Implementasi Metode Weighted Product Dan Fuzzy C-Means Dalam Pemilihan Peminatan Jurusan Pada SMA Perguruan Rakyat 2

Authors

  • Eri Riana Universitas Bina Sarana Informatika

DOI:

https://doi.org/10.30865/jurikom.v5i6.999

Abstract

As per the rules applicable curriculum in Indonesia, high school students of class X to class XI up to experience election majors. Majors are available in the high school fields of interest include Natural Sciences, Social Sciences, and Linguistics. Majors will be tailored to students' abilities in areas of interest that exist, the goal for later in life, lessons are given to students to be more focused because it was in accordance with the ability of the field of interest. One of the considerations for selecting students are majors in determining student achievement in semester one and two (class X) in the form of scores. Lack of accuracy of the electoral process in the majors with the manual system of high school led to the need for the use of computational methods for grouping students majoring in the electoral process. Weighted Product Method and Fuzzy C-Means is a method that is easy and often used in the data grouping technique for making an estimate that is efficient and does not require a lot of parameters. Several studies have concluded that the method of Weighted Product and Fuzzy C-Means can be used to classify data based on certain attributes. This research will be used Weighted Product method and Fuzzy C-Means to cluster the data based on high school students value the core subjects for the majors. This study also tested the accuracy of the method and the Product Weighted Fuzzy C-Means in determining the majors in high school.

References

Kusrini, 2006. â€Algoritma Data Miningâ€,Yogyakarta : Andi

Kusumadewi, S, 2004. “Aplikasi Logika Fuzzy Untuk Pendukung Keputusanâ€, Yogyakarta : Graha Ilmu.

Larose, Daniel T. 2005, “Discovering Knowledge in Data : An Introduction to Data Miningâ€. John Willey & Sons, Inc

Mangkoesapoetra, Arief. 2004 “Statistika : Analisa Multivariat, Seri Metode Kuantitatifâ€. Jakarta : STMIK Nusa Mandiri

Maman, 2006. “Sistem Pendukung Keputusan : Model Penentuan Siswa Teladan Pada SMK YP-Karya I Tangerang dengan Pendekatan Logika Fuzzyâ€. Jakarta : Universitas Budi Luhur

Marimin, Nurul. 2010. “Aplikasi Teknik Pengambilan Keputusan Dalam Rantai Pasokâ€. Bogor : Cetakan 1 IPB Press

Pramudiono, I. 2006. Apa Itu Data Mining ? http://datamining.japati.net/bin/indodm.cgi

Diakses tanggal 28 Oktober 2013

Sri, Hari. 2010. “Aplikasi Logika Fuzzy Untuk Pendukung Keputusanâ€. Yogyakarta : Edisi 2 Graha Ilmu

Sri Kusuma Dewi, Hartati, “Neuro Fuzzy, Integrasi Sistem Fuzzy Dan Jaringan Syarafâ€. Yogyakarta : Graha Ilmu

Eko Sudaryanto, 2009, “Pengaruh Minat Belajar dan Penjurusan Terhadap Prestasi Belajar Siswa di SMK Katolik ST Lois Randublatungâ€, Skripsi, Fakultas Keguruan dan Ilmu Pendidikan, Universitas Muhammadiyah Surakarta, Surakarta

Irfan, Nasrulloh. 2011, “Model Pemilihan Jurusan SMK Teknologi Informasi Dengan Pendekatan Logika Fuzzy†Jakarta : Universitas Budi Luhur

Ernawati, Susanto (2009), “Pembagian Kelas Peserta Kuliah Berdasarkan Fuzzy Clustering dan Partition Coefficient and Exponential Separation Indexâ€, Program Studi Teknik Informatika, Universitas Atma Jaya, Yogyakarta.

Arwan Ahmad Khoiruddin, 2007, “Menentukan Nilai Akhir Kuliah Dengan Fuzzy C-Meansâ€, Proceeding pada Seminar Nasional Sistem dan Informatika di Bali, Jurusan Teknik Informatika, Universitas Islam Indonesia, Yogyakarta

Dunham, Margaret,H. (2003), “Data Mining Introuctory and Advanced Topicsâ€, New Jersey, Prentice Hall.

Kusumadewi, S., Hartati, S., 2006, Fuzzy Multi Atribute Decision Making, Graha Ilmu, Yogyakarta

Additional Files

Published

2018-12-27

How to Cite

Riana, E. (2018). Implementasi Metode Weighted Product Dan Fuzzy C-Means Dalam Pemilihan Peminatan Jurusan Pada SMA Perguruan Rakyat 2. JURNAL RISET KOMPUTER (JURIKOM), 5(6), 540–562. https://doi.org/10.30865/jurikom.v5i6.999