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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) MATEMATIKA JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Ilmu Sosial dan Humaniora CAUCHY: Jurnal Matematika Murni dan Aplikasi TELKOMNIKA (Telecommunication Computing Electronics and Control) 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 JOURNAL OF APPLIED INFORMATICS AND COMPUTING 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) Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS Economic Development Analysis Journal Jurnal Keselamatan Transportasi Jalan Limits: Journal of Mathematics and Its Applications
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 Public Health Social Sciences Transportation Other

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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.
Pemodelan Kasus Tuberkulosis di Indonesia dengan Metode GWPR Guna Mendukung SDGs 2030 Toha Saifudin; Mochamad Firmansyah; Johanna Tania Victory; Mutiara Aisharezka
Limits: Journal of Mathematics and Its Applications Vol. 21 No. 3 (2024): Limits: Journal of Mathematics and Its Applications Volume 21 Nomor 3 Edisi No
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Tuberculosis (TB) is the second leading cause of death after coronary heart disease. The bacterium type Humanus of Mycobacterium tuberculosis causes the infectious illnessTB. According to WHO, in 2018 Indonesia had 8% of TB cases, the third highest after India (27%) and China (9%). Therefore, efforts are needed to reduce the number of cases and deaths due to TB, in line with efforts to achieve point 3 of target 3 of the SDGs, namely ending the TB pandemic. This study uses the Geographically Weighted Poisson Regression (GWPR) model approach with the aim of analyzing the factors that influence TB, so that preventive interventions to reduce TB cases can be carried out. The data used in this study is secondary data in the form of data on the number of TB cases in 2018 obtained from the Ministry of Health (Kemenkes RI) and the Central Agency of Statistics (BPS). The observation unit is 34 provinces in Indonesia. Based on the smallest Akaike Information Criteria (AIC) value, the best GWPR model is obtained with Adaptive Bisquare weighting. Each province has a different model. The GWPR model in West Java Province which has the highest number of TB cases in Indonesia is . The results of the analysis show that the number of poor people has a very significant influence in almost all provinces in Indonesia. While this is going on, a considerable impact can be seen in the proportion of unfit homes and the percentage of unsanitary food processing facilities (TPM). Provincial governments in Indonesia can consider the results of modeling with GWPR in formulating strategies to reduce the number of TB sufferers in their regions
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.
Comparison of Logistic Regression and Support Vector Machine in Predicting Stroke Risk Safitri, Lensa Rosdiana; Chamidah, Nur; Saifudin, Toha; Firmansyah, Mochammad; Alpandi, Gaos Tipki
Inferensi Vol 7, No 2 (2024)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v7i2.20420

Abstract

The issue of health is the third goal of Indonesia's Sustainable Development Goals (SDGs) which is state to ensuring a healthy life and promoting prosperity for all people at all ages. One of the SDGs’s concerns is deaths caused by non-communicable diseases (NCDs) including strokes. One prevention that can be done is by making a prediction of stroke for early detection. There are various methods available which are statistical methods and machine learning methods. In this research work, we aim to compare the two methods based on statistical method and machine learning method on stroke risk prediction. The data used in this research is primary data from Universitas Airlangga Hospital (RSUA) from June until August 2023. In this research, we compare the statistical method that is Logistic Regression (LR), and the machine learning method which is Support Vector Machine(SVM). We use Phyton to analyze all methods in this research. The results show that SVM with Radial Basis Kernel is better than LR in predicting stroke risk based on three goodness criteria namely sensitivity, F-1 score and accuracy where these three goodness criteria values of SVM are greater than those of LR.
Modeling the Percentage of Tuberculosis Cure in Indonesia Using a Multivariate Adaptive Regression Spline Approach Novianti, Dita Aris; Marwanda, Nadia Dwi; Saifudin, Toha; Suliyanto, Suliyanto
Inferensi Vol 7, No 2 (2024)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v7i2.20344

Abstract

Tuberculosis (TB) is an infectious disease caused by the bacterium Mycobacterium Tuberculosis. After India, Indonesia is the country with the second highest number of TB sufferers in the world. TB prevention efforts in Indonesia have been carried out, even since 1995. However, in general, 2006-2022 the TB cure in Indonesia tends to experience a downward trend. Therefore, it is important to know what variables have a significant effect and how the pattern relates to the percentage of TB cures. We urgently need this information to optimize TB handling efforts and achieve Sustainable Development Goals (SDGs) point 3, which focuses on good health and well-being. For that purpose, this study used the Multivariate Adaptive Regression Spline (MARS) approach. MARS is considered more flexible in overcoming cases of predictor variables that do not form a certain pattern to their response variables and can accommodate possible interactions between predictor variables. The best model was obtained at BF=18,MI=2, and MO=0 with minimum GCV value is 37.053 and R^2 is 91.6%, with significant predictor variables are food management sites meet the requirements according to standards, complete treatment, smoking population over 15 years, families with healthy latrines, and districts/municipalities implement healthy living germas policy. The significance of the nine predictors should prioritize enhancing the quality of health services for example ensuring a fair distribution of complete treatment for TB patients.
Peningkatan Kompetensi Guru dalam Analisis Data Hasil Pembelajaran dengan Metode Statistika Menggunakan Microsoft Excel di SD Muhammadiyah 1 Trenggalek: Improving Teachers’ Competence in Analyzing Learning Outcomes Data Using Statistical Methods with Microsoft Excel at SD Muhammadiyah 1 Trenggalek Rifada, Marisa; Saifudin, Toha; Kurniawan, Ardi; Ramadhani, Azzah Nazhifa Wina; Maharani, Prima; Sentosa, Martha Ayu
PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Vol. 11 No. 1 (2026): PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat
Publisher : Institute for Research and Community Services Universitas Muhammadiyah Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33084/pengabdianmu.v11i1.10675

