COLLABORATIVE FILTERING SMS SPAM BERBAHASA INDONESIA MENGGUNAKAN ALGORITMA NAIVE BAYES

ANIK MUHANTINI , NIM. 09650055 (2013) COLLABORATIVE FILTERING SMS SPAM BERBAHASA INDONESIA MENGGUNAKAN ALGORITMA NAIVE BAYES. Skripsi thesis, UIN SUNAN KALIJAGA.

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Abstract

Sms is a way to communicate which is still popular to use. Some reasons why SMS still popular because the cost to send sms is cheap, sending and receiving sms is easy, fast, can be done everywhere and everytime. Sms also doesn’t need internet connection. SMS abuse that occurred in Indonesia such as SMS broadcast for promoting products, services, shopping discount, fraud sms of winning lottery, asking credits, deception for transferring money to a particular account. That sms is called spam sms. That sms isn’t expected to be accepted by users. This research is using Naïve Bayes algorithm to filter Indonesian sms spam that is received by android smartphone. This research is using Naïve Bayes algorithm because Naïve Bayes is one of lightweight and fast classification algorithms for training and testing. This research is also collaborate data spam sms that is saved in centralized database. Each user uses that spam sms database together. In this research, each user is considered to be honest when updating existing spam SMS data in the database server. The results of spam SMS filtering system in Indonesian language using Naïve Bayes algorithm, with collaborative spam SMS database is obtained classification result from the incoming SMS including SMS spam or ham class. Training data for SMS is SMS 110 spam SMS and 62 ham sms. Data for testing SMS is 50 ham SMS and 50 spam SMS. The accuracy of the results obtained values of 76%, precision obtained values 52% and recall of values 100%.

Item Type: Thesis (Skripsi)
Additional Information: Pembimbing : M. Taufiq Nuruzzaman, ST., M.Eng.
Uncontrolled Keywords: Keywords : Naïve Bayes, Filtering Spam, Collaborative, SMS, Indonesian Language
Subjects: Tehnik Informatika
Divisions: Fakultas Sains dan Teknologi > Teknik Informatika (S1)
Depositing User: Miftahul Ulum [IT Staff]
Date Deposited: 25 Apr 2014 09:06
Last Modified: 08 Mar 2016 10:44
URI: http://digilib.uin-suka.ac.id/id/eprint/12096

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