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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Journal of ICT Research and Applications Indonesian Journal on Computing (Indo-JC) Majalah Ilmiah UNIKOM
Ruskanda, Fariska Zakhralativa
Widyatama University
Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Engineering Law, Crime, Criminology & Criminal Justice Social Sciences

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Journal : Indonesian Journal on Computing (Indo-JC)

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Study on the Effect of Preprocessing Methods for Spam Email Detection Fariska Zakhralativa Ruskanda
Indonesia Journal on Computing (Indo-JC) Vol. 4 No. 1 (2019): Maret, 2019
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/INDOJC.2019.4.1.284

Abstract

The use of email as a communication technology is now increasingly being exploited. Along with its progress, email spam problem becomes quite disturbing to email user. The resulting negative impacts make effective spam email detection techniques indispensable. A spam email detection algorithm or spam classifier will work effectively if supported by proper preprocessing steps (noise removal, stop words removal, stemming, lemmatization, term frequency). This research studies the effect of preprocessing steps on the performance of supervised spam classifier algorithms. Experiments were conducted on two widely used supervised spam classifier algorithms: Naïve Bayes and Support Vector Machine. The evaluation is performed on the Ling-spam corpus dataset and uses evaluation metrics: accuracy. The experimental results show that different preprocessing steps give different effects to different classifier.
Co-Authors Ayu Purwarianti Dwi Hendratmo Widyantoro Masayu Leylia Khodra Nadya Aditama Stefanus Stanley Yoga Setiawan