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All Journal MATEMATIKA JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Ilmu Sosial dan Humaniora CAUCHY: Jurnal Matematika Murni dan Aplikasi Matematika dan Sains Journal of Information Systems Engineering and Business Intelligence Prosiding SI MaNIs (Seminar Nasional Integrasi Matematika dan Nilai-Nilai Islami) Syntax Literate: Jurnal Ilmiah Indonesia MUST: Journal of Mathematics Education, Science and Technology BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Limits: Journal of Mathematics and Its Applications Zero : Jurnal Sains, Matematika, dan Terapan Cakrawala: Jurnal Litbang Kebijakan Jurnal Aplikasi Statistika & Komputasi Statistik JP2M (Jurnal Pendidikan dan Pembelajaran Matematika) G-Tech : Jurnal Teknologi Terapan Inferensi Contemporary Mathematics and Applications (ConMathA) Jurnal Keselamatan Transportasi Jalan (Indonesian Journal of Road Safety) Jurnal Layanan Masyarakat (Journal of Public Service) PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS Jurnal Keselamatan Transportasi Jalan

Toha Saifudin

Departement Of Mathematics, Faculty Of Science And Technology, Airlangga University

Author-ID : 2388908

Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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MODELLING MATHEMATICS LEARNING OUTCOMES USING A MULTIPREDICTOR SEMIPARAMETRIC REGRESSION APPROACH BASED ON SPLINE ESTIMATOR Purnama, Titania Faisha; Chamidah, Nur; Saifudin, Toha
JP2M (Jurnal Pendidikan dan Pembelajaran Matematika) Vol 11, No 1 (2025)
Publisher : Universitas Bhinneka PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jp2m.v11i1.6999

Education is one of the points of Indonesia's SDGs which is stated in goal number 4. Mathematics is one of the subjects that contributes to the realizing national education goals. In the independent curriculum, the success of the learning process at school can be seen from the criteria for achieving learning objectives. In this article, we analyzed students’ mathematics learning outcomes using a multi predictor semiparametric regression approach and interpreted the results with Spline estimator. The results shows that the differences between the types of classes greatly influence outcomes in learning mathematics, where social classes experienced a decrease of 2.435 percent compared to science classes. To increase outcomes in learning mathematics, the percentage of learning motivation must be more than 88 percent. Apart from that, high or low IQ cannot determine whether students’ mathematics learning outcomes. Furthermore, by combining linear and nonlinear components in the model effectively, the overall accuracy based on the MAPE value is 7.87 percent, so that the model can be predict the actual value high accurately. Thus, the multi predictor semiparametric regression approach based on spline estimator can explain the mathematics learning outcomes model very well.

Gender Equality in Indonesian Employment: Multivariate Adaptive Regression Spline (Mars) Analysis Dita Amelia; Toha Saifudin; Suliyanto Suliyanto; Aditya Syarifudin Akbar; Muhammad Rosyid Ridho Az Zuhro
Jurnal Ilmu Sosial dan Humaniora Vol 13 No 2 (2024)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jish.v13i2.76687

Based on data from the Central Bureau of Statistics, laborers in Indonesia, men are still more dominant for a career in the world of work. This contradicts the prevailing regulations, where gender equality is also a government development priority in realizing equitable development. This study aims to identify the factors that influence the percentage of women who work in Indonesia. The Multivariate Adaptive Regression Spline (MARS) Method is suitable for extensive data and can model relationships of interactions between various variables. The variables analyzed were the average wage of female workers, gross regional domestic product at constant prices, female workers with at least a high school education, life expectancy, provincial minimum wage, and female workers who are heads of households. Based on the research results, the best model was obtained with a coefficient of determination of 90.8%. Some influential variables in the base function are Minimum Wage for Female Workers, Female Workers with at least a high school education, Life Expectancy, and Female Workers who are Heads of Families. Based on the significant basis functions, the function that appears the most is Basis Function 5, which contains the predictor variable Average Wage of Female Workers, which shows a positive relationship with the Percentage of Female Workers with Labor Status in Indonesia. Meanwhile, based on the importance of the predictor variables, the top two are Female Workers with at least a high school education and Female Workers who are Heads of Households.

