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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
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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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

Abstract

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

Abstract

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

Abstract

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%.
TRAINING ON USE OF USER-FRIENDLY R-SHINY PROGRAM FOR DETERMINING NUTRITIONAL STATUS OF TODDLERS AT POSYANDU IN THE WORKING AREA OF THE SOBO BANYUWANGI COMMUNITY HEALTH CENTER Chamidah, Nur; Kurniawan, Ardi; Saifudin, Toha; Easyfa Wieldyanisa, Ezha; Insania Dewanty, Sanda; Azizah, Khansa
Jurnal Layanan Masyarakat (Journal of Public Services) Vol. 9 No. 3 (2025): JURNAL LAYANAN MASYARAKAT
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/.v9i3.2025.406-418

Abstract

Stunting is a form of malnutrition that serves as an important indicator for monitoring the growth and development of toddlers. However, assessing the nutritional status of toddlers does not stop at stunting, but includes a comprehensive understanding of the child's nutritional condition in real time, especially by mothers who have toddlers. Although the prevalence of stunting in Indonesia has decreased, achieving the target reduction to 14% by 2024 still requires significant efforts. This community service activity aims to improve the nutritional literacy and technical skills of posyandu cadres and mothers of infants in utilizing a user-friendly R-Shiny-based application, both in web and Android versions. This application allows users to input anthropometric data of infants (weight-for-age, height-for-age, and BMI-for-age), and then automatically generates growth charts based on reference standards. The activity was conducted in a hybrid format on June 29, 2024, with a total of 69 participants (35 offline cadres and 34 online cadres). Evaluation results showed a significant increase in cadres' knowledge, with an average post-test score (76.81) higher than the pre-test score (71.66) and a p-value from the paired t-test of 0.008. Additionally, participants gave high satisfaction scores, with an average above 75 on all indicators. The program also provides intensive mentoring and long-term monitoring to ensure smooth application use. With a data-driven approach sensitive to regional characteristics, this program is expected to serve as an innovative, sustainable, and replicable community service model in other areas to accelerate stunting reduction efforts.
MODELING DEMOCRACY INDEX IN INDONESIA WITH MULTIVARIATE ADAPTIVE REGRESSION SPLINE APPROACH Saifudin, Toha; Suliyanto, Suliyanto; Nugraha, Galuh Cahya; Valida, Hanny; Nahar, Muhammad Hafidzuddin; Fortunata, Regina
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 4 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss4pp2347-2358

Abstract

Democracy is a system of government where citizens participate in political decision-making through freely elected representatives. To measure the quality of democracy in Indonesia, the Indonesian Democracy Index (IDI) is used as a composite indicator reflecting various aspects of political freedoms, civil liberties, and governance. The IDI score declined from 6.71 in 2022 to 6.53 in 2023, the lowest in 14 years, indicating disruption in Indonesia’s democracy. Therefore, it is necessary to identify the root causes of the disruption in Indonesia’s democracy through several indicators. This study analyzes the relationship between predictor variables, including socio-economic and development indicators, and IDI using the Multivariate Adaptive Regression Spline (MARS) approach. This study uses the MARS method by considering six predictor variables, namely the Human Development Index (HDI), Gender Empowerment Index (GEI), Information and Communication Technology Development Index (ICT-DI), Press Freedom Index (PFI), Poverty Depth Index (PDI), and High School Completion Rate (HSCR). The data used is secondary data from 34 Indonesian provinces in 2023 obtained from the Statistics Indonesia-BPS. The results showed that the best model was obtained with a combination of BF = 12, MI = 3, and MO = 1 resulting in a GCV value of 11.27 and R2 of 80%. MARS model interpretation identifies the significant influence of social and economic indicators on IDI and is able to explain 80% of data variability. The significance test shows that all predictor variables significantly affect the IDI, with the highest level of importance on the ICT-DI variable. Therefore, improving ICT-DI in each province needs to be a major concern as a strategic step to improve the democracy index in Indonesia and support the achievement of Sustainable Development Goal 16 on peace, justice, and strong institutions.
PREDICTION OF NATURAL GAS PRICES ON THE NEW YORK MERCANTILE EXCHANGE BASED ON A PULSE FUNCTION INTERVENTION ANALYSIS APPROACH Sediono, Sediono; Saifudin, Toha; Dewanti, Maria Setya; Azis, Aurelia Islami
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 4 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss4pp2647-2660

Abstract

Natural gas is a key energy commodity with significant global economic impact, and its pricing is influenced by factors like weather, energy policies, geopolitics, and supply-demand balance. The Russia-Ukraine conflict disrupted Russia’s gas exports, causing price volatility and affecting global markets, including Indonesia. This has heightened the need for accurate price prediction to support policy and investment decisions. Previous studies show ARIMA-GARCH models predict well but need pulse function intervention for sudden shocks. This study aims to apply pulse function intervention analysis, which captures the immediate effects of external events on time-series data, to improve the precision of natural gas price forecasts, aiding government and industry decision-makers. The optimal intervention model for predicting natural gas prices on the New York Mercantile Exchange is the Probabilistic ARIMA (0,2,1) with a pulse function intervention order of b=0, r=2, and s=0. Using this model with the pulse function intervention approach yields consistent fluctuation patterns over time and achieves a MAPE value of 12.2586%, indicating that the model provides good predictive accuracy.
Platelet Modeling in DHF Patients Using Local Polynomial Semiparametric Regression on Longitudinal Data Utami, Tiani Wahyu; Chamidah, Nur; Saifudin, Toha
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 1 (2024): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i1.17427

