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All Journal Natural Science: Journal of Science and Technology JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) JOIN (Jurnal Online Informatika) JURNAL ILMIAH MATEMATIKA DAN TERAPAN BAREKENG: Jurnal Ilmu Matematika dan Terapan Kompartemen : Jurnal Ilmiah Akuntansi Jurnal Aplikasi Statistika & Komputasi Statistik Jurnal Varian Majalah Ilmiah Matematika dan Statistika (MIMS) Jurnal Statistika dan Aplikasinya JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Parameter: Journal of Statistics Jurnal Pengabdian Farmasi dan Sains
Fadjryani, Fadjryani
Department Statistics, Faculty Of Mathematics And Natural Sciences, Tadulako University, Indonesia
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Environmental Science Immunology & microbiology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation Other

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MODELING THE DURATION OF MATERNAL LABOR AT ANUTAPURA HAMMER HOSPITAL USING LIN-YING ADDITIVE HAZARD REGRESSION Fadjryani, Fadjryani; Setiawan, Iman; Sain, Hartayuni; Fajri, Mohammad; Gamayanti, Nurul Fiskia; Radi, Aryani; Aisya, Cici
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 1 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss1pp0523-0540

Abstract

The Central Sulawesi government has a Sustainable Development Goals (SDGs) target for 2020-2024, which sets the maternal mortality rate below 70/100,000 KH. However, in 2018-2022, the maternal mortality rate fluctuated by 128/100,000 KH. One of the factors causing maternal mortality is the duration of the labor process. The factors that are thought to have an influence on the duration of labor are gestational age, maternal age, baby height, parity, and hemoglobin levels. Therefore, this study aims to see what modeling and factors affect the duration of birth using Lin-Ying additive hazard regression analysis. Data were obtained from the medical records of normal deliveries between January and December 2023 at Anutapura Palu Hospital. The results showed that the factors that affect the duration of birth are preterm gestational age, aterm gestational age, maternal age 20-35 years, primigravida mothers, multigravida mothers, and mothers who are not anemic. A limitation of this study is the relatively short data collection period of one year, which may not capture variations or trends in labor outcomes over time.
COMPARISON OF OVERSAMPLING, UNDERSAMPLING, AND SMOTE TECHNIQUES FOR MULTICLASS BALANCE DATA HANDLING IN RANDOM FOREST AND MULTINOMIAL LOGISTIC REGRESSION Fadjryani; Asfar; Nazwa; Tokandari, Allin Floria; Lestari, Tri Andayani; Ghani, Muhammad Azi Zarir
Jurnal Statistika dan Aplikasinya Vol. 9 No. 2 (2025): Jurnal Statistika dan Aplikasinya
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.09207

Abstract

Class imbalances in multiclass classifications are an important challenge in applied machine learning, particularly in the medical field such as predicting how patients will exit. Although various studies have demonstrated the effectiveness of resampling techniques, the best combination of classification algorithms and balancing methods for highly unbalanced multiclass hospital data is still rarely studied. This study aims to compare the performance of Random Forest (RF) and Multinomial Logistic Regression (MLR) algorithms in dealing with class imbalances using three resampling techniques: Random Oversampling (ROS), Random Undersampling (RUS), and Synthetic Minority Oversampling Technique (SMOTE). The dataset used included 1,032 inpatients with Non-Insulin-Dependent Diabetes Mellitus (NIDDM) at Undata Hospital, Central Sulawesi, for the period January 2021 to December 2023. Data pre-processing includes coding, normalization, and data sharing by stratified sampling (80:20). Feature selection was conducted using Recursive Feature Elimination (RFE), and model evaluation was conducted with 5-fold cross-validation using accuracy, recall, F1-score, and MCC metrics. The results showed that the combination of RF and ROS provided the best performance with an accuracy of 93.65%, F1-macro of 0.935, and a balanced accuracy of 0.95. This combination has been shown to be able to recognize minority classes well without sacrificing overall accuracy. In contrast, the MLR model shows the lowest performance, especially when using RUSs that cause the loss of important data. Although SMOTE is showing competitive results, it remains below ROS in this context. This study was limited to structured clinical data and only compared two types of classification models. In the future, deep learning-based approaches or advanced ensembles can be explored. The novelty of this study lies in the thorough evaluation of the combination of balancing techniques and classical classification algorithms for medical predictions with extremely unbalanced multiclass data.
Analysis of the Relationship Between Net Exports and Gross Regional Domestic Product Using the Panel Vector Correction Model (PVECM) Approach Soleha, Salma; Gamayanti, Nurul Fiskia; Sain, Hartayuni; Fadjryani, Fadjryani
Jurnal Varian Vol. 8 No. 3 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v8i3.4898

Abstract

In regional economic growth, various factors play a role, including net exports, a key indicator of international trade. The purpose of this study is to analyze the long-term relationship and causal link between net exports and Gross Regional Domestic Product (GRDP) in Indonesia. The method used in this study is the Panel Vector Error Correction Model (PVECM), applied to panel data from 34 provinces in Indonesia for the period 2010–2023. The results of the study indicate a cointegration relationship between net exports and GRDP, in which a 1-unit increase in net exports decreases GRDP by 5.445139 units. The Granger Causality test shows a significant bidirectional relationship between the variables, indicating that they influence each other. The R² value of 54.99% indicates that the model explains 54.99% of the variation in net exports. The implication of these findings suggests that policymakers need to consider the quality and composition of export and import activities, as well as regional trade structures, to ensure that international trade contributes positively to regional economic growth.
Co-Authors Aan Bin Mardi Abdul Mahatir Najar Afriza, D A Afriza, Dini Aprilia Agus Indra Jaya Ainanur Aisya, Cici Aldi Setiawan, Aldi Amaliah, Fika Reski Ambarwati B. Sarabi , Valina Annisa, N Arfa, Fhahnul Aiman H Asfar Asrima Aulia, Nanda Batara, Mohammad Chalfin Lieputera Kaliongga Damayanti, Virga Dewi Puji Astuti, Dewi Puji DEWI SARTIKA Diah Daniaty Difa Shalsabila Eka Rizky Wulansari Eliani Eliani Fika Reski Amaliah Fitri, Yuhelni Gamayanti, Nurul Fiskia Ghani, Muhammad Azi Zarir Harmila, D Hartayuni Sain Iman Setiawan Ismail, Nurmasita Iut Tri Utami Jannah , Miftahul Junaidi Junaidi Junaidi Junaidi Juni Wijayanti Puspita Lestari, Tri Andayani Marulu, Puja Lestari Maulidyani Abu Mohammad Fajri Mu'arif, Z Mujahida, A S Mukarrama, F.A. Musyarofah, U Nazwa Nur Azizah Nur'Eni Nur?Eni, Nur?Eni Nurdin, Ansor Nureni, Nureni Nurfadilah, Khalilah Nursanti, M Radi, Aryani Raihanah, Ghina Rizqa Rais Rais Resnawati Salsabila, P Setiawan, Iman Siti Helmyati Soleha, Salma Suaib, Tri Putri Andayani Syaiful Hendra Tokandari, Allin Floria Wawan Saputra Yulisharyasti, Luthfiah