Abstract

Muhammadiyah 1 Trenggalek Elementary School is one of the leading private elementary schools in Trenggalek Regency that implements an innovative system in its learning and has a strong commitment to improving the quality of education. However, most of the teachers in this elementary school still lack understanding of the concept of statistics along with the application of technology to analyze student learning data, so that the evaluation of student learning outcomes becomes less than optimal. Therefore, this community service program is carried out to provide intensive training on basic understanding of statistics, the use of Microsoft Excel to process data, and the application of analysis results to improve teaching methods. This program was carried out through several stages, consisting of providing offline training and assistance to groups of teachers in applying the training results to student learning data. The evaluation results show an increase in teacher understanding of the training material provided, with evidence of an increase in the average pre-test score of 64.46 to 71.08 in the post-test. Thus, this community service activity can be said to have succeeded in increasing teacher competence in using Microsoft Excel as a means of analyzing student learning data, which is also a start to improving the quality of Muhammadiyah 1 Trenggalek Elementary School teachers.
Co-Authors Abdul Aziz Aditya Syarifudin Akbar Aflaha, Nabila Shafa Aini Divayanti Arrofah Aisharezka, Mutiara Aisyah, Arlisya Shafwan Al Hasri, Ilham Maulana Alfi Nur Nitasari Alfredi Yoani Alpandi, Gaos Tipki Ameliatul 'Iffah Ana, Elly Andini Putri Mediani Angga Kusuma Bayu Viargo Angga Kusuma Bayu Viargo Aniq Atiqi Any Tsalasatul Fitriyah Ardi Kurniawan Ardi Kurniawan Ariani, Fildzah Tri Januar Aulia, Niswa Faizah Auliyah, Nina Ayuning Dwis Cahyasari Azis, Aurelia Islami Azizah, Khansa Belindha Ayu Ardhani Bryan Given Christiano Ginzel Chaerobby Fakhri Fauzaan Purwoko Christopher Andreas Dewanti, Maria Setya Dewanty, Sanda Insania Diah Puspita Ningrum Dita Amelia Dita Amelia Dita Amelia, Dita Doni Muhammad Fauzi Dwika Maya Harsanti Easyfa Wieldyanisa, Ezha Elly Pusporani Erfiana Erfiana Fachriza Yosa Pratama Faiza, Atikah Fajrina, Sofia Falasifah, Sabrina Fatmawati Fatmawati Fauziah, Nathania Fa’iqotus Zuqna Dwi Syauqie Felix Reba Fina Insyiroh Firmansyah, Mochamad FIRMANSYAH, MOCHAMMAD Fitriana Nur Afifa Fitriani, Mubadi'ul Fortunata, Regina Gaos Tipki Alpandi Gaos Tipki Alpandi Hardiansyah, Fernanda Rizky Hasyim, Maylita Herdianto, Muhammad Hendra Ika Purnamasari Ilma Amira Rahmayanti Indrasta, Irma Ayu Insania Dewanty, Sanda Isryad Yoga Adyatma Johanna Tania Victory Jovansha Ariyawan 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 Marwanda, Nadia Dwi Mediani, Andini Putri Mia Khoirunnisa Mochamad Firmansyah Mochamad Rasyid Aditya Putra Mohammad Noufal Ubadah Muhammad Rosyid Ridho Az Zuhro Mutiara Aisharezka Nabila Nurdin Nahar, Muhammad Hafidzuddin Naufal Ramadhan Al Akhwal Siregar Naura, Sheila Sevira Asteriska Novianti, Dita Aris Nugraha, Galuh Cahya Nur Chamidah Nur Chamidah Nur chamnidah Nur Rahmah Miftakhul Jannah Nurrohmah, Zidni 'Ilmatun Panjaitan, Leni Sartika Puspasari, Laili Raaulia Gita Nafsi Rahayu, Rizky Dwi Kurnia Ramadhani, Azzah Nazhifa Wina Ramadhanty, Devira Thania Ramadhina, Fidela Sahda Ilona Recylia, Rien Rimuljo Hendradi Risky Wahyuningsih Sa'idah, Andini Sabrina Salsa Oktavia 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 Siti Maghfirotul Ulyah Sri Wahyuningsih Sugha Faiz Al Maula Suliyanto Suliyanto Suliyanto Syaugi Sungkar, Salman Teguh Susanto Teguh Susanto Tiani Wahyu Utami Titania Faisha Purnama Trisa, Nadya Lovita Hana Valida, Hanny Verina Tita Nabila Victory, Johanna Tania VITA FIBRIYANI Wahyuli, Diana Widyawati, Ayu Wieldyanisa, Ezha Easyfa Wulandari, Indana Zulfa Yan Dwi