Klasifikasi Penyebab Penyalahgunaan Narkoba Dari Berita Online Dengan Menggunakan Naive Bayes

  • Laili Wahyunita atpn
Keywords: naive bayes, preprocessing data, text document representatio, presicion, recall

Abstract

This research conducted the classification process by applying the method of classification of Naive Bayes. News article document is one form of text data that is not structured so that requires the process of cleaning data and pre-processing first. The Naive Bayes approach is an approach that refers to Bayes's Theorem, where it uses the principle of statistical opportunity to combine previous knowledge. The use of this technique is based on the need of the system to know the probability value of the data to be classified. Waterfall method was used for built this classificaiton system. Accuracy rate up to 60 % with the highest precision and recall is 80% and 90%.

Downloads

Download data is not yet available.

References

[1] Arifin, A. Z., & Setiono, A. N. (2002). Klasifikasi dokumen berita kejadian berbahasa indonesia dengan algoritma single pass clustering. In Prosiding Seminar on Intelligent Technology and its Applications (SITIA), Teknik Elektro, Institut Teknologi Sepuluh Nopember Surabaya.
[2] Singhal, Anoop., “An Overview of Data Warehouse, OLAP and Data Mining“,” Data Warehousing and Data Mining Techniques for Cyber Security”, New York,2007
[3] Bramer, Max., “Principles of Data Mining”,Springer, London, 2007.
[4] Afiatin, T., 2008, Pencegahan penyalahgunaan narkoba, Gadjah Mada University Press, Yogyakarta.
[5] Amir, M.P., dan Syahrul, B., 2007, Narkoba ancaman generasi muda, Gerpana, Kalimantan Timur.
[6] Candradewi, I. and Harjoko, A., 2015. Pemrosesan Video Untuk Klasifikasi Jenis Kendaraan Menggunakan Algoritma Support Vector Machine (Doctoral dissertation, Universitas Gadjah Mada).
[7] Damayanti, R., 2015, Laporan akhir, Survey Nasional Perkembangan Penyalahguna Narkoba Tahun Anggaran 2014, BNN,Jakarta.
[8] Han, J. dan Kamber, M., 2006, Data Mining:Concepts and Technique 2nd Edition, Morgon Kauffman Publisher, San Fransisco.
[9] Hamzah, A. (2012). KLASIFIKASI TEKS DENGAN NAÏVE BAYES CLASSIFIER (NBC). Seminar Nasional Aplikasi Sains & Teknologi (SNAST) Periode III, (p. 9). Yogyakarta.
[10] Junianto, E., 2014, Penerapan PSO untuk Seleksi Fitur pada Klasifikasi Dokumen Berita Menggunakan Naive Bayes Classifier, Thesis, Pascasarjana Magister Ilmu Komputer STIMIK Nusa Mandiri, Jakarta
[11] Prasetyo, E, 2012, Data Mining Konsep dan Aplikasi Menggunakan MATLAB, 1st
ed., ANDI OFFSET, Yogyakarta.
[12] Pressman, R.S., 2002, Rekayasa Perangkat Lunak, (diterjemahkan oleh: LN Harnaningrum), Penerbit ANDI, Yogyakarta.
[13] Rish, I., 2001, An Empirical Study Of The Naive Bayes Classifier, IBM Research
Report, Thomas J. Watson Research Center, Yorktown Heights, New York.
[14] Situmorang, Y. B., 2012, Perlindungan Hukum Bagi Korban Penyalahgunaan Narkotika (Studi Kasus Di Polresta Yogyakarta) (Doctoral dissertation, UAJY).
[15] Siswantoro, S., 2004, Penegakan Hukum Psikotropika Dalam Kajian Sosiologis Hukum, PT RajaGrafindo Persada, Jakarta. hlm.2.
[16] Sumanthi, S. dan Esakkirajan, S.PY., 2007, Fundamentals of Relational Database Management Systems, Springer Belin Heidelberg.
[17] Tan, P.N., Stelnbach, M., and Kumar,V., 2006, Introduction to Data Mining, Pearson Education, Boston
Published
2017-06-12
Section
Articles
Abstract viewed = 421 times
PDF downloaded = 357 times