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All Journal Journal of Information Technology and Computer Science Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal SOLMA Conference on Innovation and Application of Science and Technology (CIASTECH) Jurnal Aplikasi Dan Inovasi Ipteks SOLIDITAS Journal of Artificial Intelligence and Digital Business Prosidia Widya Saintek Pangripta Jurnal Ilmiah Kajian Perencanaan Pembangunan Maeswara: Jurnal Riset Ilmu Manajemen dan Kewirausahaan E-Amal: Jurnal Pengabdian Kepada Masyarakat JITEEHA: Journal of Information Technology Applications in Education, Economy, Health and Agriculture
Ahmad Fairuzabadi
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Social Sciences Transportation Other

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Analysis of Online Transportation Customer Satisfaction Using C4.5 Algorithm Irawan, Ryan Avrilio; Marpaung, Fhadillah Ain; Saputra, Idris Ivan; Widarti, Dinny Wahyu; Fairuzabadi, Ahmad
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 2 No. 1 (2025): February
Publisher : Lumina Infinity Academy Foundation

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In the era of increasing business competition, transportation companies are required to enhance the efficiency and effectiveness of their services. One method that can be employed to optimize fleet management is through Data Mining analysis. This study focuses on optimizing Ojek online transportation services using the C.4.5 Algorithm method. The aim of this research is to group customers and areas based on service demand patterns, thus improving fleet distribution and reducing waiting times. The data used in this study includes location, demand, and trip frequency information. The analysis results show that the C.4.5 algorithm method effectively groups the data, providing optimal fleet distribution and enhancing service performance. This research demonstrates that applying data mining through the C.4.5 algorithm method can be an effective strategy for improving management and operational efficiency in Ojek online transportation services, offering competitive advantages in service efficiency and customer satisfaction.
The Role of Digital Technology in Sustainable Public Asset Management in Malang City Fairuzabadi, Ahmad; Afrianto , Eko; Pratama, Lionardi Ursaputra; Muhammad Yusuf Bahtiar
PANGRIPTA Vol. 8 No. 2 (2025): Pangripta Jurnal Ilmiah Kajian Perencanaan Pembangunan
Publisher : Badan Perencanaan Pembangunan Kota Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (759.163 KB) | DOI: 10.58411/eb5hta18

Abstract

Public asset management is a critical component of urban governance, yet many local governments face persistent challenges related to efficiency, transparency, and sustainability. This study investigates the role of digital technology in transforming public asset management in Malang City, Indonesia, a mid-sized urban center seeking to modernize its governance systems. A qualitative descriptive design was applied using a qualitative survey distributed to 42 stakeholders, including municipal officials, IT staff, community representatives, and digital practitioners. The open-ended responses were analyzed thematically, supplemented by document analysis of Malang’s Smart City reports and official statistics. The results show that the adoption of Geographic Information Systems (GIS), Internet of Things (IoT) monitoring, and blockchain-secured records has significantly improved asset registry accuracy, maintenance scheduling, and decision-making efficiency. Transparency and citizen participation have increased through online dashboards and reporting applications, fostering greater public trust. Furthermore, digitalization has supported sustainability objectives by reducing energy consumption, enabling climate resilience planning, and aligning asset management practices with Sustainable Development Goals. Nevertheless, the study also reveals persistent challenges, including limited funding for system upgrades, uneven digital literacy among staff and citizens, and regulatory constraints that hinder data integration across agencies. These findings contribute to the growing literature on digital governance by providing empirical evidence from a non-metropolitan Indonesian city and demonstrating how digital transformation can simultaneously enhance efficiency, transparency, and sustainability in public asset management.
Evaluasi Usabilitas dan Pengalaman Pengguna Game Puzzle Drag-and-Drop “Puzzlemetry” untuk Pembelajaran Bangun Datar Gabungan pada Siswa SMK dengan Instrumen CSUQ Fairuzabadi, Ahmad; Kadir, Shaifany Fatriana
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 2 (2025): Mei - Juli
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i2.2829