LEPROSY CASE MODELING IN EAST JAVA USING SPATIAL REGRESSION WITH QUEEN CONTIGUITY WEIGHTING Saifudin, Toha; Rifada, Marisa; Makhbubah, Karina Rubita; Ramadhanty, Devira Thania
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp2141-2154

Leprosy, a highly contagious disease caused by the bacterium Mycobacterium leprae, can result in permanent disability if left untreated. It remains a significant public health issue in many regions, particularly tropical countries like Indonesia. Despite ongoing control efforts, incidence rates are still high in some areas. In 2023, East Java had the highest number of leprosy cases in Indonesia, with 2,124 out of 7,166. To understand the factors contributing to these cases, this study explores various influences and offers policy recommendations to reduce leprosy in East Java. The study uses spatial modeling with a weighting scheme based on queen contiguity, selected because leprosy spreads through human interactions and movement, creating spatial dependencies. It examines spatial, social, economic, educational, and environmental factors based on cross-sectional data from 38 regencies/cities in East Java for 2023. Among the regression models tested, the spatial error regression model proved most effective, showing an R-Square value of 67.14% and an AIC of 213.023. Key findings identified () average years of schooling and () healthcare worker ratios as significant factors influencing leprosy cases. These results aim to guide policymakers in developing stronger leprosy control strategies and offer a basis for further research in East Java.

COMPARISON OF LEAST SQUARE SPLINE AND ARIMA MODELS FOR PREDICTING INDONESIA COMPOSITE INDEX Fitriyah, Any Tsalasatul; Chamidah, Nur; Saifudin, Toha
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp2169-2178

The Indonesian Composite Index (ICI) reflects Indonesia's economic growth. ICI predictions are significant considerations for investors when making investment decisions. Two approaches can be used to predict ICI: parametric and nonparametric approaches. Therefore, this study compares parametric and nonparametric approaches to predict ICI. In its application, the parametric approach requires several assumptions to be met, such as linearity. This differs from analysis with a nonparametric approach that does not require certain assumptions. The parametric approach in this study uses the ARIMA model. ARIMA is widely used to predict time series data. In the nonparametric approach, in this study, we used nonparametric regression based on the least square spline. Spline is chosen because it can handle data that tends to fluctuate by placing knot points when data changes occur. In this study, ICI monthly data obtained from the website investing.com was used. Investing.com is a website that financial analysts often use as a data source to monitor world economic conditions, including the ICI. The Mean Absolute Percentage Error (MAPE) value is determined to assess the accuracy of the prediction. The study results indicate that the analysis with ARIMA cannot meet the assumptions, so ARIMA modeling cannot be continued. Different results were obtained in nonparametric regression modeling based on the least square spline estimator. Prediction of ICI using nonparametric regression based on the least square spline estimator has a MAPE value of 2.613% (less than 10%), which means the model is a highly accurate prediction, meaning modeling using nonparametric regression based on the least square spline estimator is better than the ARIMA model for predicting ICI.

Modeling Prevalence of Hypertension in Indonesia with Multivariate Adaptive Regression Splines Method Suliyanto, Suliyanto; Saifudin, Toha; Naura, Sheila Sevira Asteriska; Dewanty, Sanda Insania; Wulandari, Indana Zulfa; Aflaha, Nabila Shafa; Aulia, Niswa Faizah
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 2 (2025): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i2.28392

Hypertension is one of the important public health problems in Indonesia, which contributes to the high prevalence of non-communicable diseases. This study aims to model the prevalence of hypertension in Indonesia using the Multivariate Adaptive Regression Splines (MARS) method to identify significant predictors and their interactions. The data used was secondary data from the 2023 Indonesian Health Survey, including variables such as smoking prevalence, physical inactivity, dietary habits (consumption of fatty and sweet foods), lack of fruit and vegetable consumption, and obesity prevalence. The MARS method was used to analyse the nonlinear relationships and interactions between these predictors. After a trial-and-error process to determine the optimal number of basis functions (BF), maximum interactions (MI), and minimum observations (MO), the best model was achieved with BF = 18, MI = 3, and MO = 1. This model produced a Generalised Cross Validation (GCV) value of 13.428 and R-Square of 0.278. This fairly low R-Square value indicates that the factors analysed have contributed to the variation in hypertension prevalence, but there are still other aspects that can be taken into account to improve the predictive power of the model. The significant predictor variables were consumption of fatty foods (X3), lack of physical activity (X2), and consumption of sweets (X4), with the highest importance on X3 (100%). The findings reveal that interactions between variables, such as dietary habits and physical inactivity, significantly influence the prevalence of hypertension. For example, higher consumption of fatty and sweet foods combined with low physical activity increases the risk of hypertension. These results demonstrate the effectiveness of the MARS method in capturing complex and nonlinear relationships and serve as findings that highlight the need for health policies that focus on healthy diets and increased physical activity, in line with Goal 3 of the SDGs, “Good Health and Well-Being,” which aims to reduce premature mortality from noncommunicable diseases. Recommended interventions include nutrition education campaigns and community-based exercise programs to reduce the prevalence of hypertension in Indonesia.

