Analisis Clustering Dokumen Tugas Akhir Mahasiswa Sistem Informasi Universitas Nasional menggunakan Metode K-Means Clustering
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Abstract
The purpose of this study was to determine the results of the analysis of the final project document for students majoring in information systems, National University. The research data is grouped based on the theme, object and research method. In this study, the K-Means Clustering method will be used which in the data includes the type of final project, year of publication and reasons for selecting the data. The data collection technique was chosen from the thesis document. The subjects in this study were part of the document that was processed in the abstract. Based on the results of the Clustering process above using the K-means algorithm method and the rapidminer application, it is concluded; 1) In the three clusters, it shows that the final project data 1 has 3 data, the final project 2 has 5 data, the final project 3 has 3 data and the final project 4 has 5 data., 2) In the three clusters the data is the most years old. group 3, namely in cluster 2 there are 3 data, cluster 3 there is 1 data, 3) In the three clusters, it shows that the data for the selection of 3 at least in cluster 2 there is 1 data.
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Genius Zendrato, F. S., Triayudi, A., & E, E. T. (2022). Analisis Clustering Dokumen Tugas Akhir Mahasiswa Sistem Informasi Universitas Nasional menggunakan Metode K-Means Clustering. Jurnal JTIK (Jurnal Teknologi Informasi Dan Komunikasi), 6(1), 70–76. https://doi.org/10.35870/jtik.v6i1.389
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Computer & Communication Science
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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Romindo, R., Muttaqin, M., Rasinus, R., Israwan, L.F., Yuswardi, Y., Karim, A., Sari, A.N., Putri, E.E. and Samosir, K., 2021. Sistem Informasi. Yayasan Kita Menulis.
Putri, S.U., Irawan, E. and Rizky, F., 2021. Implementasi Data Mining Untuk Prediksi Penyakit Diabetes Dengan Algoritma C4. 5. Kesatria: Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen), 2(1), pp.39-46.
Ginantra, N.L.W.S.R., Arifah, F.N., Wijaya, A.H., Septarini, R.S., Ahmad, N., Ardiana, D.P.Y., Effendy, F., Iskandar, A., Hazriani, H., Sari, I.Y. and Gustiana, Z., 2021. Data Mining dan Penerapan Algoritma. Yayasan Kita Menulis.
Jabat, J.T. and Murdani, M., 2019. Penerapan Data Mining Pada Penjualan Produk Retail Menggunakan Metode Clustering. Pelita Informatika: Informasi dan Informatika, 8(1), pp.26-32.
Sibuea, M.L. and Safta, A., 2017. Pemetaan Siswa Berprestasi Menggunakan Metode K-Means Clustring. JURTEKSI (Jurnal Teknologi dan Sistem Informasi), 4(1), pp.85-92.
Sani, A., 2018. Penerapan metode k-means clustering pada perusahaan. Jurnal Ilmiah Teknologi Informasi, 353, pp.1-7.
Amri, M.A., Windarto, A.P., Wanto, A. and Damanik, I.S., 2019. Analisis Metode K-Means Pada Pengelompokan Perguruan Tinggi Menurut Provinsi Berdasarkan Fasilitas Yang Dimiliki Desa. KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer), 3(1).
Dewi, S.M., Windarto, A.P., Damanik, I.S. and Satria, H., 2019, August. Analisa Metode K-Means pada Pengelompokan Kriminalitas Menurut Wilayah. In Seminar Nasional Sains dan Teknologi Informasi (SENSASI) (Vol. 2, No. 1).
Nurzahputra, A., Muslim, M.A. and Khusniati, M., 2017. Penerapan algoritma K-Means untuk clustering penilaian dosen berdasarkan indeks kepuasan mahasiswa. Techno. Com, 16(1), pp.17-24.
Khanmohammadi, S., Adibeig, N. and Shanehbandy, S., 2017. An improved overlapping k-means clustering method for medical applications. Expert Systems with Applications, 67, pp.12-18.
Yu, S.S., Chu, S.W., Wang, C.M., Chan, Y.K. and Chang, T.C., 2018. Two improved k-means algorithms. Applied Soft Computing, 68, pp.747-755.
Chi, D., 2021, January. Research on the Application of K-Means Clustering Algorithm in Student Achievement. In 2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) (pp. 435-438). IEEE.
Fabregas, A.C., Gerardo, B.D. and Tanguilig III, B.T., 2017. Enhanced initial centroids for k-means algorithm. International Journal of Information Technology and Computer Science, 1, pp.26-33.
Mohd, W.M.W., Beg, A.H., Herawan, T., Noraziah, A. and Chiroma, H., 2019. Multi-dimensional K-Means Algorithm for Student Clustering. In Proceedings of the International Conference on Data Engineering 2015 (DaEng-2015) (pp. 119-128). Springer, Singapore.