Journal of Engineering and Applied Sciences

Year: 2019
Volume: 14
Issue: 15
Page No. 5123 - 5129

Power Plant Clustering in Indonesia by using k-Means

Authors : Purba Daru Kusuma

Abstract: There are two problems in Indonesian electricity statistical report that are published by the Ministry of Energy and Mineral Resources. First, most of these reports are presented in tabular form. Second, these reports are independent and have not been related to other data, yet such as geographic and demographic data. So, these reports are still difficult to be analyzed. In this research, we proceed and analyze the Indonesian power plant installed capacity data that is published by the Ministry of Energy and Mineral Resources. This data then is combined with the demographic and geographic data. The main research is to mapping the distribution of the installed capacity of power plants based on provinces. In this research, we use k-means clustering as the basis clustering method. The analyzed data is the installed capacity of the PLN’s power plants, both they are owned or rented. Based on the clustering result there are several findings in installed capacity of power plants in Indonesia. First, there are significant gap between provinces in the island of Java and provinces outside the island of Java. PLN’s owned power plants dominate in Java while PLN’s rented power plants dominate in outer Java. DI Yogyakarta is not only behind any provinces in the island of Java but also behind lots of provinces in Indonesia provinces in Sumatera are promising to competing East Java and Central Java.

How to cite this article:

Purba Daru Kusuma , 2019. Power Plant Clustering in Indonesia by using k-Means. Journal of Engineering and Applied Sciences, 14: 5123-5129.

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