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All Journal Brahmana : Jurnal Penerapan Kecerdasan Buatan
Sundari Retno Andani
AMIK Tunas Bangsa, Pematangsiantar, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering

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Clustering Pada Pelanggan Perusahaan Air Bersih Dengan Algoritma K-Means Arif Ramadhan Siregar; Sundari Retno Andani; Widodo Saputra
Brahmana : Jurnal Penerapan Kecerdasan Buatan Vol 1, No 1 (2019): Edisi Desember
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (375.348 KB) | DOI: 10.30645/brahmana.v1i1.2

Abstract

progress, and increasing living standards have caused the need for clean Clean water services are a very important component of public services. Water is a basic need that cannot be separated from human life. The supply of clean water is of particular concern to every country in the world, including in Indonesia. Population growth, development water to continue to increase. Technological improvements and rapid population growth are now encouraging mineral water companies to continue to innovate and expand their market network in order to continue to survive and compete with companies - companies. A product that can be desired by consumers must be able to provide satisfaction to consumers who consume these products. In realizing the goals to achieve customer satisfaction, companies must be able to learn in advance about products that consumers are interested in, habits carried out by consumers, why consumers are interested in consuming these items, and how many products are needed by consumers. The author wants clean water customers which will be clustered using the K-means algorithm to do which provinces will get customers of clean water companies.
Teknik Data Mining Dalam Clustering Produksi Susu Segar Di Indonesia Dengan Algoritma K-Means Ilham Safitra Damanik; Sundari Retno Andani; Dedi Sehendro
Brahmana : Jurnal Penerapan Kecerdasan Buatan Vol 1, No 1 (2019): Edisi Desember
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (583.289 KB) | DOI: 10.30645/brahmana.v1i1.5

Abstract

Milk is an important intake to meet nutritional needs. Both consumed by children, and adults. Indonesia has many producers of fresh milk, but it is not sufficient for national milk needs. Data mining is a science in the field of computers that is widely used in research. one of the data mining techniques is Clustering. Clustering is a method by grouping data. The Clustering method will be more optimal if you use a lot of data. Data to be used are provincial data in Indonesia from 2000 to 2017 obtained from the Central Statistics Agency. The results of this study are in Clusters based on 2 milk-producing groups, namely high-dairy producers and low-milk producing regions. From 27 data on fresh milk production in Indonesia, two high-level provinces can be obtained, namely: West Java and East Java. And 25 others were added in 7 provinces which did not follow the calculation of the K-Means Clustering Algorithm, including in the low level cluster.
Co-Authors Arif Ramadhan Siregar Dedi Sehendro Ilham Safitra Damanik Widodo Saputra