2019
DOI: 10.37385/jaets.v1i1.18
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Implementation Of Data Mining For Determining Majors Using K-Means Algorithm In Students Of SMA Negeri 1 Pangkalan Kerinci

Abstract: SMA Negeri 1 Pangkalan kerinci is one of the middle schools located at Jalan Lintas Timur Kerinci Pelalawan Indonesia which currently has 2 majors namely Science and IPS. This student majors can lead learners to focus more on developing their own abilities and interests. Selection of inappropriate majors can be very detrimental to students of their interests and careers in the future. With the majors are expected to maximize the potential, talent or individual talents, so as to maximize academic value. Based o… Show more

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Cited by 24 publications
(13 citation statements)
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“…A wide range of procedures including partitioning methods, hierarchical clustering methods, density-based clustering methods, and grid-based methods have been introduced to identify the similarity or differences among the observations and thus enable optimal clustering of the samples. The Lloyd algorithm is used in this work given that it is a partition method that can be applied easily using the K-means technique, , which involves the iterative application of three steps until convergence is achieved: Randomly initializing the center point of the clusters; Distributing samples among the clusters by clustering each sample to its nearest center; and Updating the centers’ position using the average values of each cluster’s members. …”
Section: Modeling Frameworkmentioning
confidence: 99%
“…A wide range of procedures including partitioning methods, hierarchical clustering methods, density-based clustering methods, and grid-based methods have been introduced to identify the similarity or differences among the observations and thus enable optimal clustering of the samples. The Lloyd algorithm is used in this work given that it is a partition method that can be applied easily using the K-means technique, , which involves the iterative application of three steps until convergence is achieved: Randomly initializing the center point of the clusters; Distributing samples among the clusters by clustering each sample to its nearest center; and Updating the centers’ position using the average values of each cluster’s members. …”
Section: Modeling Frameworkmentioning
confidence: 99%
“…Irawan [20] k-means clustering CRISP-DM. Successfully applied data mining techniques with the k-means clustering method which aims to help students determine the correct course according to the established criteria.…”
Section: Referencesmentioning
confidence: 99%
“…Data mining adalah suatu kegiatan analisa data untuk mencari suatu pola tertentu, dengan jumlah data yang besar dan bertujuan utuk menghasilkan informasi yang dapat digunakan dan dikembangkan lebih lanjut [11]. Data mining adalah metode untuk menemukan informasi baru yang berguna dari kumpulan data yang besar dan dapat membantu dalam pengambilan keputusan [12].…”
Section: Data Miningunclassified