IMPLEMENTASI METODE WEIGHTED PRODUCT DAN FUZZY C- MEANS DALAM PEMILIHAN PEMINATAN JURUSAN PADA SMA PERGURUAN RAKYAT 2
Sari
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.
Keywords: Clustering, Major Student, Fuzzy C-Means, Weighted Product
Teks Lengkap:
PDFReferensi
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
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