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All Journal SPEKTRUM INDUSTRI Jurnal Ilmiah Teknik Industri Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Bahasa Rupa INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Madani : Indonesian Journal of Civil Society Journal of Industrial Engineering and Operation Management (JIEOM) JENIUS: Jurnal Terapan Teknik Industri International Journal on Social Science, Economics and Art Jurnal Teknologi dan Manajemen Industri Terapan Journal Of Resource Management, Economics And Business (REMICS) Open Access DRIVERset
Achmad Zaki Yamani
Institut Teknologi Telkom Purwokerto
Religion Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Social Sciences Transportation

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Journal : Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)

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Penentuan Centroid Awal K-means pada Proses Clustering Data Evaluasi Pengajaran Dosen Ridho Ananda; Achmad Zaki Yamani
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 3 (2020): Juni 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (439.837 KB) | DOI: 10.29207/resti.v4i3.1896

Abstract

Decision making about microteaching for lecturers in ITTP with the low teaching quality is only based on three lowest order from teaching values. Consequently, the decision is imprecise, because there is possibility that the lecturers are not three. To get the precise quantity, an analysis is needed to classify the lecturers based on their teaching values. Clustering is one of analyses that can be solution where the popular clustering algorithm is k-means. In the first step, the initial centroids are needed for k-means where they are often randomly determined. To get them, this paper would utilize some preprocessing, namely Silhouette Density Canopy (SDC), Density Canopy (DC), Silhouette (S), Elbow (E), and Bayesian Information Criterion (BIC). Then, the clustering results by using those preprocessing were compared to obtain the optimal clustering. The comparison showed that the optimal clustering had been given by k-means using Elbow where obtain four clusters and 0.6772 Silhouette index value in dataset used. The other results showed that k-means using Elbow was better than k-means without preprocessing where the odds were 0.75. Interpretation of the optimal clustering is that there are three lecturers with the lower teaching values, namely N16, N25, and N84.
Co-Authors Ade Yanyan Ramdhani Ahmad Faisal Aiza Yudha Pratama Arif Wirawan Muhammad Aswan Munang Azril Dwi Setiawan Dina Rachmawati Dina Rachmawaty Elfa Swaratama Emmareta Fauziah Familia Dwi Winati Farid Nugroho Fauzan Romadlon Galih Putra Pamungkas Hikmah Yogi Prasojo Karima, Halim Qista Mardhiana, Hawwin Marier, Syauqie Muhammad Muhammad Alim Safa'at Muhammad Nur Faiz Muhammad Reza Yuriandhan Nabila Noor Qisthani Nizar Aulia Alharizmi Nurchasanah Nurchasanah Nurisusilawati, Isnaini Ridho Ananda Winati, Famila Dwi