Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal INTECOMS: Journal of Information Technology and Computer Science Jurnal Teknologi Informatika dan Komputer
Hendra Rahman
Universitas Pamulang
Computer Science & IT Electrical & Electronics Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Monitoring Dan Analisis Traffic Jaringan Internet Pada Store PT. Central Mega Kencana Dengan Software Zabbix Mohammad Bahtiar; Hendra Rahman; Triratna Rahayu Rahmawati; Nunuk Irawati; Thoyyibah T
INTECOMS: Journal of Information Technology and Computer Science Vol 7 No 3 (2024): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/intecoms.v7i3.10323

Abstract

Masalah jaringan internet yang sering dialami oleh beberapa store di PT Central Mega Kencana adalah ketika kecepatan internet store lambat dibeberapa daerah di Indonesia maka tim store tersebut menghubungi tim IT untuk melakukan pengecekan, setelah dilakukan pengecekan terdapat beberapa store yang load pemakaian bandwidth nya cukup besar dan perlu diupgrade dari sisi layanan ISP (Internet Service Provider). Tujuan dilakukan penelitian ini adalah untuk mendapatkan data yang dapat menjelaskan bagaimana mekanisme monitoring jaringan internet store, melihat kondisi router store yang terhubung apakah terjadi down internet atau tidak serta sebagai dasar pengajuan upgrade layanan ISP yang digunakan pada setiap store. Metode yang digunakan dalam penelitian ini menggunakan metode action research. Hasil dari penelitian ini menampilkan gambar traffic jaringan dari 5 store acak yang di monitoring perhari selama 7 hari, traffic tertinggi, traffic terendah, rata-rata, dan downtime untuk rata-rata traffic. Dengan adanya software ZABBIX dapat memudahkan seorang administrator IT dalam memonitoring suatu jaringan, dan dapat juga mengetahui apabila terjadinya trouble.
Sentiment Analysis of the Indonesian Megathrust Earthquake and Tsunami Issue Using BERT and Roberta Methods Hendra Rahman; Taswanda Taryo; Sudarno Wiharjo
Jurnal Teknologi Informatika dan Komputer Vol. 12 No. 1 (2026): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v12i1.3563

Abstract

The megathrust earthquake in Indonesia is a major potential natural disaster capable of triggering high-magnitude earthquakes and tsunamis, thereby influencing public perception. This study aims to analyze public opinion and identify the main topics related to the megathrust earthquake issue using Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT Pretraining Approach (RoBERTa) models. The dataset consists of 16,592 comments collected from the X social media platform during the period 2012–2025, which were classified into three sentiment categories, positive, negative, and neutral. The research methodology included exploratory data analysis, text preprocessing, model training, and evaluation using four experimental scenarios. The results indicate that the best performance was achieved using an 80:10:10 train–validation test split with ten training epochs. The BERT model outperformed RoBERTa, achieving an accuracy of 92,4350%, precision of 92,4291%, recall of 92,4350%, and F1-score of 92,4292%. These findings demonstrate that BERT is more effective in capturing the linguistic context of the Indonesian language. Furthermore, this study contributes to the advancement of artificial intelligence-based sentiment analysis for monitoring public opinion on disaster-related issues and provides a valuable foundation for developing more effective risk communication strategies, disaster mitigation education, and evidence-based policymaking that is more responsive to public perception.
Co-Authors Mohammad Bahtiar Nunuk Irawati Sudarno Wiharjo Taswanda Taryo Thoyyibah T Triratna Rahayu Rahmawati