Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal Teknosains: Media Informasi Sains dan Teknologi Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) Bulletin of Economic Studies (BEST)
Adiatma Adiatma
UNIVERSITAS ISLAM NEGERI ALAUDDIN MAKASSAR
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Mathematics Medicine & Pharmacology Physics

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Panel Data Regression Analysis with GLMM Approach (Case Study: HDI in South Sulawesi Province) Adiatma Adiatma; Adnan Sauddin; A. Hikmawati
Bulletin of Economic Studies (BEST) Vol 1 No 3 (2021)
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/best.v1i3.25873

Abstract

South Sulawesi is a province consisting of several regencies/cities. To understand well the HDI of South Sulawesi, it takes a good understanding of the HDI situation of each Regency/City. The HDI situation which continues to increase from year to year can be used as an indicator to measure success in human development efforts. HDI can also determine the ranking or level of development of a region/country. This study aims to determine the factors that have a significant effect on HDI and to find out the best panel data regression model for HDI in South Sulawesi. The method used in this study is panel data regression analysis with the Generalized Linear Mixed Model (GLMM) approach. The results showed that the variable life expectancy (AHH), average length of school (RLS) and per capita expenditure (PP) had a significant effect on the human development index (HDI) in South Sulawesi Province in 2014-2018.Keywords: HDI, Panel Data Regression, Generalized Linear Mixed Model.
Penerapan Model Seemingly Unrealated Regression (SUR) Spasial pada Tingkat Kasus Kriminalitas di Provinsi Sulawesi Selatan Rasyid, Adiatma; Kasse, Irwan; Sauddin, Adnan
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 9 No 1 (2021): VOLUME 9 NOMOR 1 TAHUN 2021
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v9i1.19361

Abstract

This research conducted discusses the crime rate in South Sulawesi Province. There are several main factors that can lead to crime, especially in South Sulawesi Province. This research was conducted to see the Spatial Seemingly Unrealated Regression SUR) model at the crime rate in South Sulawesi Province, but there are assumptions that do not meet the SUR Spatial Analysis, so the model obtained is limited to the Spatial Autoregressive (SAR) and Spatial Eror Model (SEM). The SAR model obtained shows that the population, the number of poor people, and the GDP per capita have a positive and significant effect on the risk of the population being affected by crime. The SEM model obtained shows a positive and significant effect between the population, the number of unemployed has a negative and significant effect on the risk of the population being exposed to crime.
Model regresi nonparametrik dengan pendekatan spline (Studi kasus: Gizi buruk di Kota Makassar) Alwi, Wahidah; Adiatma, Adiatma; Sauddin, Adnan; Faradila, Adhe
Teknosains Vol 19 No 1 (2025): Januari-April
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/teknosains.v19i1.52467

Abstract

Penelitian ini membahas tentang pemodelan gizi buruk di Kota Makassar melalui pendekatan regresi nonparametrik spline. Mengingat bahwa hubungan antara tingkat gizi buruk pada balita di Kota Makassar dengan faktor-faktor yang diduga mempengaruhinya tidak membentuk pola tertentu. Sehingga penulis menggunakan pemodelan regresi nonparametrik spline. Metode spline sangat baik dalam memodelkan data yang memiliki pola yang berubah-ubah pada sub-sub interval tertentu. Dalam penelitian ini menggunakan empat faktor yang diduga mempengaruhi persentase gizi buruk balita di Kota Makassar. Faktor-faktor tersebut adalah Berat Badan Lahir Rendah (BBLR), balita yang mendapatkan pelayanan kesehatan, balita yang mendapatkan vitamin A dan balita yang mendapatkan ASI eksklusif. Data Profil Dinas Kesehatan Kota Makassar tahun 2021 mencakup persentase gizi buruk pada balita serta empat faktor yang diduga memengaruhinya. Melalui penggunaan regresi nonparametrik spline, dihasilkan bahwa semua variabel prediktor mempengaruhi persentase gizi buruk balita di Kota Makassar, dengan nilai R² sebesar 98,74%. Ini berarti model regresi nonparametrik spline yang diperoleh mampu menjelaskan 98,74% dari variasi persentase gizi buruk balita.
Co-Authors A. Hikmawati Adnan Sauddin Faradila, Adhe Irwan Kasse Wahidah Alwi