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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) Zero : Jurnal Sains, Matematika, dan Terapan Cakrawala: Jurnal Litbang Kebijakan PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat 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 Limits: Journal of Mathematics and Its Applications

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 Public Health Social Sciences Transportation Other

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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%.

ESTIMATING THE CONCENTRATION OF NO2 WITH THE COKRIGING METHOD IN THE CAPITAL CITY OF JAKARTA Saifudin, Toha; Faiza, Atikah; Puspasari, Laili; Nurrohmah, Zidni 'Ilmatun
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 4 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss4pp1985-1996

The increase in transportation activities is the leading cause of the emergence of the air pollution risk, which harms public health. especially in big cities. Nitrogen Dioxide (NO2) gas is one of the critical factors explaining air pollution. NO2 contributes to particle pollution and acid deposits and is a precursor of ozone, the leading cause of photochemical smog. Meanwhile, Sulfur Dioxide (SO2) is another substance that is a source of pollutants and can cause acid rain and aerosolized sulfate particle pollution. Therefore, it is necessary to estimate the concentration of pollutants, especially NO2. One method that can be used in this estimation is Cokriging, which considers secondary variables to record primary variables. Based on the results obtained, the Cokriging analysis shows that the estimation of NO2 content in the five predicted areas, namely Tanjung Priok, Johar Baru, Gelora Bung Karno, Pancoran, Halim Perdanakusuma, has a quality standard value below 80 µppm (quality standard value set by the BMKG). In summary, the research unveils variations in SO2 and NO2 levels across distinct regions in Jakarta, with Monas recording the highest SO2 levels (10 μppm), while Grogol exhibits the lowest NO2 levels (16 μppm). The average SO2 level among all surveyed areas is 5.875 μppm, while NO2 averages 17.375 μppm. These findings emphasize the pressing need to implement measures aimed at preserving air quality within the limits established by government standards. Additionally, Cokriging estimates reveal that the content of NO2 in Tanjung Priok, a coastal area, significantly deviates from estimations in other Jakarta areas and ranks as the highest among the locations studied, with GBK displaying the lowest content.

COMPARISON OF POISSON REGRESSION AND GENERALIZED POISSON REGRESSION IN MODELING THE NUMBER OF INFANT MORTALITY IN WEST JAVA 2022 Saifudin, Toha; Salsabila, Fatiha Nadia; Fitriani, Mubadi'ul; Kholidiyah, Azizatul; Auliyah, Nina; Ariani, Fildzah Tri Januar; Suliyanto, Suliyanto
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp35-50

In line with the Sustainable Development Goals (SDGs), the Infant Mortality Rate (AKB) is a very important health indicator, especially in neonatal and perinatal care. West Java Province consistently ranks third nationally in terms of infant mortality in 2020 and 2021. This study analyzes the factors influencing infant mortality in West Java in 2022 using secondary data from the 2022 West Java Provincial Health Profile. The response variable is the number of infant deaths, while the predictor variables include the percentage of K-4 coverage (X1), high-risk pregnancy (X2), family with PHBS (X3), exclusive breastfeeding (X4), and complete immunization coverage (X5). Given the count-based nature of the data, Poisson regression was used, which assumes equidispersion where the variance is equal to the mean. However, the analysis found overdispersion, where the variance significantly exceeds the mean, making Poisson regression unsuitable. To address this, Generalized Poisson Regression (GPR) was applied, as GPR introduces a dispersion parameter that accounts for overdispersion, thus better fitting the data. The initial Poisson regression results showed that X1, X2, X4, and X5 significantly influenced infant mortality, while the GPR model showed that only X2 and X3 were significant factors, with a dispersion parameter of -3.116. The GPR model shows that every additional one high-risk pregnancy increases the infant mortality rate by 1.00006, while an increase of one unit of clean and healthy living practices reduces the mortality rate by 2.66%. Model evaluation using AIC, BIC, and RMSE confirmed that the GPR model better described the relationship between predictor variables and infant mortality rates compared to Poisson regression. These findings emphasize the need to use GPR to model cases with overdispersion in count data, so as to provide more reliable information for policy and intervention strategies.

MODELING CHRONIC FILARIASIS CASES IN WEST JAVA USING A MULTIVARIATE ADAPTIVE APPROACH REGRESSION SPLINES Kurniawan, Ardi; Firmansyah, Mochammad; Saifudin, Toha
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 2 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss2pp1249-1260

One of the most crippling infectious diseases in the world is filariasis. Indonesia is a unitary country with 34 provinces, where West Java is one of the 5 provinces with the most filariasis sufferers in Indonesia as of 2021. Reinfection occurs in places that have implemented POMP. Therefore, monitoring operations must be carried out to track the emergence of new cases and risk factors for transmission. The aim of this research focuses on describing and modeling the number of chronic filariasis in West Java, as well as interpreting the best model results obtained. The method used is a method with a nonparametric regression approach, namely Multivariate Adaptive Regression Spline. The results of the research show that the best model obtained is a combination of 15 base functions, maximum interaction 2, and minimum observation between knots 1. From this model, the predictor variable that has the most influence on the response variable in order based on the level of variable importance is the Percentage of Population Access to Facilities Decent Sanitation, Percentage of Households with Clean and Healthy Behavior (PHBS), Sex Ratio, and Percentage of Poor Population. The interpretation of the best model is that the variable Percentage of Population Access to Adequate Sanitation Facilities above 6,650% will contribute to a reduction in the number of chronic filariasis; the Sex Ratio variable below 103,300 will contribute in the form of a reduction in the number of chronic filariasis. it can be seen that the predictor variable that has the most influence on the response variable is the variable Percentage of Population Access to Proper Sanitation Facilities with an importance level of 100%.

Co-Authors Abdul Aziz Aditya Syarifudin Akbar Adyatma, Isryad Yoga Afifa, Fitriana Nur 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 Andini Putri Mediani Angga Kusuma Bayu Viargo Aniq Atiqi Any Tsalasatul Fitriyah Ardi Kurniawan Ardi Kurniawan Ariani, Fildzah Tri Januar Ariyawan, Jovansha Arrofah, Aini Divayanti Aulia, Niswa Faizah Auliyah, Nina Ayuning Dwis Cahyasari Azis, Aurelia Islami Azizah, Khansa Baihaqi, Mochamad Belindha Ayu Ardhani Budijono, Gabriella Agnes 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 Fauzi, Doni Muhammad 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 Januarta, R. Arya Khairian, Farhan Aldan Kholidiyah, Azizatul Leni Sartika Panjaitan Lensa Rosdiana Safitri M. Fariz Fadillah Mardianto Maelcardino Christopher Justin Mahadesyawardani, Arinda Maharani, Prima 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 Pratama, Fachriza Yosa Purnama, Titania Faisha Puspasari, Laili Rahayu, Rizky Dwi Kurnia Ramadhani, Azzah Nazhifa Wina 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 Sentosa, Martha Ayu Setyawan, Muhammad Daffa Bintang Shalwa Oktavrilia Kusuma Siagian, Kimberly Maserati Sihite, Rivaldi 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 Zhafira, Azizah Atsariyyah

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