Article Per Year (5 Year)
p-Index From 2021 - 2026
3.575
P-Index
This Author published in this journals
All Journal ComEngApp : Computer Engineering and Applications Journal JSI: Jurnal Sistem Informasi (E-Journal) Jurnal Teknologi Informasi dan Ilmu Komputer Annual Research Seminar Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) BAREKENG: Jurnal Ilmu Matematika dan Terapan PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Jurnal Infomedia Riau Journal of Empowerment Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) CCIT (Creative Communication and Innovative Technology) Journal Indonesian Journal of Electrical Engineering and Computer Science Sriwijaya Journal of Informatics and Applications Jurnal Generic Jurnal Informatika dan Rekayasa Komputer Journal of Embedded Systems, Security and Intelligent Systems
Desty Rodiah
Department Informatics Engineering, Faculty Of Computer Science, Sriwijaya University
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Library & Information Science Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

Published : 32 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 32 Documents
Search

 1   2   3   4 
Implementation of K-Means and TOPSIS Algorithm for Determining High School Student Majors Yunita Yunita; Desty Rodiah; Putri Eka Wahyuni; Junia Kurniati; Dama Putra Sarpanda
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 2 (2025): June 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v6i2.8358

Abstract

This study focuses on the implementation of the K-means algorithm to assist high school students in selecting majors that align with their interests and skills. Utilizing a dataset of 231 grade X students from 2022, the K-means algorithm successfully formed two distinct clusters. The results indicated an accuracy of 81.81% for the K-means clustering process, recall of 81.75%, precision of 77.87%, and specificity of 81.75%. Following this, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was applied to rank the students within each cluster based on various weighted criteria. The TOPSIS method achieved a final ranking accuracy of 80.9%. The findings demonstrate the effectiveness of combining K-means and TOPSIS in facilitating informed decision-making for students regarding their academic paths.
Abstractive Dialogue Summarization using Fine-Tuning Pre-Trained Language Model BART Desty Rodiah; Hanif Syahri Ramadhani
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 3 (2026): June 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i3.7488

Abstract

The increasing volume of conversational data on digital platforms necessitates effective automatic summarization methods. This study investigates the use of a pre-trained BART (Bidirectional and Auto-Regressive Transformers) model for abstractive dialogue summarization on the DialogSum dataset, which consists of 14,460 English dialogues. The model is fine-tuned using a sequence-to-sequence framework with systematic hyperparameter tuning, including variations in learning rate, beam size, and training epochs. The optimal configuration is achieved using a learning rate of 2e-5, a beam size of 6, and 5 training epochs. Model performance is evaluated using ROUGE and BERTScore metrics. The experimental results show that the proposed model attains an average ROUGE-L F1-score of 0.40, indicating moderate structural similarity between generated and reference summaries, and an average BERTScore F1-score of 0.69, reflecting strong semantic alignment. These findings suggest that fine-tuned BART is effective in preserving semantic relevance in abstractive dialogue summarization, although further improvements are required to enhance lexical precision and discourse-level coherence.
Co-Authors Abdiansah Abdiansyah, Abdiansyah Afandi, Defrian Ahmad Nauvan Zikri Al Ghifran Akbar, Muhammad Rafi Al-Filambany, Muhammad Gibran Allsela Meiriza, Allsela Alvi Syahrini Utami Angga Adiningrat Mulyanata Anita Desiani Ardani, Vanya Terra Ari Firdaus Arti Dian Nastiti Buchari, Muhammad Ali Dama Putra Sarpanda Defrian Afandi Dellin Irawan Dian Palupi Rini Dian Palupi Rini Dicky Ahmad Rizaldi Dinda Lestarini Dite Geovanni Erwin Erwin Erwin, Erwin Fahriza, Dicky Febrivia, Pretty Fujianti Firdaus Firdaus Fitria Khoirunnisa Geovanni, Dite Hanif Syahri Ramadhani Irawan, Dellin Irmeilyana Jambak, Muhammad Ihsan Junia Kurniati Junia Kurniati Junia Kurniati, Junia Kanda Januar Miraswan Luh Sri Mulia Eni M. Fachrurrozi . Mardiana Mardiana Marjusalinah, Anna Dwi Mastura Diana Marieska Mudinillah, Adam Muhammad Akmal Shidqi Muhammad Gibran Al-Filambany Muhammad Naufal Rachmatullah Ngudiantoro . Novi Yusliani Nur Hamidah Oktaria Permata Sari Osvari Arsalan Putri Eka Wahyuni Qurrota ‘Aini Muthmainnah Rizki Kurniati Rusdi Efendi Sadana, Feron Samsuryadi Samsuryadi Saparudin Saparudin Sarifah Putri Raflesia Shidqi, Muhammad Akmal Sri Indra Maiyanti Sri Indra Maiyanti Sugandi Yahdin Vanya Terra Ardiani Winda Agusthia Yunita YUNITA Yunita Yunita Yunita Yunita Yunita Yunita