Mining Grouping Biopharmaceutical Plants in Indonesia Using the K-Means Algorithm: Application of Data Mining in Production
English
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Ridha Maya Faza Lubis
*
Southern Taiwan University of Science and Technology (STUST),
Taiwan, Province of China
- Jen-Peng Huang Southern Taiwan University of Science and Technology, Taiwan, Province of China
- Mula Sigiro University of HKBP Nommensen, Medan, Indonesia
- Joel Panjaitan Akademi Teknik Deli Serdang, Indonesia (*) Corresponding Author
Abstract
There are various types of biopharmaceutical plants or medicinal plants in Indonesia, including ginger, galangal, kencur, turmeric, lempuyang and curcuma aeruginosa whose production is widespread in various provinces in Indonesia. reached 160 million USD annually. Then the application of data mining used to classify biopharmaceutical plant production data in Indonesia from this study resulted in 2 clusters namely cluster 0 which in this cluster is a cluster with low production value of biopharmaceutical plants in Indonesia, namely the Provinces of West Sumatra, Riau, Jambi, South Sumatra, Bengkulu, Lampung, Kep. Bangka Belitung, Kep. Riau, DKI Jakarta, DI Yogyakarta, Banten, Bali, West Nusa Tenggara, East Nusa Tenggara, West Kalimantan, Central Kalimantan, South Kalimantan, East Kalimantan, North Kalimantan, Central Kalimantan, Southeast Sulawesi, Maluku, West Papua and Papua. While cluster 1 is the cluster where the production rate of biopharmaceutical plants is the highest in Indonesia, namely the Provinces of North Sumatra, West Java, Central Java, East Java and South Sulawesi. From the results that have been obtained, it is hoped that it will be useful for organizations, groups or individuals engaged in the biopharmaceutical plant sector so that they can review the existing deficiencies and can increase the production of biopharmaceutical plants in each province.
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