Jurnal Gaussian
Vol 3, No 4 (2014): Jurnal Gaussian

PENERAPAN METODE KLASIFIKASI SUPPORT VECTOR MACHINE (SVM) PADA DATA AKREDITASI SEKOLAH DASAR (SD) DI KABUPATEN MAGELANG

Octaviani, Pusphita Anna (Unknown)
Wilandari, Yuciana (Unknown)
Ispriyanti, Dwi (Unknown)



Article Info

Publish Date
30 Oct 2014

Abstract

Accreditation is the recognition of an educational institution given by a competent authority, that is Badan Akreditasi Nasional Sekolah/Madrasah (BAN - S/M) after it is assessed that the institution has met the eight components of the accreditation assessment. An elementary school, as one of the compulsory basic education, should have the status of accreditation to ensure the quality of education. This study aimed to apply the classification method Support Vector Machine (SVM) on the data accreditation SD in Magelang. Support Vector Machine (SVM) is a method that can be used as a predictive classification by using the concept of searching hyperplane (separator functions) that can separate the data according to the class. SVM using the kernel trick for non-linear problems which can transform data into a high dimensional space using a kernel function, so that the data can be classified linearly. The results of this study indicate that the prediction accuracy of SVM classification using Gaussian kernel function RBF is 93.902%. It is calculated from 77 of 82 elementary schools that are classified correctly with the original classes. Keywords : Accreditation, Classification, Support Vector Machine (SVM), hyperplane, Gaussian RBF Kernel, Accuracy 

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Journal Info

Abbrev

gaussian

Publisher

Subject

Other

Description

Jurnal Gaussian terbit 4 (empat) kali dalam setahun setiap kali periode wisuda. Jurnal ini memuat tulisan ilmiah tentang hasil-hasil penelitian, kajian ilmiah, analisis dan pemecahan permasalahan yang berkaitan dengan Statistika yang berasal dari skripsi mahasiswa S1 Departemen Statistika FSM ...