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Analisis Klasifikasi SMS Spam Menggunakan Logistic Regression Ferin Reviantika Suprihati
Jurnal Sistem Cerdas Vol. 4 No. 3 (2021)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v4i3.166

Abstract

SMS or Short Message Service is usually found on cell phones. SMS is divided into two categories, namely SMS spam and SMS non-spam (ham). Spam SMS is an SMS that is annoying to phone users because it tends to contain messages that are not important such as promos and scams. Meanwhile, non-spam SMS (ham) tend to contain important SMS, such as messages from previous users. In this study, the classification of spam SMS and non-spam SMS (ham) was carried out using the logistic regression method. The purpose of this study is to distinguish or classify between spam and non-spam SMS (ham). The dataset in this study amounted to 1143 data, there are two columns, namely the text column and the label column. The number for spam messages is 566 messages and the number for non-spam messages is 577. The proposed method gets a better accuracy of 95%.