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All Journal Jurnal Informasi dan Komputer Jurnal Ilmiah Wahana Pendidikan
Virgaria Zuliana
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Religion Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Mathematics Social Sciences Other

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Penerapan K-Means Clustering dalam Pengelompokan Kasus Tuberkulosis di Provinsi Jawa Barat Fadhlan Sulistiyo Hidayat; Rizma Berliana Putri Affandi; Virgaria Zuliana; Tesa Nur Padilah
Jurnal Ilmiah Wahana Pendidikan Vol 8 No 15 (2022): Jurnal Ilmiah Wahana Pendidikan
Publisher : Peneliti.net

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (183.523 KB) | DOI: 10.5281/zenodo.7049113

Abstract

Tuberculosis is a very common infectious disease and is lethal in most of the cases. This is the background of this research, namely because there are many cases of Tuberculosis in Jawa Barat. According to data obtained from the Open Data Jabar, namely Tuberculosis Data in Jawa Barat Province, showing data that in 2020 all districts and cities in Jawa Barat had a number of Tuberculosis cases starting from 320 cases in Banjar Regency which was the lowest case, and 10,248 cases in Bogor Regency which is the highest case in Jawa Barat. The purpose of this study was to cluster TB cases into high and low categories based on gender. The data we use is data on the number of TB cases in Jawa Barat province in 2020 which consists of 27 districts/cities. In this study using the Clustering method with the K-Means algorithm. The results obtained based on the test, the clusters obtained were 2 with cluster 0 with 23 low TB cases and 4 clusters for high TB cases. Researchers hope that the results of this study can become knowledge for the government to reduce the number of TB in Jawa Barat
Analisis Sentimen Program Migrasi TV Digital Menggunakan Algoritma Naive Bayes dengan Chi Square Virgaria Zuliana; Garno Garno; Iqbal Maulana
Jurnal informasi dan komputer Vol 10 No 2 (2022): Jurnal Sistem Informasi dan Komputer yang terbit pada tahun 2022 pada bulan 10 (
Publisher : STMIK Dian Cipta Cendikia Kotabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35959/jik.v10i2.366

Abstract

Currently, television occupies the number 2 position as a source of information after social media. The analog TV broadcast system will be replaced with digital TV based on a plan issued by the Ministry of Communication and Information in Indonesia. Social media is useful for sharing thoughts and opinions about events, products and more, for example on the ongoing digital TV migration. The advantages of digital TV include superior technology and clear, crisp picture clarity. Some people argue that they are satisfied with the transition to digital TV, while others are the opposite. So that researchers are interested in these two opinions and are interested in analyzing public sentiment regarding the migration program for digital TV broadcasts on Twitter social media because of these two responses. The Naive Bayes method with Chi Square feature selection is used in the research process to examine differences in public opinion about migration to digital TV broadcasts. The results of the classification with 191 positive sentiment data and 185 negative sentiment data resulted in 96% accuracy, 93% precision and 100% recall.
Co-Authors Fadhlan Sulistiyo Hidayat Garno Garno Iqbal Maulana Rizma Berliana Putri Affandi Tesa Nur Padilah