Abstract

Regression analysis is one of the statistical methods used to model the relationship between response variables and predictor variables. Semiparametric regression is a combination of parametric and nonparametric regression. The estimator used in estimating the semiparametric regression model in this research is the Local Polynomial. Longitudinal data can be found in the health sector, including dengue hemorrhagic fever (DHF) data. The laboratory criteria for indication of DHF is thrombocytopenia. This research aims to obtain platelets model for DHF patients that can be used for forecasting so that it is hoped that it can provide information to the medical team in treating DHF patients. The estimated model used is Local Polynomial semiparametric regression on longitudinal data. The response variables in this research were platelets of DHF patients, which were influenced by hemoglobin as parametric predictor variable and examination time while hospitalized as nonparametric predictor variable. In the local polynomial regression model, it is necessary to select the optimal bandwidth and polynomial order method, GCV. The optimum bandwidth selection based on the GCV method obtained is 1.5 and polynomial order of 2, then applied to DHF patient platelet data, producing an estimated local polynomial semiparametric regression model that follows the actual data pattern. Modeling the platelets of DHF patients obtained using a local polynomial estimator resulted in an R2 value of 84.25% and MAPE of 4.5%, indicating highly accurate forecasting, so it can be concluded that the resulting model is better at predicting.
Mapping Food Insecurity: Spatial Modelling of Undernourishment Prevalence in Indonesia using Geographically Weighted Regression Saifudin, Toha; Chamidah, Nur; Ramadhina, Fidela Sahda Ilona; Al Hasri, Ilham Maulana; Trisa, Nadya Lovita Hana; Valida, Hanny; Setyawan, Muhammad Daffa Bintang
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 4 (2025): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i4.32063

Abstract

Undernourishment is a major global issue, with significant impact observed in Indonesia. A method of assessing the prevalence of energy deficiency resulting from inadequate nutrition is through the Prevalence of Undernourishment (PoU) index. From 2019 to 2022, Indonesia's PoU increased gradually, reaching 10.21% in 2022, indicating growing undernourishment and unstable food availability. This study aims to utilize Geographically Weighted Regression (GWR) to identify and analyze the factors contributing to undernourishment. The data were obtained from the Central Bureau of Statistics (BPS) in 2024, covering 38 provinces in Indonesia. This study examined six factors: per capita spending, access to potable water, mean years of schooling, access to adequate sanitation, college participation rate, and mean food expenditure. The findings show that the GWR model outperformed the conventional model, demonstrating greater explanatory power by accounting for 96.1% of the spatial variation in undernourishment and achieving the lowest AIC value of 176.7052. These findings highlight the need for region-specific food security policies, particularly in eastern Indonesia. The results can inform targeted government interventions and guide future spatial econometric research on food security.
IMPROVING EDUCATION AND DETERMINING THE NUTRITIONAL STATUS OF TODDLERS IN REALIZING NUTRITION-CONSCIOUS FAMILIES IN BANYUWANGI USING R-SHINY Chamidah, Nur; Kurniawan, Ardi; Saifudin, Toha; Sa'idah, Andini; Widyawati, Ayu; Fajrina, Sofia
Jurnal Layanan Masyarakat (Journal of Public Services) Vol. 8 No. 1 (2024): JURNAL LAYANAN MASYARAKAT
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jlm.v8i1.2024.061-073

Abstract

Stunting is a condition where a child's development and growth is disturbed, which has long-term impacts, including the potential for impaired brain development due to insufficient cognitive development and a greater risk of developing chronic diseases such as diabetes, hypertension, obesity, cancer, and so on. One effort to reduce stunting rates is to increase knowledge of nutrition awareness in the family. UNAIR Statistics Study Program, participates in efforts to reduce stunting rates with community service activities (Pengmas), in the form of outreach activities regarding basic and practical knowledge in the form of workshops and training activities using R-Shiny based WEB and Android to determine the nutritional status of toddlers which can used anywhere and anytime. This community service activity was carried out in the working area of "‹"‹the Tampo Community Health Center, Banyuwangi, East Java, involving 62 female cadre representatives from 31 local posyandu. The results of this community service activity can increase knowledge regarding education and nutrition knowledge for toddlers in the context of achieving nutrition-aware families. This is proven by the results of statistical analysis of pre-test and post-test scores which conclude that there is an increase in scores from pre-test to post-test with a significance level of 5%. Based on the results of the feedback questionnaire given to participants, the posyandu cadre mother felt very satisfied with an average score of 86, gained useful knowledge, and made it easier for posyandu cadres to find out the nutritional status of toddlers.
Local Polynomial Estimator in The Nonparametric Model of Inflation in Indonesia Aziz, Abdul; Chamidah, Nur; Saifudin, Toha
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 1 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i1.27625

Abstract

Inflation is a general and continuous increase in prices of goods and services over a certain period.  Nonparametric regression analysis can be used to model inflation data that does not form a particular pattern. This study applies a local polynomial nonparametric method to model the rate of change rate in the inflation over a period considering two factors influencing inflation: the rate of change in the BI interest rate and the rate of change rate in the money supply from the previous period. The bivariate local polynomial method estimates the nonparametric regression function by considering the optimum Gaussian kernel bandwidth and polynomial order using the Taylor series expansion and WLS estimator. The optimal local polynomial nonparametric regression model was obtained based on a minimum GCV value of  0.015108 with two optimum Gaussian kernel bandwidth values of 0.1 and 0.03 in polynomial order of 1. The best model had a MAPE value of 3.45%, showing that all the prediction models were highly accurate. The benefits gained are additional information and consideration for determining monetary policy, especially inflation in Indonesia, by determining the BI interest rate and money supply.
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