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All Journal Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) Journal of Mathematics, Computation and Statistics (JMATHCOS)
Wahidah Alwi
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Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Mathematics Medicine & Pharmacology

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Analisis Forecasting Peserta KB Jenis Suntik dan Pil Di Kabupaten Sidenreng Rappang Dengan Metode Seasonal Autoregressive Moving Average (SARIMA) Ahmad Faiz; Andi Mariani; Wahidah Alwi
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 12 No 2 (2024): VOLUME 12 NO 2 TAHUN 2024
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v12i2.54841

Abstract

This study aims to analyze the increasing demand for contraceptives, making forecasting necessary to anticipate future needs and prevent supply shortages. To support this program, an effective forecasting method is required to predict the number of family planning (FP) participants in the future. This study employs the SARIMA (Seasonal Autoregressive Integrated Moving Average) time series method to forecast the number of FP participants using injections and pills in Sidenreng Rappang Regency. The results show that the SARIMA (0,1,0)(0,1,1)12 model is the most suitable for injection-based FP participants, while the SARIMA (1,1,0)(0,1,1)12 model is used for pill-based FP participants. The forecast indicates a decline in the numiber of injection and pill FP participants from January 2024 to December 2025.
Implementasi regresi binomial negatif dalam mengatasi overdispersi pada analisis determinan jumlah pengangguran di pulau Sulawesi tahun 2023 Erna; Ermawati; Wahidah Alwi; Sri Dewi Anugrawati
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 13 No 2 (2025): VOLUME 13 NO 2, 2025
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v13i2.61738

Abstract

This study focuses on the implementation of negative binomial regression as a solution to overcome the problem of overdispersion in the analysis of determinants of unemployment on the island of Sulawesi in 2023. Unemployment is not only viewed as a statistical phenomenon or economic issue, but also as an important indicator that reflects social welfare and the success of development in a region. Sulawesi Island, with its growth in the agricultural and industrial sectors, faces serious challenges in reducing unemployment rates, which have the potential to cause regional disparities if not addressed appropriately. This study aims to develop an appropriate negative binomial regression model to overcome overdispersion and identify the main factors that influence the unemployment rate. The method used is negative binomial regression analysis of district/city unemployment data in Sulawesi Island, which is discrete and shows symptoms of overdispersion. With significant variables including population size, Human Development Index (HDI), and the number of job placement or fulfillment services. These three factors have been proven to have a significant effect on the number of unemployed people in Sulawesi Island in 2023.
Co-Authors Adiatma Adnan Sauddin Ahmad Faiz Ale Miftahulhaer, Ale Miftahulhaer Andi Mariani Andi Nurfadhilah Anugrawati, Sri Dewi Ermawati Erna Hasmira Ilham Nur Ilahi Irwan, Muh. lili putri inasari Muh. Irwan Muh. Irzan Muhammad Ihsan Salim Nahda Islamiah. M Nurfadilah, Khalilah Susrianti Wahyuni Abidin