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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Sistemasi: Jurnal Sistem Informasi Jurnal Teknologi Sistem Informasi dan Aplikasi JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Sistem Informasi dan Informatika (SIMIKA) CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) Jurnal Riset Sistem Informasi dan Teknologi Informasi (JURSISTEKNI) Jurnal Restikom : Riset Teknik Informatika dan Komputer Jurnal Computer Science and Information Technology (CoSciTech) JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Pengabdian West Science Jurnal Informatika: Jurnal Pengembangan IT
Muhammad Anton Permana
Nusa Putra University
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Public Health Social Sciences

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Crime index based on text mining on social media using multi classifier neural-net algorithm Teddy Mantoro; Muhammad Anton Permana; Media Anugerah Ayu
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 3: June 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i3.23321

Abstract

Everyday criminal issues appear on social media, even some crime news is often disturbing to the public but it gives a warning to the public to remain careful and alert to the surrounding environment. However, following large amounts of crime information on social media is not effective, especially for busy people. Therefore, there is a need to efficiently and effectively summarize information in a way that is meaningful and easy to see, attracts people’s attention, and can be used by law enforcement officials. The purpose of this study is to present the index crime based on social media by looking for patterns of crime. This study proposes the projected index crime based on crime trends by using text mining to classify tweet texts and post contents into 10 crime classes. The classification method uses the neural-net multi classifier algorithm which has several classifiers namely logistic regression, naïve bayes, support vector machine (SVM), and decision tree in parallel. In this approach, the classifier that provides the best accuracy will be the winning classifier and will be used in the next learning process. In this experiment, in using the multi classifier neural-net, the logistics regression classifier often provides the best accuracy.
Co-Authors Adhitia Erfina Agus Kuncoro Arny Lattu Aulia, Gesi Carty Irawan Dede Sukmawan Erlina Erlina Gina Syabani Hamzah, Shela Septiani Indriani Nurfitri Mauliyati, Sabrina Fauziah Media Anugerah Ayu, Media Anugerah Muhammad Alif Nuryaqin Muhammad Rahmat Faizal Muhammad Ramdani Mulyani, Eneng Sri Paisal, Irvan Pathur Ropik Rahman, Aura Ratri Pramudita Riska Fitria Rahmat Saepudin, Sudin Saputra, Dimas Selviani Widiastuti sihabudin sihab Siti Atisa Hartati Syachra Indyra Puteri Tahlia, Nita Teddy Mantoro Widy Karisma Wina Setiawaty Wisuda Jatmiko