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All Journal ILKOMNIKA: Journal of Computer Science and Applied Informatics Djtechno: Jurnal Teknologi Informasi Jurnal Ilmiah Ilmu Terapan Universitas Jambi JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Rahman, Dzul Fadli
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Industrial & Manufacturing Engineering

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Pendekatan Eksploratif dalam Analisis Data Harga Pangan Nasional dengan Tableau Rahman, Dzul Fadli; Munir, Agus Qomaruddin
ILKOMNIKA Vol 6 No 2 (2024): Volume 6, Nomor 2, Agustus 2024
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/ilkomnika.v6i2.659

Abstract

Penelitian ini menganalisis data Harga Pangan Nasional di Indonesia dari tahun 2020 hingga 2023 menggunakan metode Exploratory Data Analysis (EDA). Python, Visual Studio Code dan Tableau dipilih untuk kemudahan dalam penggunaan library statistik dan visualisasi data. Analisis dilakukan dalam tiga bentuk: univariat, bivariat, dan multivariat. Hasil univariat menunjukkan distribusi pasar dan sumber pangan, dengan dominasi bahan nabati. Analisis bivariat menunjukkan harga pangan lebih tinggi di wilayah timur, dengan daging sebagai komoditas termahal dan beras yang termurah. Analisis multivariat membandingkan harga pangan di Yogyakarta dan Merauke, menunjukkan harga lebih tinggi di Merauke kecuali beras yang stabil di kedua kota. Studi ini juga menekankan pentingnya visualisasi data dalam mempermudah pemahaman informasi kompleks, menggunakan berbagai jenis grafik untuk menunjukkan pola dan tren yang membantu pengambilan keputusan strategis. Hasil penelitian ini dapat dikembangkan untuk memprediksi perubahan harga pangan dan memberikan wawasan yang lebih dalam.
Optimasi Algoritma Support Vector Machine untuk Analisis Sentimen dengan Bayesian Optimization Yudianto, Muhammad Resa Arif; Zakariah, Masduki; Rozam, Nadhir Fachrul; Rahman, Dzul Fadli; Sari, Tika Novita; Mustofa, Zaenal
Jurnal Teknik Informatika dan Sistem Informasi Vol 11 No 3 (2025): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v11i3.11524

Abstract

This study examines the effect of Bayesian Optimization in improving the performance, computational efficiency, and sustainability of Aspect-Based Sentiment Analysis models using Support Vector Machine (SVM). A dataset consisting of 988 customer reviews about Borobudur Temple, classified into six dimensions: Attractiveness, Facilities, Accessibility, Visual Image, Price, and Human Resources is used to compare two scenarios, namely Baseline SVM and SVM enhanced with Bayesian Optimization (BO). Important metrics used include accuracy, computational duration, energy usage, and carbon emissions. The results show that BO significantly improves accuracy, especially on difficult aspects such as Facilities (from 0.7294 to 0.8682) and Price (from 0.8047 to 0.9576). The most complicated aspect, namely visual image due to the very minimal number of datasets (unbalanced), achieved an increase in accuracy from 0.6729 to 0.72. In addition, BO reduces training time, especially for resource-intensive tasks such as the visual image aspect, reducing training time from 13.04 seconds to 9.4 seconds. Substantial reductions in energy consumption and CO₂ emissions are seen in line with sustainable machine learning principles. The hyperparameter adaptability of SVM, with linear kernels performing well in simpler tasks, while polynomial and sigmoid kernels improve performance for more complex parts. BO substantially alleviates the limitations of Baseline SVM, offering a robust, efficient, and environmentally friendly solution for ABSA. Future research can explore more enhancements for complex tasks to improve performance and efficiency.
SEMANTIC WEB IMPLEMENTATION FOR ENHANCING BUDGET TRANSPARENCY IN YOGYAKARTA CITY GOVERNMENT: AN ONTOLOGY AND RDF-BASED FRAMEWORK Rahman, Dzul Fadli; Setiyawan, Ramadhana; Artanto, Herjuna
Djtechno: Jurnal Teknologi Informasi Vol 6, No 3 (2025): Desember
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v6i3.7448

