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All Journal METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi
Ari Rizkita
Universitas Efarina
Computer Science & IT Economics, Econometrics & Finance

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Akurasi K-Means dengan Menggunakan Cluster dan Titik Grid Terbaik pada Pemetaan Grid Interatif K-Means Johanes Terang Kita Perangin Angin; Ari Rizkita; Robet Robet; Octara Pribadi
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp127-129

Abstract

Traditional K-Means face 2 (two) main problems, namely: Determination of Initial Centroid and poor initial cluster. Determining the initial centroid using random numbers is one of the main problems in classical K-Means which results in low accuracy and long computation time. Likewise, determining the good centroid of each cluster without being accompanied by a process of paying attention to the performance of each cluster can also cause the accuracy value obtained is not good. This study will contribute to how the performance obtained by determining a good initial centroid is combined with the use of a good cluster. Determination of a good initial centroid is done by using the K-Means Grid Mapping which divides the determination of the centroid into several Grid Points. The result of this research is a combination of Iterative K-Means with Grid Mapping K-Means to become Iterative Grid Mapping K-Means which will get a good initial centroid and also a good cluster shown in the table of iris and abalone, comparison of the variables in the iris and abalone affecting the best cluster as a result.
Co-Authors Johanes Terang Kita Perangin Angin Octara Pribadi Robet Robet