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All Journal JURNAL SISTEM INFORMASI BISNIS Elkom: Jurnal Elektronika dan Komputer Bulletin of Electrical Engineering and Informatics Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Transformatika Scientific Journal of Informatics Register: Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Informatika Upgris Prosiding 2nd Seminar Nasional IPTEK Terapan (SENIT) 2017 Progresif: Jurnal Ilmiah Komputer Jurnal Teknologi Informasi dan Komunikasi Jurnal Sosial dan Teknologi INFORMATIKA Jurnal Pengabdian Mandiri Jurnal Teknik Informatika dan Teknologi Informasi Jurnal Manajemen Informatika & Teknologi Jurnal Riset Rumpun Seni, Desain dan Media (JURRSENDEM) Community: Jurnal Pengabdian Pada Masyarakat Journal of Technology Informatics and Engineering Seminar Nasional Teknologi dan Multidisiplin Ilmu Jurnal Indonesia : Manajemen Informatika dan Komunikasi SWAGATI: Journal of Community Service Saturnus: Jurnal Teknologi dan Sistem Informasi International Journal of Information Technology and Business Systematic Literature Review Journal Journal of Engineering, Electrical and Informatics Global Science: Journal of Information Technology and Computer Science Jurnal Publikasi Sistem Informasi dan Manajemen Bisnis Jurnal Publikasi Ilmu Komputer dan Multimedia Jurnal Publikasi Teknik Informatika
Toni Wijanarko Adi Putra
Universitas Sains Dan Teknologi Komputer
Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Nursing Public Health Social Sciences Other

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Cost-Sensitive Fraud Detection with Reliability Calibration: A Practical Pipeline with XGBoost and Focal-Proxy Reweighting Danang Danang; Toni Wijanarko Adi Putra
International Journal of Information Technology and Business Vol. 8 No. 1 (2025): November : International Journal of Information Techonology and Business
Publisher : Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/ijiteb.812025.13-24

Abstract

Fraud detection on payment transactions is an extremely imbalanced, high-stakes classification task in which deployment decisions depend not only on ranking quality but also on reliable probability estimates. We study credit card fraud detection on a standard real-transaction benchmark (284,807 transactions; 492 frauds) and target two deployment requirements: cost-sensitive thresholding under asymmetric error costs and reliability calibration so model outputs can be interpreted as stable risk scores. We benchmark logistic regression and XGBoost and propose a focal-proxy reweighting scheme for boosted trees via iterative weight updates inspired by focal loss. Probabilities are calibrated on validation using Platt scaling, temperature scaling, and isotonic-style monotone calibration; the best calibrator is selected by minimum validation Brier score. For decision-making, we choose the operating threshold that minimizes expected cost, Cost(t) = 10 · FN(t) + 1 · FP(t), on validation, then evaluate on a held-out test set. On the benchmark split (train 199,364; validation 42,721; test 42,722), the calibrated XGBoost baseline achieves AUROC 0.973, AUPRC 0.812, fraud-class F1 0.767, and expected cost 154 with very low calibration error (ECE = 1.1 × 10⁻⁴). Overall, calibration reduces ECE and improves or maintains the Brier score, while cost-aware thresholding makes the FN/FP trade-off explicit via decision curves. 
Privacy Protection and Trust in the Digital Era: A Systematic Review of Data Breach Impacts on SDG Progress Toni Wijanarko Adi Putra; Danang Danang
International Journal of Information Technology and Business Vol. 8 No. 1 (2025): November : International Journal of Information Techonology and Business
Publisher : Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/ijiteb.812025.24-34

Abstract

Objective – In the digital transformation era, the integrity of personal data has become essential for maintaining trust and ensuring the sustainability of digital services. This paper aims to systematically review how data privacy violations affect public trust and progress toward Sustainable Development Goals (SDGs), especially SDG 9 (infrastructure and innovation) and SDG 16 (strong institutions and justice). Methodology—This study adopts the Systematic Literature Review (SLR) approach based on Kitchenham’s framework. Relevant articles from 2021–2025 were retrieved from Scopus, IEEE, Springer, and ScienceDirect using a predefined search string aligned with PICOC. A total of 19,504 records were screened, and 36 high-quality studies were selected after applying inclusion/exclusion criteria and quality assessment tools (e.g., CASP, AMSTAR). Findings—The review reveals that sectors such as education, healthcare, and smart cities are increasingly adopting data protection technologies, including encryption, federated learning, differential privacy, and blockchain. However, many still face regulatory, infrastructural, and human literacy gaps. Breaches in personal data significantly reduce public trust, impair the exercise of digital rights, and pose ethical and operational risks for achieving SDGs. Limitations – The study is limited by the timeframe (2021–2025) and focuses primarily on peer-reviewed literature. Practical insights from developing countries may be underrepresented due to database indexing limitations. Contribution – This review contributes a cross-sectoral synthesis of technological and regulatory practices for data protection, identifies key challenges, and outlines a strategic roadmap for policymakers and technologists to integrate ethical data governance for sustainable digital futures.
PENGEMBANGAN SISTEM INFORMASI E-VOTING BERBASIS WEB UNTUK PEMILIHAN KETUA KARANG TARUNA SEMARANG SELATAN DENGAN PENERAPAN KEAMANAN DATA MENGGUNAKAN METODE HASHING Cahyo Arief Budiman; Toni Wijanarko Adi Putra; Budi Hartono
JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI Vol. 17 No. 2 (2026): September
Publisher : Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtikp.v17i2.1829

