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All Journal Jurnal Informasi dan Teknologi Journal of Computer Networks, Architecture and High Performance Computing Informanika Jurnal Pengabdian Masyarakat (ABDIRA) Jurnal Minfo Polgan (JMP) Dedikasi: Jurnal Pengabdian Kepada Masyarakat Jurnal Informatika dan Komputer (JIK) Jurnal Sistem Informasi Mahakarya (JSIM) Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer ALKHIDMAH: Jurnal Pengabdian dan Kemitraan Masyarakat
Defi Pujianto
Universitas Mahakarya Asia
Religion Aerospace Engineering Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Nursing Social Sciences Other

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RANCANG BANGUN APLIKASI DESA BERBASIS ANDROID MENGGUNAKAN ANDROID STUDIO PADA DESA KARTA MULYA KECAMATAN MADANG SUKU I, OKU TIMUR Sarkowi; Sri Hartati; Defi Pujianto
JIK : Jurnal Informatika dan Komputer Vol 17 No 1 (2026): Jurnal Informatika dan Komputer (JIK)
Publisher : Universitas Mahakarya Asia

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Abstract

Desa Karta Mulya merupakan salah satu desa yang berada di Kecamatan Madang Suku I Kabupaten OKU Timur. Sebagai unit pemerintahan, desa merupakan salah satu unit pemerintahan yang memiliki peran penting dalam pembangunan daerah. Namun, terdapat masalah yang ditemukan di Desa Karta Mulya yaitu tidak adanya aplikasi desa yang memudahkan masyarakat mengakses informasi dan masih terbatasnya akses masyarakat untuk menyampaikan keluhan atau pengaduan terkait dengan pelayanan yang diberikan  oleh pemerintah desa., OKU Timur.       Oleh karna itu dirancanglah sebuah aplikasi desa berbasis android menggunakan android studio pada Desa Karta Mulya, Kecamatan Madang Suku I Untuk memperoleh data-data yang diperlukan dalam aplikasi ini penulis melakukan penelitian terlebih dahulu dengan cara menggunakan metode interview, metode referensi dan metode observasi. Aplikasi menyediakan informasi terkait desa dan fitur pengaduan.  
Performance Analysis of an Offline Text Detection System Based on Edge AI A Case Study of DokuScan Pro Defi Pujianto; Kadarsih Kadarsih; Sri Hartati
Journal of Computer Networks, Architecture and High Performance Computing Vol. 8 No. 1 (2026): Articles Research Januari 2026
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v8i1.7854

Abstract

The growing use of mobile document scanning applications has increased the demand for text detection systems that can operate reliably in offline and on-device environments. Although Edge AI enables local inference without network dependency, system-level empirical evidence regarding its performance under real-world mobile usage conditions remains limited. This study presents a system-level evaluation of an offline Edge AI–based text detection system for mobile document scanning, using DokuScan Pro as a case study. The evaluation was conducted on 40 document images captured under varying lighting conditions, capture angles, and background characteristics. System performance was assessed using precision, recall, F1-score, and inference time to characterize on-device behavior rather than algorithmic novelty. Experimental results show that the system achieved a precision of 1.00, a recall of 0.975, and an F1-score of approximately 0.98, with an average inference time of 63.8 ms per image during fully offline execution on mobile devices. These results indicate stable system-level performance under real-world document scanning conditions with controlled computational overhead. This study provides empirical system-level insights into the feasibility and practical limitations of deploying Edge AI–based text detection in offline mobile document scanning applications, thereby complementing existing model-centric research with evidence from real-world, on-device evaluation.
Perbandingan Kinerja Isolation Forest Dan Local Outlier Factor (LOF) Dalam Deteksi Anomali Transaksi Digital Sri Hartati; Defi Pujianto; Kadarsih
BETRIK Vol. 17 No. 01 (2026): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/5w76ab74

Abstract

The rapid growth of digital transactions has increased the risk of anomalous activities such as fraud, particularly in highly imbalanced datasets where fraudulent transactions are significantly fewer than normal transactions. This imbalance presents a major challenge in anomaly detection, as models tend to be biased toward the majority class. This study aims to compare the performance of Isolation Forest and Local Outlier Factor (LOF) algorithms in detecting anomalies in digital transaction data.The research adopts an experimental approach using the Credit Card Fraud Detection dataset, which consists of 284,807 transactions, including 492 fraudulent cases. Data preprocessing involves feature normalization using StandardScaler, followed by a stratified train-test split with a ratio of 70:30. Model evaluation is conducted using confusion matrix, precision, recall, and F1-score metrics.The results show that Isolation Forest outperforms LOF. Isolation Forest successfully detects 37 out of 148 fraudulent transactions with a precision of 0.2824, recall of 0.25, and F1-score of 0.2652. In contrast, LOF detects only 2 fraudulent transactions, with a precision of 0.0137, recall of 0.0135, and F1-score of 0.0136. These findings indicate that isolation-based approaches are more effective and robust than density-based methods in handling highly imbalanced datasets.
Co-Authors Abdulloh Fakih Alfiana Amanda Rahayu Astuti Andika Saputra Ari Sulfani Bahru Wandino Budi Kurniawan Budi Kurniawan Dian Meilantika Dian Sri Agustina Didik Arifin Dwi Martha, Andre Dwi Permana Sari Haris Saputro Heru Jun Samudra Indrapraja, Rachmadi Judijanto, Loso Kadar sih Kadarsih Kadarsih Kadarsih Kadarsih Kadarsih, Kadarsih Mahrizal Mahrizal Mita Agustina Mudinillah, Adam Muhammad Romzi Nilam Permata Ocha Rosalina Putri Wahyu Kirani Resta Dwi Duta Taruna Dika Rusidi Rusidi Safaruddin Safaruddin Salamudin salamudin salamudin Sarkowi Satria Novari sih, Kadar sri hartati Suryanto Suryanto Wisnumurti Yohana Fransisca Dessy Kristianti