JIKSI (Jurnal Ilmu Komputer dan Sistem Informasi)
Vol 1, No 1 (2013): Jurnal Ilmu Komputer dan Sistem Informasi

PENENTUAN KELAS DENGAN NEAREST NEIGHBOR CLUSTERING DAN PENGGUNAAN METODE NAÏVE BAYES UNTUK KLASIFIKASI DOKUMEN

Handry Wardoyo (Unknown)
Jeanny Pragantha (Unknown)
Viny Christanti M. (Unknown)



Article Info

Publish Date
31 Dec 2013

Abstract

Clustering is a process of grouping documents that will form into several classes. The difference between clustering with classification is the classification will determine the class of the new document and the result is the new document will be joined into one class. In this research, clustering or grouping is used to group documents into classes based on threshold values. Several experiment is conducted to get the optimal threshold value. The optimal threshold will be used to train data clustering for naive bayes. The results of naive bayes training is used to determine the class of new document in testing phase. Results of clustering and classification depends on the words in the document, the narrower the discussion, the more accurate the results obtained from clustering and classification

Copyrights © 2013






Journal Info

Abbrev

jiksi

Publisher

Subject

Computer Science & IT Mathematics Other

Description

Jurnal Ilmu Komputer dan Sistem Informasi (JIKSI) diterbitkan oleh Fakultas Teknologi Informasi Universitas Tarumanagara (FTI Untar) Jakarta sebagai media publikasi karya ilmiah mahasiswa program studi Teknik Informatika dan Sistem Informasi FTI Untar. Karya-karya ilmiah yang dihasilkan berupa hasil ...