KLASIFIKASI TEKS DATA SHORT MESSAGE SERVICES (SMS) BERBAHASA INDONESIA MENGGUNAKAN ARTIFICIAL NEURAL NETWORK

ADITYA, DWIPUTRA and Yusliani, Novi and Satria, Hadipurnawan (2024) KLASIFIKASI TEKS DATA SHORT MESSAGE SERVICES (SMS) BERBAHASA INDONESIA MENGGUNAKAN ARTIFICIAL NEURAL NETWORK. Undergraduate thesis, Sriwijaya University.

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Abstract

The development of information and communication technology, especially the internet, has created various messaging platforms such as WhatsApp, Line, Messenger, email, and Short Message Services (SMS). Nonetheless, the use of SMS has not been completely replaced by digital messaging apps in Indonesia. Therefore, SMS is still an important part of digital communication in Indonesia. In this context, SMS not only contains informative things, but also contains scams and promos that can harm and disturb the convenience of SMS users themselves. To overcome this, text classification is needed on SMS data, especially those in Indonesian. The main objective of this research is to build a system that is able to classify Indonesian SMS text data using Artificial Neural Network (ANN) into three categories, namely normal, fraud, and promo. The dataset used in this research consists of 1113 SMS that have been labeled and divided into 80% training data and 20% test data. Using the ANN algorithm, this research model achieved an accuracy of 95.5%, and produced an average value of precision 95%, recall 95%, and f1-score 95%. Keywords: Artificial Neural Network, SMS, Spam, Text Classification

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Jaringan Syaraf Tiruan, Klasifikasi Teks, SMS, Spam
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Dwiputra Aditya
Date Deposited:	25 Jun 2024 04:05
Last Modified:	25 Jun 2024 04:05
URI:	http://repository.unsri.ac.id/id/eprint/147874

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