Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Jurnal Sintak
V.R, Baiq Jasmin Sabhira Safwa
Unknown Affiliation
Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Decision Sciences, Operations Research & Management Mathematics

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Segmentation Of Educational Quality In Indonesian Provinces Based On K-Means Clustering V.R, Baiq Jasmin Sabhira Safwa; Tectona, Zakiy Suryahadi; Widodo, Edy
JURNAL SINTAK Vol. 4 No. 2 (2026): MARET 2026
Publisher : LPPM-ITEBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62375/jsintak.v4i2.794

Abstract

The quality of education in Indonesia still exhibits disparities among provinces, reflecting differences in educational attainment and access. This study aims to segment the quality of education across Indonesian provinces based on the similarity of educational characteristics using the K-Means Clustering method. The data used consist of provincial-level education data that have undergone outlier detection and standardization to ensure comparability across variables. K-Means Clustering analysis was performed by forming three clusters representing provinces with low, medium, and high levels of educational quality. The clustering results indicate that most provinces fall into the medium education quality cluster, while a smaller number of provinces remain in the low education quality cluster. These findings demonstrate that the K-Means Clustering method is able to provide a clear representation of segmentation patterns and disparities in educational quality across Indonesian provinces and can serve as a basis for supporting more targeted and equity-oriented education policy formulation. Keywords: education; quality; K-Means; clustering; provinces
Cluster Analysis and Discriminant Analysis for Grouping Provinces Based on Factors Affecting Poverty Levels in Indonesia 2018-2020 Kariyam; V.R, Baiq Jasmin Sabhira Safwa; Alifia, Juan Latif; Oktarani, Larasati; Andanitya, Putri Pratista; Ikhsani, Willia Diva
JURNAL SINTAK Vol. 4 No. 2 (2026): MARET 2026
Publisher : LPPM-ITEBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62375/jsintak.v4i2.802

Abstract

Poverty is a condition that occurs due to the inability of a person or group to meet the minimum basic needs, such as food, clothing, health, housing, and education, which are necessary to maintain survival. The poverty level of an area is influenced by various factors, including the Open Unemployment Rate (TPT), the Provincial Minimum Wage (UMP), and the Human Development Index (IPM). This research aims to group provinces in Indonesia based on factors that affect poverty and determine the discriminatory function of the group formed. The analysis method used is cluster analysis to group provinces into several poverty level groups and discriminatory analysis to form a separating function between the groups. The results of cluster analysis show the formation of three groups, namely the group with the highest poverty level consisting of 7 provinces, the group with moderate poverty level consisting of 8 provinces, and the group with the lowest poverty level which includes other provinces. Furthermore, discriminant analysis produces a discriminant function that is able to distinguish between poverty levels quite well. The results of this research are expected to be considered by the government in formulating poverty alleviation policies that are more on target
Co-Authors Alifia, Juan Latif Andanitya, Putri Pratista Edy Widodo Ikhsani, Willia Diva Kariyam Oktarani, Larasati Tectona, Zakiy Suryahadi