Prediksi Harga Emas dan Nilai Tukar Rupiah dengan Pendekatan Estimator Deret Fourier Birespon Wahyuli, Diana; Chamidah, Nur; Saifudin, Toha; Herdianto, Muhammad Hendra
Cakrawala Vol. 19 No. 1: Juni 2025
Publisher : Badan Riset dan Inovasi Daerah Provinsi Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32781/cakrawala.v19i1.777

Harga emas dan nilai tukar merupakan indikator ekonomi penting yang berdampak signifikan pada stabilitas ekonomi dan kebijakan moneter. Prediksi yang akurat dibutuhkan untuk mendukung pencapaian Sustainable Development Goals (SDGs) 8: Pekerjaan Layak dan Pertumbuhan Ekonomi, terutama dalam menjaga stabilitas pasar keuangan dan pengambilan keputusan berbasis data. Penelitian ini bertujuan untuk memprediksi harga emas dan nilai tukar menggunakan regresi nonparametrik birespon berbasis estimator deret Fourier. Metode ini dipilih karena fleksibilitasnya dalam menangkap pola tanpa asumsi bentuk fungsional tertentu. Data yang digunakan adalah data bulanan harga emas dan nilai tukar di Indonesia yang dibagi menjadi 80% insampel dan 20% outsampel selama periode Januari 2016 hingga Desember 2024, di mana satu variabel prediktor digunakan untuk memodelkan dua respon secara simultan. Model dievaluasi menggunakan Mean Absolute Percentage Error (MAPE), dengan hasil sangat akurat, sebesar 1,31%. Model ini mendukung strategi investasi dan kebijakan ekonomi di sektor keuangan.

Representasi Perseptual Mapping Masyarakat Terhadap Perbedaan Kualitas Transportasi Di Surabaya Dengan Multidimensional Scalling Syaugi Sungkar, Salman; Khairian, Farhan Aldan; Marpaung, Josua Ronaldo Davico; Hardiansyah, Fernanda Rizky; Saifudin, Toha; Ana, Elly
Jurnal Keselamatan Transportasi Jalan (Indonesian Journal of Road Safety) Vol. 12 No. 1 (2025): JURNAL KESELAMATAN TRANSPORTASI JALAN (INDONESIAN JOURNAL OF ROAD SAFETY)
Publisher : Pusat Penelitian dan Pengabdian Masyarakat (P3M)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46447/ktj.v12i1.689

Infrastructure is one of the important factors in driving economic growth, and transportation is an inseparable part of it. This research aims to assess the sustainability of transportation in Surabaya City by looking at the level of user satisfaction from four main aspects, namely speed, comfort, safety, and price. The research was conducted in 2025 by involving 32 respondents. The data was analyzed using the Multidimensional Scaling (MDS) method, which was used to map six types of transportation modes: Indonesian Railways (KAI) Local, Suroboyo Bus, motorcycle online ojek, car online ojek, TransJatim Bus, and city transportation (angkot) or wara-wiri. The results show that Suroboyo Bus obtained the highest satisfaction score from users, with an average value of 3.13. Meanwhile that, the results of MDS mapping divide transportation modes into four groups, namely The first quadrant contains KAI Local and city transportation, the second quadrant is only filled by online motorcycle taxis, the third quadrant is inhabited by online car taxis, the fourth quadrant includes two bus-based transportation modes, namely Suroboyo Bus and TransJatim Bus. This model is evaluated using stress value of 0.06650 and RLQ of 0.97611. Both values indicate that the model is classified as good and reliable to describe customer satisfaction perceptions of transportation modes in Surabaya.

Analysis of Factor Affecting Tuberculosis Cases in West Java Province Using Panel Data Regression Approach Saifudin, Toha; Aisyah, Arlisya Shafwan; Indrasta, Irma Ayu; Amelia, Dita
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 4 (2024): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i4.24795

Tuberculosis (TB) is a disease that can cause death with the largest number of sufferers after COVID-19. In Indonesia, the number of TB cases reached 724.309 cases in 2022 with the highest number 184.406 cases in West Java Province. Given this situation, Indonesia must try to achieve the health target from SDGs, namely ending the TB epidemic by 2030. Therefore, this research aims to analyze the factors that have a significant influence on the incidence of TB in Indonesia, especially in West Java Province. The research focuses on four variables: percentage of poverty, number of diabetics, number of HIV/AIDS patients, and population density. To provide a more informative analysis, this research uses a combination of cross-section and time series data from 27 regions between 2020 and 2022. So, the method used according to the type of data is panel data regression including common effect, fixed effect, and random effect models. Based on statistical tests, namely through the chow test, hausman test, and lagrange multiplier test, it was found that the best model was fixed effect with an R-squared value of 90%. The research revealed that all the studied factors significantly influence the incidence of TB cases in West Java. The results of this study are expected to help the West Java government in an effort to reduce the number of TB cases and formulate policies by reducing the percentage of poverty and population density in West Java. By ensuring the availability of health facilities such as establishing health centers in densely populated areas and counseling programs also need to be conducted to underscore the importance of TB control in West Java.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46447/ktj.v12i1.689