Abstract

Pembelajaran geometri, khususnya pada topik bangun datar gabungan, masih menjadi tantangan bagi siswa Sekolah Menengah Kejuruan (SMK) karena menuntut keterampilan visualisasi spasial dan analitis. Untuk mengatasi keterbatasan metode konvensional, media pembelajaran digital berbasis game semakin banyak dikembangkan. Penelitian ini bertujuan mengevaluasi aspek usability dan user experience (UX) dari Puzzlemetry, sebuah game edukasi berbasis puzzle drag-and-drop yang dirancang untuk mendukung pembelajaran geometri. Desain penelitian menggunakan pendekatan Research and Development (R&D) dengan model Agile-Extreme Programming (Agile-XP). Subjek penelitian adalah 40 siswa kelas XI SMK di Malang yang dipilih secara purposif berdasarkan kesulitan dalam memahami bangun datar gabungan serta familiaritas dengan perangkat mobile. Seluruh prosedur telah memperoleh persetujuan etik dari sekolah dan orang tua siswa. Instrumen evaluasi menggunakan Computer System Usability Questionnaire (CSUQ) versi terjemahan bahasa Indonesia yang telah diuji reliabilitas internalnya (Cronbach’s α = 0,89). CSUQ terdiri dari 18 butir yang mengukur tiga dimensi: System Usefulness (7 item), Information Quality (6 item), dan Interface Quality (5 item). Setiap item dinilai dengan skala Likert 1-7, lalu dikonversi ke persentase menggunakan rumus skor aktual/skor maksimal × 100%. Kategori interpretasi ditetapkan sebagai baik (≥70%), cukup (50–69%), dan kurang (<50%). Analisis dilakukan secara deskriptif, dilengkapi interval kepercayaan 95% untuk setiap dimensi. Hasil menunjukkan skor usability agregat 78,2% (kategori baik), dengan dimensi tertinggi pada System Usefulness (80%), diikuti Interface Quality (77,5%) dan Information Quality (77%). Temuan ini mengindikasikan bahwa Puzzlemetry memiliki usability yang baik dan berpotensi mendukung pemahaman konsep geometri, meskipun aspek visual dan kualitas informasi masih memerlukan perbaikan. 
Analisis Sentimen Ulasan Shopee di Google Play dengan TF-IDF dan Logistic Regression Kadir, Shaifany Fatriana; Fairuzabadi, Ahmad
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 2 (2025): Mei - Juli
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i2.2850

Abstract

Pertumbuhan aplikasi belanja daring mendorong meningkatnya jumlah ulasan pengguna yang tersedia di Google Play Store. Ulasan ini tidak hanya mencerminkan pengalaman pengguna, tetapi juga berperan sebagai masukan penting bagi pengembang aplikasi. Penelitian ini menganalisis sentimen ulasan aplikasi Shopee Indonesia (package com.shopee.id) periode 2024–2025 dengan menggunakan pendekatan Term Frequency–Inverse Document Frequency (TF-IDF) dan algoritma Logistic Regression. Data sebanyak 5.000 ulasan dikumpulkan melalui pustaka google-play-scraper dan dilabeli otomatis berdasarkan skor rating: 1–2 negatif, 3 netral, dan 4–5 positif. Proses preprocessing meliputi normalisasi teks, penghapusan stopword bahasa Indonesia, serta stemming. Distribusi data yang timpang (4049 positif, 796 negatif, 155 netral) ditangani dengan Random Oversampling pada data latih. Evaluasi dilakukan menggunakan stratified split 80:20 dan 5-fold cross-validation. Hasil menunjukkan Logistic Regression memberikan performa terbaik dengan akurasi 85,11% dan macro-F1 0,58 pada data uji, lebih baik dibandingkan SVM dan Naive Bayes. Confusion matrix memperlihatkan bahwa kelas positif dapat dikenali dengan baik (F1=0,92), sementara kelas netral sulit diprediksi (F1=0,14). Visualisasi WordCloud digunakan untuk menggambarkan kata dominan pada tiap kelas. Studi ini menegaskan efektivitas Logistic Regression untuk analisis ulasan aplikasi berbahasa Indonesia, meskipun tantangan besar masih terdapat pada ketidakseimbangan kelas minoritas.
Co-Authors Adya Hermawati Afida Rahman Afrianto , Eko Ahmad Afif Supianto Ahmad Afif Supianto Ahmad Farhan Ana Sopanah, Ana Andrean Yogha Saputra Bayu Nusman Choirul Anam Dinny Wahyu Widarti Dwi Anggarani Fadilah, Mega Fianita Fatriana Kadir, Shaifany Firman Nurdiyansyah Fitra Abdurrachman Bachtiar Hafif Hidayatulloh Heni Pujiastuti Herman Tolle Irawan, Ryan Avrilio Ismail Akbar Khojanah Hasan Lionardi Ursa Putra M. Yusuf Bahtiar, M. Yusuf Marpaung, Fhadillah Ain Mulyono Mulyono Ngudi Tjahjono Pawestri, Hartini Prasetyaning Pratama, Lionardi Ursaputra Saputra, Idris Ivan Survival Wahyudi, Untung Wijaya, Irsyad Maulana