Abstract

Penerapan teknologi Semantic Web dalam pengelolaan data pemerintah menjadi strategi penting untuk meningkatkan transparansi dan keterbacaan mesin terhadap data terbuka. Penelitian ini bertujuan untuk mentransformasikan data Anggaran Murni Kota Yogyakarta tahun 2022 dari format tabular ke dalam representasi semantik menggunakan Resource Description Framework (RDF) dan Web Ontology Language (OWL). Ontologi dikembangkan dengan mendefinisikan lima kelas utama, yaitu Anggaran, Daerah, KategoriAnggaran, KelompokAnggaran, dan JenisAnggaran, serta dilengkapi dengan object property dan data property yang menggambarkan relasi dan atribut antarentitas. Representasi RDF kemudian diuji menggunakan beberapa query SPARQL untuk mengekstraksi informasi, seperti total anggaran, surplus atau defisit, dan identifikasi entitas tanpa alokasi. Visualisasi struktur ontologi dilakukan menggunakan plugin OWLViz untuk memastikan konsistensi logis antar kelas dan properti. Hasil penelitian menunjukkan bahwa model ontologi yang dikembangkan mampu merepresentasikan struktur anggaran secara terstruktur, konsisten, dan mendukung kueri semantik. Penelitian ini memberikan kontribusi terhadap upaya keterbukaan data pemerintah daerah dan dapat dikembangkan lebih lanjut untuk integrasi lintas wilayah serta visualisasi interaktif berbasis Web Semantik.
DEVELOPMENT AND ISO 25010 EVALUATION OF A WEB-BASED LABORATORY AND WORKSHOP INVENTORY SYSTEM Wulandari, Bekti; Rahman, Dzul Fadli; Fitriyanto, Doni; Dewanto, Satriyo Agung; Muhammad Munir
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 10 No. 1 (2026): Volume 10, Nomor 1, February 2026
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v10i1.47430

Abstract

Effective management of laboratory tools and materials is essential to support experimentation and practical learning in higher education. However, many institutions still rely on manual inventory processes, which lead to data inaccuracies, inefficiencies, and limited monitoring capabilities. This study aims to develop and evaluate a web-based laboratory and workshop inventory management system tailored to the Department of Electronics and Informatics Education Engineering (DPTEI). The research adopts a Research and Development (R&D) design using the Waterfall Model, encompassing communication, planning, modeling, construction, and deployment phases. Data were collected from 22 participants (laboratory officers, workshop technicians, and lecturers) selected through purposive sampling. Requirement analysis was conducted via observations, structured interviews, and document review, while system evaluation employed questionnaires and automated testing tools. System quality was assessed using ISO 25010 criteria—functional suitability, reliability, performance efficiency, and usability—and a paired t-test was used to compare inventory management efficiency before and after implementation. The system achieved 100% functional suitability, very high reliability (up to 99.84% in stress testing), and strong performance efficiency with an average Largest Contentful Paint (LCP) of 1.180 seconds. The System Usability Scale (SUS) yielded a score of 84, classified as excellent, and the paired t-test (p = 0.002) indicated a significant improvement in inventory efficiency. These findings demonstrate that the developed system is robust, reliable, and well-accepted by users, contributing a domain-specific, empirically validated solution for digital resource management in academic laboratory settings.
Co-Authors Agus Qomaruddin Munir Bekti Wulandari Dewanto, Satriyo Agung Doni Fitriyanto Herjuna Artanto Muhammad Munir Muhammad Resa Arif Yudianto Nadhir Fachrul Rozam Setiyawan, Ramadhana Tika Novita Sari Zaenal Mustofa Zakariah, Masduki