Implementasi Algoritma K-Medoids Untuk Mengelompokkan Limbah Pabrik Yang Berbahaya (Studi Kasus: PT.Indowastek)

Almendo Hidac Rislen Sihite (Universitas Budi Darma, Medan)

KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer)
Vol 4, No 1 (2020): The Liberty of Thinking and Innovation

Waste is waste material resulting from human activities that has no economic value. Waste has types, namely: liquid waste, gas waste, solid waste, and hazardous waste, where the most dangerous waste for humans is hazardous waste. Data mining is the process of recognizing an interesting knowledge of the amount of data in the database and so that a pattern is obtained that has a method, one of the K-Medoids algorithms. The result of this research is where a hazardous factory waste can be grouped into harmful wastes in the company PT. Indowastek with the K-Medoids algorithm, if the company has no problem determining these wastes with this algorithm makes it easier for PT Indowastek.Keywords: K-Medoids Algorithm, Data Mining, Waste, Hazardous