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All Journal Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD
Fitri, Nurul Aisyah
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Computer Science & IT

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Pengelompokan Data Pertumbuhan dan Kontribusi Ekonomi Indonesia Menurut Provinsi Menggunakan Metode K-Means Clustering Maulidiah, Rizka; Muchtar, Mutmainnah; Fitri, Nurul Aisyah; Asriani, Ika; Yasmine, Mutiara Putri
Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Vol. 6 No. 2 (2023): J-SISKO TECH EDISI JULI
Publisher : STMIK Triguna Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jsk.v6i2.7769

Abstract

Since the Covid-19 pandemic in recent years, several countries have been preoccupied with how to break the chain of the spread of the virus, including Indonesia, whose government policies are considered contradictory in efforts to improve the economy in Indonesia so that the economy has decreased in many regions in Indonesia. The importance of restoring the regional economy in order to improve people's welfare requires the government to be able to pay more attention to the region. to group the economic growth and economic contribution of Indonesian cities using data mining techniques with the K-Means Clustering algorithm using rapid miner tools. This research will classify into 3 clusters, high, medium, and low clusters. The results obtained for Indonesia's economic growth resulted in 2 provinces for high clusters, 1 low cluster, and 31 provinces for medium clusters. For the economic contribution of high clusters are 3 provinces, low clusters are 24 provinces, and medium clusters are 7 provinces. This method is considered to work well on the object of this research data.
Co-Authors Asriani, Ika Maulidiah, Rizka Mutmainnah Muchtar Yasmine, Mutiara Putri