Article Per Year (5 Year)
p-Index From 2020 - 2025
1.152
P-Index
This Author published in this journals
All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan Al-Khwarizmi: Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) ESTIMASI: Journal of Statistics and Its Application
Sirajang, Nasrah
Unknown Affiliation
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Energy Engineering Mathematics Mechanical Engineering Physics Public Health Transportation Other

Published : 8 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search
Journal : ESTIMASI: Journal of Statistics and Its Application

 1 
Implementasi Algoritma Centroid Linkage dan K-Medoids dalam Mengelompokkan Kabupaten/Kota di Sulawesi Selatan Berdasarkan Indikator Pendidikan Raja, Nur Alfianingsih; Tinungki, Georgina Maria; Sirajang, Nasrah
ESTIMASI: Journal of Statistics and Its Application Vol. 5, No. 1, Januari, 2024 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v5i1.13605

Abstract

Cluster analysis is a multivariate analysis technique that aims to cluster the observational data or variables into clusters in such a way that each cluster is homogeneous according to the factors used for clustering. This study used the Centroid linkage algorithm that was useful for forming groups based on the distance between centroids and the K-Medoids algorithm that was based on the use of the most centered object (medoid) to group districts/cities and obtained comparison results based on the education indicator data in South Sulawesi. The implementation of the Centroid Linkage Algorithm and K-Medoids on the education indicator data in South Sulawesi in 2018, showed that the grouping of districts/cities in South Sulawesi produced 2 clusters with cluster 1 of 21 districts/cities, and cluster 2 of 3. To determine the best method, it was seen from the value of the Standard Deviation ratio in the cluster 〖(S〗_W) and Standard Deviation between Clusters 〖(S〗_B) showed the same standard deviation ratio (S) in the Centroid Linkage algorithm and K-Medoids that was equal to 104,967.
Analisis Regresi Data Panel Dengan Model Efek Umum, Model Efek Tetap Dan Model Efek Acak (Studi Kasus: Inflasi Dan Indeks Pembangunan Manusia) ada, Nuralyatussa’; Herdiani, Erna Tri; Sirajang, Nasrah
ESTIMASI: Journal of Statistics and Its Application Vol. 5, No. 2, Juli, 2024 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v5i2.33279

Abstract

Panel data regression analysis is a method for modeling the influence of independent variables on dependent variables, on a combination of cross-section and time-series data. This research aims to estimate a panel data regression model with a generalized effects model using the least squares method, estimate a fixed effects model with the Least Square Dummy Variable and estimate a random effects model with Generalized Least Square on inflation and human development index data. The results obtained show that the factors that have a significant influence at the 5% level on the inflation rate in 2014-2019 are the dollar exchange rate with a coefficient of determination of the general effects model of 61.06%, then the HDI level in South Sulawesi in 2011-2017 is significantly influenced by factors such as average length of schooling and life expectancy with a coefficient of determination of the fixed effects model of 89.73%, and the HDI level in South Sulawesi in 2016-2019 is significantly influenced by the factors of life expectancy, per capita expenditure and poverty with a coefficient of determination of the random effects model amounting to 63.07%.
Estimasi Parameter Model Three-Factor Completely Randomized Design dengan Metode Robust MM Nurkamalia, Nurkamalia; Kalondeng, Anisa; Sirajang, Nasrah
ESTIMASI: Journal of Statistics and Its Application Vol. 6, No. 1, Januari, 2025 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v6i1.18323

Abstract

When conducting experiments, it is often found that there are errors in the observed responses. It can cause data outliers to appear whose existence results in making conclusions inaccurate. Therefore, outliers need to be overcome by applying the robust regression method. The robust method used is the robust MM because it has a high level of efficiency and breakdown point. The Robust MM method is useful for obtaining parameter estimates in a three-factor Completely Randomized Design (CRD) which is applied to the data on average abdominal fat of broiler chickens experiencing outliers in four observations. The results showed that the presence of outliers caused no effect of differences in age of chicken and the interaction between age of chicken and feeding fermented kiambang on the average abdominal fat of broiler chickens. However, after the data was replaced with estimated data obtained from the Robust MM method to overcome outliers, it showed that there was an effect of age of chicken and the interaction between age of chicken and feeding of fermented kiambang on the average abdominal fat of broiler chickens.
Pemodelan Regresi Seemingly Unrelated Menggunakan Metode Maximum Likelihood pada Data Panel Hikmah, Nurul; Raupong, Raupong; Sirajang, Nasrah
ESTIMASI: Journal of Statistics and Its Application Vol. 6, No. 2, Juli, 2025 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v6i2.34463

Abstract

This study aims to model and predict the Human Development Index (HDI) values in South Sulawesi Province for the period 2014–2022 using a multiple linear regression approach with the Maximum Likelihood Estimation (MLE) method. Multiple linear regression analysis often encounters multicollinearity issues among independent variables; therefore, Principal Component Analysis (PCA) is employed as a dimensionality reduction technique to eliminate correlations among explanatory variables. In addition, due to the potential correlation of residuals among equations in a multivariate model, the Seemingly Unrelated Regression (SUR) approach is used, which is also estimated using the MLE method. The data utilized in this study is panel data, which offers advantages in obtaining more comprehensive and accurate information regarding the relationships between the analyzed variables. The estimation results of the SUR model indicate that variables such as Life Expectancy (UHH), Mean Years of Schooling (RLS), Expected Years of Schooling (HLS), and Adjusted Per Capita Expenditure have a significant influence on HDI across all districts/cities in South Sulawesi. One of the estimated equations from the SUR model is y22t=81.44+0.670KU122 which illustrates the relationship between the principal component and HDI in a specific region.
Co-Authors ada, Nuralyatussa’ Affan, Fajar Aidawayati, Aidawayati Anisa Anisa Anna Islamiyati Anwar, Andi M. B., Hasmawati Edy Saputra Rusdi Georgina Maria Tinungki Herdiani, Erna Tri Jaya, A. Kresna Jusmawati Jusmawati, Jusmawati Jusmawati Massalesse Kalondeng, Anisa Kasbawati Kasbawati Muhammad Zakir Naimah Aris Nur Erawaty Nurkamalia, Nurkamalia Nurul Hikmah Raja, Nur Alfianingsih Ramadhan, Muh. Nur Bahri Raupong, Raupong Sahriman, Sitti Sari, Ummi Sri Astuti Thamrin Thoha, Syamsuddin Usrah, Muhammad Jayzul Wahda, Wahda Wahyuni, Alfiana