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All Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JurTI (JURNAL TEKNOLOGI INFORMASI)
Bella Nurseptia
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Computer Science & IT

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Penerapan Algoritma K-Means Untuk Mengelompokkan Kabupaten/Kota Dalam Upaya Pemetaan Lapangan Pekerjaan Baru Bella Nurseptia; Apriade Voutama; Nono Haeryana
(JurTI) Jurnal Teknologi Informasi Vol 6, No 2 (2022): DESEMBER 2022
Publisher : Universitas Asahan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36294/jurti.v6i2.2934

Abstract

Pengangguran menjadi suatu permasalahan yang dihadapi Indonesia sebagai negara berkembang. Banyak dampak negatif yang dapat muncul akibat tingginya jumlah pengangguran di suatu wilayah. Cara untuk mengatasi tingginya tingkat pengangguran adalah dengan mengoptimalkan pembangunan lapangan pekerjaan baru. Berdasarkan catatan Badan Pusat Statistik (BPS) Indonesia, Jawa Barat merupakan salah satu provinsi di Indonesia dengan tingkat pengangguran yang tinggi. Padahal sejak beberapa tahun terakhir Provinsi Jawa Barat menjadi peringkat pertama Provinsi di Indonesia dengan aliran dana Penanaman Modal Asing (PMA) yang besar. Penelitian ini akan mengelompokkan Kabupaten/Kota di Jawa Barat berdasarkan atribut  TPT, TPAK dan PMA. Dari data yang diolah dengan menggunakan algoritma K-Means menghasilkan 3 cluster, dimana ketiga cluster tersebut memiliki karakteristik yang berbeda sehingga dapat membantu pemerintah di Jawa Barat mengoptimalkan pemetaan lapangan pekerjaan baru.
Pemetaan Tingkat Kekerasan Pada Anak dan Perempuan Menggunakan Algoritma K-Medoids (Studi Kasus : P2TP2A DKI Jakarta) Bella Nurseptia; Nina Sulistiyowati; Apriade Voutama
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 10 No 4 (2023): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v10i4.5910

Abstract

Since 2018-2022 P2TP2A DKI Jakarta Province has recorded an increase in cases of violence against children and women. The lack of public awareness of the issue of violence is one of the factors in the increase in these cases. One of the efforts that can be made by the government to optimize handling, prevention and reducing the number of cases of violence is to classify and map areas based on the level of violence against children and women. This study uses the CRISP-DM methodology which consists of the stages of Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, Deployment. The algorithm used to classify data on cases of violence against children and women in 2018-2022 is k-medoids. Determination of the number of clusters is carried out using 2 methods, namely the elbow method and the silhouette coefficient. The result of this study is the grouping of regions based on the level of violence against children and women visualized using QGIS tools. The results of the cluster evaluation show that the lowest DBI value is 1.484557, where the optimal number of clusters is 3 with the method of determining the number of k using the elbow method. Clustering results show that cluster 1 is an area with a low level of violence consisting of 6 sub-districts, cluster 2 is an area with a moderate level of violence consisting of 30 sub-districts, and cluster 3 is an area with a high level of violence consisting of 8 sub-districts
Co-Authors Apriade Voutama Nina Sulistiyowati Nono Haeryana