Abstract

The election of the South Semarang Youth Organization (Karang Taruna) Chairperson is a democratic organizational process that plays a crucial role in leadership renewal. However, conventional election methods relying on paper ballots face several challenges, such as limited member access, operational costs, the risk of counting errors (human error), and lengthy vote tabulation processes. This study aims to develop a web-based e-voting information system for the South Semarang Youth Organization Chairperson election, incorporating the SHA-256 hashing method as a security mechanism for vote data. The research employs a Research and Development (R&D) methodology using a mixed-methods approach and the Waterfall development model, comprising stages for requirements analysis, design, implementation, testing, and evaluation. The system is designed to manage user authentication, voter and candidate data, the voting process, data storage, and automated result tabulation. Applying the SHA-256 algorithm to vote data generates a hash value acting as a digital fingerprint, which preserves data integrity and detects alterations through the avalanche effect mechanism. Research findings indicate that the system enhances the efficiency and transparency of the election process. An analysis of tabulation times reveals that the manual method takes approximately 110 minutes, whereas the e-voting system requires only 2–3 minutes, achieving a time efficiency rate of 97.27%. Consequently, the developed system offers a faster, more accurate, secure, and transparent election solution while supporting the digitalization of the youth organization's electoral processes.
Rancang Bangun Sistem Edukasi Cryptocurrency Berbasis Web dengan Simulasi Trading Aloysius Rianto; Toni wijanarko adi putra; Budi Hartono
Jurnal Manajemen Informatika & Teknologi Vol. 6 No. 2 (2026): Oktober : Jurnal Manajemen Informatika & Teknologi
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/mifortekh.v6i2.1319

Abstract

A significant increase in public engagement with cryptocurrency investment opportunities has not been paralleled by an equivalent enhancement in financial literacy, thereby amplifying the likelihood of financial detriment for those entering the market. This study's primary objective is to engineer a web-based cryptocurrency educational system, augmented with a risk-free trading simulation module, employing the Prototyping development model. The architecture of this system facilitates the delivery of structured educational content on financial literacy alongside a dynamic space for practicing transactions. Live market prices are continuously retrieved through the CoinGecko API, featuring an integrated system for calculating a uniform trading fee of 0.1% for every transaction. The system's performance was rigorously tested using Black-Box Testing methodologies. Quantitative findings revealed a complete 100% success rate in terms of functionality, confirming that all six essential features perform as intended. Additionally, the average latency for market price synchronization from the API did not exceed two seconds. This development underscores the system's proven efficacy and high suitability as a safe and secure avenue for novice cryptocurrency investors to enhance their knowledge.
Optimalisasi Konten Interaktif Berbasis FiveM dengan Rockstar Editor untuk Memberikan Edukasi dan Pengembangan Keterampilan Gamer Arrivo Athaillah Maheswara; Toni Wijanarko Adi Putra; Budi Hartono
Jurnal Manajemen Informatika & Teknologi Vol. 6 No. 2 (2026): Oktober : Jurnal Manajemen Informatika & Teknologi
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/mifortekh.v6i2.1345

