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Faisal Muhammad
Universitas Raharja
Computer Science & IT

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Penerapan Data Mining Menggunakan Algoritma K-Means Untuk Clustering Perokok Usia Lebih dari 15 Tahun Suharmanto; Wiranti Sri Utami; Nila Pratiwi; Faisal Muhammad
Bulletin of Information Technology (BIT) Vol 4 No 4: Desember 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i4.1067

Abstract

Smoking is an activity that can have a bad impact on health, both for yourself and for others. This is because there are various kinds of ingredients that are dangerous to health, there are 4000 types of chemicals found in cigarettes, starting from nicotine and other substances that can cause cancer in humans. The dataset obtained from BPS (Central Statistics Agency) can be utilized by using K-Means Clustering to determine the grouping of smokers aged more than 15 years in each region. The grouping of smokers aged over 15 years can be seen through 3 clusters, Cluster 1 is the highest level of smoking in 10 provinces out of 34 provinces studied, Cluster 2 is the medium level with 15 provinces out of 34 provinces studied, and Cluster 3 is the lowest level. with 9 Provinces.
Penerapan Data Mining Menggunakan Metode Cluster K-Means Untuk Pengelompokkan Fasilitas Sekolah Faisal Muhammad; Suharmanto; Janu Ilham Saputo; Wiranti Sri Utami
Bulletin of Information Technology (BIT) Vol 6 No 4 (2025): Desember 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v7i1.2340

Abstract

School Facilities are facilities provided by schools or universities to support activities and can be utilized by students, teachers, students and staff within the scope of a particular education. In order to create good teaching and learning activities (KBM) and support the development process and achievements, good schools or universities must have classroom facilities, laboratories, libraries, canteens, places of worship and fields. By applying data mining and utilizing the data sources obtained and the application of the K-Means cluster method, information related to school facilities can be drawn. The number of clusters obtained is 2 clusters with the number of squares according to the cluster of 76.0%.
Pemanfaatan Algoritma K-Medoids Clustering dalam Menentukan Pendapatan Bersih Komoditas Pertanian Faisal Muhammad; Wiranti Sri Utami; Muhammad Subali; Janu Ilham Saputo; Haryanto; Martinus Gawi Tiga
Bulletin of Information Technology (BIT) Vol 7 No 2 (2026)
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v7i2.2682

Abstract

Agricultural products are one of the sectors that have a major role in the Indonesian economy. Currently, Indonesia is the largest producer in the world that produces Palm Oil, Cloves, Cinnamon, Nutmeg, and many others. Abundant agricultural products can be applied to research using Data Mining techniques. Data Mining is a technique that applies statistical analysis and artificial intelligence in extracting useful information from a database. In this study the author will use the K-Medoids method, K-Medoids is one of the Data Mining techniques. Analysis of K-Medoids results uses the silhouette coefficient which is used to measure the distance between clusters. The objective value using K-Medoids cluster analysis on the dataset used is 5.742047 and 5.093438. After conducting cluster analysis with the silhouette coefficient, the best results obtained are 2 clusters from 12 data and 12 attributes.
Co-Authors Haryanto Janu Ilham Saputo Martinus Gawi Tiga Muhammad Subali Nila Pratiwi Suharmanto Suharmanto Wiranti Sri Utami