Kristuisno Martsuyanto Kapiluka
IPB University

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ANALISIS MULTIVARIAT UNTUK PEMETAAN KARAKTERISTIK MUTU PENDIDIKAN SEKOLAH MENENGAH KEJURUAN (SMK) DI INDONESIA Kristuisno Martsuyanto Kapiluka; Dhea Dewanti; Budi Susetyo
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 3 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v4i3.328

Abstract

Evaluation of the education quality in Indonesia, especially in Vocational High Schools (VHS), carried out through the Presidential Instruction 2016. The implementation of these instructions is not easy because of the different characteristics of each region both geographically and socio-culturally. This study aims to analyze related to the mapping of the characteristics of the quality of vocational education from 34 provinces in Indonesia. The methods used are correspondence analysis, biplot analysis, and cluster analysis which are multivariate statistical analysis methods. The correspondence analysis results show that there are differences in the characteristics of the quality of vocational education from each province based on school accreditation. The biplot analysis show that Teacher Quality is greatest diversity variable compared to other variables. In addition, the provinces of Aceh, East Nusa Tenggara, West Sulawesi and Central Kalimantan have a quality score below the average and are dominated by non-accredited VHSs based on the results of the analysis. The k-means cluster analysis with 4 optimal clusters gives the result that cluster 2 is the cluster with the best quality value while cluster 4 is the cluster with the lowest quality value. Three analytical concluded that provinces with very good quality scores such as DKI Jakarta, Bali and DI Yogyakarta can be used as pilot provinces for other provinces. Meanwhile, provinces with VHS quality scores below the provincial average as a whole should receive attention in order to further improve the quality of their VHSs
Bahasa Inggris Dhea Dewanti; Kristuisno Martsuyanto Kapiluka; Febryna Sembiring; Ajeng Bita Alfira; Anang Kurnia
Jurnal Matematika, Statistika dan Komputasi Vol. 21 No. 1 (2024): SEPTEMBER 2024
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v21i1.35584

Abstract

Multilevel binary logistic regression analysis is a development of logistic regression for hierarchical data structures. Hierarchical data is data from a population that has levels. This research examines the relationship model of Life Expectancy, Mean Years of Schooling, Expected Years of Schooling, Regency/City Minimum Wage as explanatory variables at level 1 (Regency) and Gross Regional Domestic Income (GRDP) as an explanatory variable at level 2 (Provincial) against Unemployment Rate (UR) as a response variable. The research results show that Life Expectancy and Minimum Wage at level 1 and GRDP at level 2 have a significant influence on district/city TPT on Java Island in 2022