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All Journal Jurnal Media Infotama Jurnal Pseudocode ILKOM Jurnal Ilmiah Infotek : Jurnal Informatika dan Teknologi SKANIKA: Sistem Komputer dan Teknik Informatika GATOTKACA Journal (Teknik Sipil, Informatika, Mesin dan Arsitektur) Jurnal Pengabdian Masyarakat Ilmu Terapan (JPMIT) Jurnal PADAMU NEGERI (Pengabdian pada Masyarakat Bidang Eksakta) Jurnal Dehasen Untuk Negeri Jurnal Media Computer Science Digital Transformation Technology (Digitech) Jurnal Komputer, Informasi dan Teknologi
Toibah Umi Kalsum
Universitas Dehasen Bengkulu
Aerospace Engineering Agriculture, Biological Sciences & Forestry Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Nursing Physics Public Health Transportation Other

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Application Of Data Mining To Determine The Amount Of Production Using The K-Means Method (Case Study At Pt. Coca Cola Distribution Indonesia Bengkulu) Yessi Mardiana; Toibah Umi Kalsum
GATOTKACA Journal (Teknik Sipil, Informatika, Mesin dan Arsitektur) Vol. 3 No. 1 (2022)
Publisher : Perkumpulan Dosen Muda (PDM) Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37638/gatotkaca.v3i1.459

Abstract

This study applies Data Mining using the Clustering method to determine the amount of production based on the level of product sales at PT. Coca Cola Distribution Indonesia Bengkulu branch. The algorithm used is K-Means Clustering, where data grouped based on the same characteristics will be included in the same group and the data sets entered into the groups do not overlap. The information displayed is in the form of product data groups based on the level of sales, so that it is known the amount of production at PT. Coca Cola Distribution Indonesia which is adjusted to product clusters with high, medium and low sales levels, resulting in product clusters that could be utilized by PT. Coca Cola Distribution Indonesia in determining the number of production of the next product
Co-Authors Achmad Teddy Subagya Adhadi Kurniawan Agung Pradana Iskandar Agus Susanto Aji Sukmo Andi Kurniawan Dahlan Suhardi Dandi Ilham Pratama Daniel Daniel Decky Mandala Putra Dedi Apriadi Diko Susanto Dimas Aldi Romadoni eko prasetyo rohmawan Eni Yuliza Fadhil Azmi Farhan Hazairin febri romadhon Fredricka, Jhoanne Harri Agustian Hary Satria Pratama Hendri Alamsyah Hendry Alamsyah Herdiansyah Herdiansyah Hermawansa Indra Saputra Julias Sulicdio Kanedi, Indra Kanedi Khairil Khairil Khairil Pseudocode Liza Yulianti M. Azzahrul Ikhsan Marsoni Marsoni Martoni Martoni Oke Hermanto AP okky abdurahman Ovi Susanti Poppy Septea Utami Prahasti Reno Supardi Renta Risnauli N Reza Rahmansa Riska Riska Riski Amalia Rizka Rizka Rizka Tri Alinse Robin Darmanto Rohanita Rohanita Rosdiana Rosdiana Sallaby, Achmad Fikri Titien Kumala Sari Tria Nova Wika Febriani Yanolanda Suzantri H Yessi Mardiana Yode Arliando Yoli Andi Rozzi