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ComEngApp : Computer Engineering and Applications Journal
Published by Universitas Sriwijaya
ISSN : 22524274     EISSN : 22525459     DOI : 10.18495
Core Subject : Science, Engineering,
Computer Science & IT Engineering
ComEngApp-Journal (Collaboration between University of Sriwijaya, Kirklareli University and IAES) is an international forum for scientists and engineers involved in all aspects of computer engineering and technology to publish high quality and refereed papers. This Journal is an open access journal that provides online publication (three times a year) of articles in all areas of the subject in computer engineering and application. ComEngApp-Journal wishes to provide good chances for academic and industry professionals to discuss recent progress in various areas of computer science and computer engineering.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 333 Documents
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LoTQA: Local Benchmarking of Large Language Models for Table Question Answering Muhammad Arya All Fajri; Muhammad Ikhsan Rizki Pratama; Firdaus Firdaus; Abdiansah Abdiansah
Computer Engineering and Applications Journal Vol. 15 No. 2 (2026)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/comengapp.v15i2.1350

Abstract

TableQA memainkan peran penting dalam mendukung pengambilan keputusan berbasis data dan meningkatkan efisiensi pencarian informasi. Penggunaan Large Language Models (LLM) melalui layanan cloud atau API eksternal memungkinkan sistem untuk secara otomatis memahami struktur tabel dan konteks pertanyaan, melakukan generalisasi, penalaran kontekstual, dan memahami hubungan semantik antar entitas dalam tabel untuk menghasilkan jawaban yang lebih relevan dan akurat. Pendekatan ini mengakibatkan peningkatan signifikan dalam biaya komputasi, potensi risiko keamanan data, dan keterbatasan dalam pengembangan, kustomisasi, dan pengujian model. Penelitian ini mengusulkan LoTQA untuk tugas TableQA. LoTQA adalah pendekatan yang memanfaatkan eksekusi lokal untuk mengevaluasi dan membandingkan metode LLM dalam menghasilkan jawaban dari data tabel terstruktur. Evaluasi kinerja pada LoTQA (Qwen3:4b, LoRA Fine-tuned) memperoleh nilai SacreBLUE sebesar 8,613, BLEU-1 sebesar 35,623, BLEU-2 sebesar 26,592, BLEU-3 sebesar 22,723, ROUGE-1 sebesar 0,364, ROUGE-2 sebesar 0,177, ROUGE-L sebesar 0,311, dan METEOR sebesar 0,317. Hasil ini menunjukkan bahwa metode LoTQA cukup baik dalam menyediakan kalimat yang bermakna secara semantik untuk prediksi, bahkan dengan sumber daya yang rendah. Hasil evaluasi kinerja untuk setiap model LLM yang digunakan menunjukkan bahwa model Qwen3:4b mencapai skor tertinggi untuk SacreBLEU, ROUGE-1, ROUGE-2, ROUGE-L, dan METEOR. Studi ini menunjukkan bahwa LoTQA berkinerja cukup baik pada tugas TableQA, meskipun dengan sumber daya yang rendah.
A real-time intruder detection and notification system using the LBPH facial recognition method via the LINE application Nitit WangNo
Computer Engineering and Applications Journal Vol. 15 No. 2 (2026)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/comengapp.v15i2.1360

Abstract

Face detection and recognition in images and videos is a widely studied topic in the field of biometrics, with increasing importance in security and surveillance applications. This paper presents the development of a real-time face recognition system designed to enhance security and automation. The system utilizes a Haar-cascade classifier for initial face detection and the Local Binary Pattern Histogram (LBPH) algorithm for face recognition, based on a locally generated training dataset. It operates in two main stages: detecting human faces and identifying individuals. In cases where an unrecognized face is detected, the system sends an immediate alert via the LINE application. Key components of the system include real-time processing, identity verification, and access control. The proposed system shows strong potential for practical deployment in areas such as crowd monitoring and personal security in sensitive environments like airports. Experimental results demonstrate a recognition accuracy ranging from 90% to 93.45%, validating the effectiveness of the approach.
Implementation and Training of Linux-Based Network Administration to Enhance Network Infrastructure Izulhak Algi Fahrizal; Andi Rakhmat Baharuddin
Computer Engineering and Applications Journal Vol. 15 No. 2 (2026)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/comengapp.v15i2.1370

Abstract

This article aims to comprehensively synthesize the relationship between Linux server implementation, network administration training, and their impact on network infrastructure improvement. Linux servers are becoming increasingly important in modern network management because they support service flexibility, resource efficiency, security, automation, and high availability, while network administration training is a key factor in building the technical competencies of network administrators. This study employs a systematic review method on 35 scientific articles classified into three main topics: Linux server implementation, network administration training, and the impact on network infrastructure. The review results indicate that Linux server implementation contributes to improved performance, stability, efficiency, and reliability of network services, whereas hands-on training plays a role in enhancing administrators’ operational skills and readiness. These findings confirm that improvements in Linux server-based network infrastructure depend on the integration of the quality of technical implementation and the competencies of the personnel managing it.

Page 34 of 34 | Total Record : 333

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