CLUSTERING KETERAMPILAN TEKNOLOGI INFORMASI DAN KOMPUTER UNTUK MENGURANGI KESENJANGAN PENGUASAAN TIK MENGGUNAKAN METODE K-MEANS PADA SELURUH PROVINSI DI INDONESIA

Barirotun Najah, . (2023) CLUSTERING KETERAMPILAN TEKNOLOGI INFORMASI DAN KOMPUTER UNTUK MENGURANGI KESENJANGAN PENGUASAAN TIK MENGGUNAKAN METODE K-MEANS PADA SELURUH PROVINSI DI INDONESIA. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

This research was conducted to determine the grouping of information technology and computer (ICT) skills by province in Indonesia using the k-means method which can later help the government to determine the grouping of ICT skill levels by province. Information Technology and Computers (ICT) are all activities related to processing, managing and delivering or transferring information between facilities or media. This research is the application of the Kmeans algorithm and the evaluation of the Davies Bouldin Index (DBI) technique and the Calinski Harabasz Index. This research uses the elbow method to determine the best number of clusters. This study obtained the best cluster with k of 3, namely, cluster 0 with the moderately skilled category in 22 provinces, cluster 1 in the highly skilled category in 8 provinces, and cluster 2 in the less skilled category in 4 provinces.

Item Type: Thesis (Skripsi)
Additional Information: [No.Panggil: 1910511119] [Pembimbing: Widya] [Penguji 1: Tjahjanto] [Penguji 2: Anita Muliawati]
Uncontrolled Keywords: Information and Computer Technology (ICT), K-Means, Cluster, Davies Bouldin Index (DBI), Calinski Harabasz Index.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User: Barirotun Najah
Date Deposited: 01 Aug 2023 03:47
Last Modified: 01 Aug 2023 03:47
URI: http://repository.upnvj.ac.id/id/eprint/25350

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