PENERAPAN ALGORITMA K-MEANS PADA SMA PROVINSI DKI JAKARTA UNTUK MENENTUKAN SEKOLAH TERBAIK BERDASARKAN NILAI UN

Education is an important aspect in human resource development in Indonesia. One indicator to measure the quality of education is the National Examination (UN) score. However, parents or students often have difficulty choosing the best school in DKI Jakarta Province because of the many choices available. This research aims to apply the K-Means algorithm to group high school schools in DKI Jakarta Province based on National Examination scores. By using the clustering method, it is hoped that groups of schools with the best achievements can be found, making it easier to select schools based on these criteria. In this research, the data used are high school National Examination scores in DKI Jakarta obtained from the Ministry of Education and Culture. The results of this research show that the K-Means algorithm can be effectively used to group schools based on National Examination scores, thereby providing a clearer picture for the public in determining quality schools.

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Publication Details

Journal
Jurnal Ilmiah Multidisiplin Ilmu
Published
2025-02-01
DOI
https://doi.org/10.69714/bncwkr16
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

PENERAPAN ALGORITMA K-MEANS PADA SMA PROVINSI DKI JAKARTA UNTUK MENENTUKAN SEKOLAH TERBAIK BERDASARKAN NILAI UN

Muhammad Hasan, Zaehol Fatah
Jurnal Ilmiah Multidisiplin Ilmu
Data Mining and Machine Learning Applications
article

PENERAPAN ALGORITMA K-MEANS PADA SMA PROVINSI DKI JAKARTA UNTUK MENENTUKAN SEKOLAH TERBAIK BERDASARKAN NILAI UN

Muhammad Hasan, Zaehol Fatah
article en

Abstract

Education is an important aspect in human resource development in Indonesia. One indicator to measure the quality of education is the National Examination (UN) score. However, parents or students often have difficulty choosing the best school in DKI Jakarta Province because of the many choices available. This research aims to apply the K-Means algorithm to group high school schools in DKI Jakarta Province based on National Examination scores. By using the clustering method, it is hoped that groups of schools with the best achievements can be found, making it easier to select schools based on these criteria. In this research, the data used are high school National Examination scores in DKI Jakarta obtained from the Ministry of Education and Culture. The results of this research show that the K-Means algorithm can be effectively used to group schools based on National Examination scores, thereby providing a clearer picture for the public in determining quality schools.

Jurnal Ilmiah Multidisiplin IlmuVol. 2(1)
Universitas Ibrahimy (ID)
Decent work and economic growth
Openalex Percentile: Top 98%
Data Mining and Machine Learning Applications
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