) method is the best forecasting method for the best rice harvest area in Panti District, Jember Regency with an average MAPE value is 0.05668374, MSE is 5.587553, and RMSE is 2.3638. Meanwhile, forecasting rice productivity using the ANN BP method (7,(7,3),1) is a fairly good forecasting method with an average MAPE value of 0.05703856 MSE of 4.828465, and RMSE of 2.197377. Therefore, the ARIMA model (1,0,1) (1,0,2)[12] is quite effective for predicting the amount of rice production in Panti District, Jember Regency, East Java Province for the next few years.
Development of LSLC-Based Collaborative Learning Model Learning Tools And Their Effects on Critical Thinking Skills Evi Takrimatul Ailiyyah; Pambudi, Didik Sugeng; Fatekurohman, Mohamad; Kurniati, Dian; Susanto
Vygotsky: Jurnal Pendidikan Matematika dan Matematika Vol. 6 No. 2 (2024): Vygotsky: Jurnal Pendidikan Matematika dan Matematika
Publisher : Universitas Islam Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30736/voj.v6i2.1014

Abstract

The purpose of this study is to develop collaborative learning-based learning resources and their impact on students' capacity for critical thought. This study used a combination of methods, namely development research (R&D) with Thiagarajan 4D model and experimental research. Data was collected through observations, questionnaires, tests, and interviews. The validity coefficients for the Teaching Module, worksheet, and test were 3.80, 3.80, and 3.70, respectively. Observations showed that 96% of the learning tools met practical criteria. The tools were effective, with 93% of student activities rated very good, 96% of students giving positive responses, and 85% achieving learning completion. A t-test (sig = 0.007) confirmed the collaborative learning tool based on LSLC significantly enhanced students' critical thinking skills.
Analisis Risiko Kredit Perbankan Menggunakan Algoritma K-Nearest Neighbor dan Nearest Weighted K-Nearest Neighbor Wilujeng, Dian Tri; Fatekurohman, Mohamat; Tirta, I Made
Indonesian Journal of Applied Statistics Vol 5, No 2 (2022)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v5i2.58426

Abstract

Bank is a business entity that collects public funds in the form of savings and also distributes them to the public in the form of credit or other forms.  Credit risk analysis can be done in various ways such as marketing analysis and big data using machine learning.  One example of a machine learning algorithm is K-Nearest Neighbor (KNN) and the development of the K-Nearest Neighbor algorithm is Neighbor Weighted KNearest Neighbor (NWKNN).  The K-Nearest Neighbor (KNN) algorithm is one of the machine learning methods that can be used to facilitate the classification of complex data.  The purpose of this study is to determine the results of the application of the algorithm and the comparison of the use of the KNN and NWKNN algorithms in banking credit.  The results obtained are that NWKNN is able to predict credit risk better, especially in classifying potential customers with potential losses compared to KNN. Keywords: Machine learning, KNN, NWKNN
Development of LSLC-Based Collaborative Learning Model Learning Tools And Their Effects on Critical Thinking Skills Evi Takrimatul Ailiyyah; Didik Sugeng Pambudi; Mohamad Fatekurohman; Dian Kurniati; Susanto
Vygotsky: Jurnal Pendidikan Matematika dan Matematika Vol. 6 No. 2 (2024): Vygotsky: Jurnal Pendidikan Matematika dan Matematika
Publisher : Universitas Islam Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30736/voj.v6i2.1014

Abstract

The purpose of this study is to develop collaborative learning-based learning resources and their impact on students' capacity for critical thought. This study used a combination of methods, namely development research (R&D) with Thiagarajan 4D model and experimental research. Data was collected through observations, questionnaires, tests, and interviews. The validity coefficients for the Teaching Module, worksheet, and test were 3.80, 3.80, and 3.70, respectively. Observations showed that 96% of the learning tools met practical criteria. The tools were effective, with 93% of student activities rated very good, 96% of students giving positive responses, and 85% achieving learning completion. A t-test (sig = 0.007) confirmed the collaborative learning tool based on LSLC significantly enhanced students' critical thinking skills.
Co-Authors Abduh Riski Alfian Futuhul Hadi Anak Agung Gede Sugianthara Arif, M. Ziaul Arivatus Solehah Audina, Bella Aulia, Andini Cahya Bella Audina Dian Anggraeni Dian Anggraeni Dian Atika Sofie Dian Kurniati Didik Sugeng Pambudi Dwi Putra, Candra Yanuar Dwi Putri Antika Evi Takrimatul Ailiyyah Evi Takrimatul Ailiyyah Fatmala, Siti Febriana Fendi Setiawan Firda Anisa Fajarini Firdaus Ubaidillah Firdausiah, Lailatul Firdausiah Forestryani, Veniola Hanifia, Fidiatma Foristy I Made Tirta Khan, Akhmad Safrin Sadad Khoirunnisa, Wilda Masruroh MASRUROH Masruroh Masruroh Maulidani, Noor Dyah Meisty, Ferisa Dwi Alfia Nurcholif Diah Sri Lestari Rizal, Navioer Romarizka, Cyndy Rosida, Ayu Roydatul Jamila Sholiha, Aminatus Solly Aryza SUSANTO Susanto, Susanto Tresnawanti, Dini Tutik Qomaria Wilujeng, Dian Tri Yona Eka Pratiwi Yuliani Setia Dewi Yusrillah Ihza Zianita Afni