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All Journal JATI (Jurnal Mahasiswa Teknik Informatika) Informatics and Digital Expert (INDEX)
Setio Wiyono, Briansyah
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Computer Science & IT Engineering

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Comparison of Classification for Indonesian Language News Documents Using Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM) Algorithms Sri Kusuma Aditya, Christian; Ridha Agam, Muh; Rezky Fadillah, Andhika; Setio Wiyono, Briansyah
Informatics and Digital Expert (INDEX) Vol. 6 No. 2 (2024): INDEX, November 2024
Publisher : LPPM Universitas Perjuangan Tasikmalaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36423/index.v6i2.1888

Abstract

The development of online news has grown very fast. The high volume of text documents was triggered by activities from various news sources. Due to the large amount of news that is included on the website, sometimes the news is posted not according to its category which is most likely caused by human error. The grouping of online news is important for user convenience in searching for news according to its category. It need an intelligent system that can classify online news automatically. This research evaluates deep learning techniques using LSTM and RNN, and compared with the results obtained from previous studies, which used the NBC algorithm. To experiment the system, an Indonesia News Corpus with 7 different categories and total 2100 documents, collected by crawling online national news portals, is used. Due to the unbalanced number of class compositions or news categories, integration is also carried out SMOTE. The average empirical results show that the classification accuracy from RNN with SMOTE with an accuracy of 95.2% and followed by LSTM with SMOTE is 97.8%, both of which are able to outperform the NBC method with an accuracy of 73.2%.
PENGEMBANGAN SISTEM MANAJEMEN KOS BERBASIS APLIKASI MOBILE PADA KOS SIDORAME12 Laksana Bhakti, Rysa; Nuryasin, Ilyas; Setio Wiyono, Briansyah
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 3 (2025): JATI Vol. 9 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i3.13708

Abstract

Bisnis rumah kos merupakan usaha yang menyediakan tempat tinggal sementara bagi perantau yang bekerja atau menempuh pendidikan. Namun, pengelolaan kos yang masih dilakukan secara manual sering kali menghadapi kendala dalam pencatatan penyewa, pembayaran sewa, dan administrasi keuangan. Penelitian ini bertujuan untuk mengembangkan sistem manajemen kos berbasis aplikasi mobile untuk Kos SidoRame12 guna meningkatkan efisiensi pengelolaan. Metode pengembangan yang digunakan adalah prototipe, yang memungkinkan iterasi perancangan berdasarkan umpan balik pengguna. Sistem ini dikembangkan menggunakan framework Flutter untuk frontend dan Laravel untuk backend. Pengujian dilakukan dengan metode Black-Box Testing dan User Acceptance Testing (UAT) untuk memastikan fungsionalitas serta kepuasan pengguna. Hasil pengujian menunjukkan bahwa sistem yang dikembangkan telah memenuhi kebutuhan pengguna dan dapat diterima dengan baik. Dengan adanya sistem ini, diharapkan pengelola kos dapat mengurangi kesalahan administrasi dan meningkatkan efisiensi operasional.
Co-Authors Eko Budi Cahyono Laksana Bhakti, Rysa Rezky Fadillah, Andhika Ridha Agam, Muh Sri Kusuma Aditya, Christian