Spatial Modeling of Food Security Index in Central Java Using Mixed Geographically Weighted Regression Chamidah, Nur; Saifudin, Toha; Mahadesyawardani, Arinda; Fauziah, Nathania; Rahayu, Rizky Dwi Kurnia; Siagian, Kimberly Maserati; Wieldyanisa, Ezha Easyfa
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 1 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i1.25044

Central Java plays an important role in Indonesia’s food security, ranking second nationally in the 2023 Food Security Index (FSI). However, nearly 45% of its districts/cities fall below the provincial average, reflecting spatial disparities. This study applies the Mixed Geographically Weighted Regression (MGWR) method to model the factors influencing FSI in Central Java by considering global and local spatial heterogeneity. Six clusters were formed based on similar characteristics. The MGWR model identifies that the factor of households not having access to clean water has a global negative effect which contributes 0.1710 points in decreasing the FSI, while population density is the dominant local factor that has a significant negative effect on the FSI in 21 districts/cities, covering approximately 60% of the area in Central Java. The MGWR model using a fixed Gaussian kernel outperforms global regression and GWR, with the lowest AIC, highest (93.11%), and a MAPE of 1.00838%.

Co-Authors Abdul Aziz Aditya Syarifudin Akbar Aflaha, Nabila Shafa Aisharezka, Mutiara Aisyah, Arlisya Shafwan Al Hasri, Ilham Maulana Aldawiyah, Najwa Khoir Alfi Nur Nitasari Alfredi Yoani Alpandi, Gaos Tipki Ana, Elly Angga Kusuma Bayu Viargo Aniq Atiqi Any Tsalasatul Fitriyah Ardi Kurniawan Ardi Kurniawan Ariani, Fildzah Tri Januar Ariyawan, Jovansha Aulia, Niswa Faizah Auliyah, Nina Ayuning Dwis Cahyasari Azis, Aurelia Islami Azizah, Khansa Belindha Ayu Ardhani Chaerobby Fakhri Fauzaan Purwoko Christiano Ginzel, Bryan Given Christopher Andreas Dewanti, Maria Setya Dewanty, Sanda Insania Diah Puspita Ningrum Dita Amelia Dita Amelia, Dita Easyfa Wieldyanisa, Ezha Elly Ana Elly Pusporani Erfiana Erfiana Faiza, Atikah Fajrina, Sofia Falasifah, Sabrina Fatmawati Fatmawati Fauziah, Nathania Fina Insyiroh Firmansyah, Mochamad FIRMANSYAH, MOCHAMMAD Fitriani, Mubadi'ul Fortunata, Regina Gaos Tipki Alpandi Gaos Tipki Alpandi Hardiansyah, Fernanda Rizky Herdianto, Muhammad Hendra Ilma Amira Rahmayanti Indrasta, Irma Ayu Insania Dewanty, Sanda Khairian, Farhan Aldan Kholidiyah, Azizatul Leni Sartika Panjaitan Lensa Rosdiana Safitri M. Fariz Fadillah Mardianto Maelcardino Christopher Justin Mahadesyawardani, Arinda Makhbubah, Karina Rubita Marisa Rifada Marpaung, Josua Ronaldo Davico Marshanda Aprilia Marthabakti, CitraWani Mediani, Andini Putri Mochamad Rasyid Aditya Putra Muhammad Rosyid Ridho Az Zuhro Muzakki, Naufal Nahar, Muhammad Hafidzuddin Naura, Sheila Sevira Asteriska Nugraha, Galuh Cahya Nur Chamidah Nur chamnidah Nur Rahmah Miftakhul Jannah Nurdin, Nabila Nurrohmah, Zidni 'Ilmatun Oktavia, Sabrina Salsa Panjaitan, Leni Sartika Purnama, Titania Faisha Puspasari, Laili Rahayu, Rizky Dwi Kurnia Ramadhanti, Aulia Ramadhanty, Devira Thania Ramadhina, Fidela Sahda Ilona Recylia, Rien Risky Wahyuningsih Sa'idah, Andini Safitri, Lensa Rosdiana Salma Bethari Andjani Sumarto Salsabila, Fatiha Nadia Sa’idah Zahrotul Jannah Sediono, Sediono Setyawan, Muhammad Daffa Bintang Shalwa Oktavrilia Kusuma Siagian, Kimberly Maserati Siti Maghfirotul Ulyah Sugha Faiz Al Maula Suliyanto Suliyanto Suliyanto Syaugi Sungkar, Salman Tiani Wahyu Utami Trisa, Nadya Lovita Hana Ubadah, Mohammad Noufal Valida, Hanny Victory, Johanna Tania Wahyuli, Diana Widyawati, Ayu Wieldyanisa, Ezha Easyfa Wulandari, Indana Zulfa Yan Dwi

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