Abstract

The rapid advancement of digital technology has significantly increased the production of multimedia content, particularly digital videos. In addition to serving as entertainment, video has become an important medium for communication, documentation, and creative expression. Grand Theft Auto V (GTA V), through its Rockstar Editor feature, provides users with cinematic video recording and editing capabilities. However, beginner users often encounter difficulties in understanding its advanced editing features due to the lack of structured and interactive learning resources. This study aims to develop an interactive video editing tutorial integrated into the FiveM platform to assist novice users in learning Rockstar Editor more effectively. The research employed the Research and Development (R&D) method using the Multimedia Development Life Cycle (MDLC) model, which consists of six stages: concept, design, material collecting, assembly, testing, and distribution. The developed learning media was implemented using Lua, HTML, CSS, and JavaScript within the FiveM environment. System evaluation was conducted through observations, literature studies, and questionnaires distributed to beginner users. The evaluation results indicate that the developed media is easy to use, provides well-structured learning materials, enhances user engagement, and improves users' understanding of video recording and editing using Rockstar Editor. Therefore, the interactive learning media developed in this study is considered effective in supporting contextual, practical, and engaging game-based learning for beginner FiveM users.
Implementasi Algoritma Klasifikasi K-Nearest Neighbors untuk Prediksi Risiko Depresi pada Pengguna Media Sosial Nanda Natalia; Toni Wijanarko Adi Putra; Budi Hartono
Jurnal Manajemen Informatika & Teknologi Vol. 6 No. 2 (2026): Oktober : Jurnal Manajemen Informatika & Teknologi
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/mifortekh.v6i2.1351

Abstract

This study focuses on  developing  a classification model to predict the level of depression risk among social media users using machine learning techniques. This research is based on the increasing use of social media, which may have negative impacts on mental health, particularly depression, thus highlighting the importance of early detection. This study applies a quantitative approach using the K-Nearest Neighbor (KNN) algorithm as the classification method. The dataset used is secondary data obtained from Kaggle, consisting of 481 respondents, including variables related to social media usage behavior and mental health indicators. This research stages include data preprocessing, splitting the dataset into training and testing sets with an 80:20 ratio, model training, and evaluation using accuracy and F1-score metrics. The results show that  KNN algorithm is capable of classifying depression risk into several categories, with an accuracy of 38%. This indicates that the model demonstrates an initial classification capability, although its performance still needs improvement. Therefore, further development is required to enhance the model’s accuracy in supporting early detection of depression risk based on social media behavioral data
Perancangan Sistem Deteksi Wajah Real-Time Menggunakan Convolutional Neural Network pada Perangkat Komputer Desktop Virgiawan Restu Pratama; Dani Sasmoko; Toni Wijanarko Adi Putra
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 7 No. 3 (2026): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v7i3.1982

Abstract

This research aims to design and implement a real-time face detection system use a Convolutional Neural Network (CNN) on a desktop computer. The research consisted of data preprocesing, collection, model training, and performance evaluation. The dataset contained 200 facial images, which were resized to 224 ×is 224 pixels, normalized, and divided into training and testing sets. The model was developed using TensorFlow, Keras, and OpenCV, and evaluated use confusion matrix based on precision, accuracy, recall, and F1-score. The research results is that the proposed model can detect and recognize faces effectively, as demonstrated by an accuracy value of 97.22%, along with recall, precision, and F1-score values of 97%. The implementation of Batch Normalization and Dropout improved training stability and enhanced the model's generalization capability. These findings indicate that the CNN -based approach is effective for real-time face detection on desktop computer systems.
Co-Authors Achmad Solechan Agung Surono Ahmad Ashifuddin Aqham Aldho Dwi Kurniawan Alex Ristanto Pratama Aloysius Rianto Andra Matarisman Arditya Himawan Arrivo Athaillah Maheswara Arsito Ari Kuncoro Aslina Baharum Budi Hartono Budi Hartono budi hartono Budi Hartono Cahyo Arief Budiman Chandani, Chicie Chicie Chandani Danang Danang Danang, Danang Dani Sasmoko Dani Sasmoko Dendy Kurniawan Devi Astri Nawangnugraeni Dimas Rahardian Dwi Prasetyaningsih Edy Siswanto Eko Siswanto Eko Siswanto Endrahadi Rahadian Endro Farhan Afif Ilmi Febryantahanuji Febryantahanuji Fitro Nur Hakim Fitro Nur Hakim Fujiama Diapoldo Silalahi Fujiama Diapoldo Silalahi Hakim , Fitro Nur Haryo Kusumo Haryo Kusumo Iman Saufik Suasana Isaac Vital Jarot Dian Susatyono Khoirur Rozikin Kusumo, Haryo Kusworo Adi Lawrence Adi Supriyono M. Zakki Abdillah Migunani Migunani Mohamad Irkam Muhammad Walid Syahrul Churum mukhamad masrur Nanda Natalia Nuris Dwi Setiawan R Rizal Isnanto Rizal Dewo Susanto Roni Eka Setiawan Rusito Siswanto Siswanto Siswanto Siswanto Siswanto, Edy Solikhin Solikhin Sulartopo Sulartopo Ulil Asyhar Unang Achlison Victor Gayuh Utomo Virgiawan Restu Pratama Wibowo, Mars Caroline Yehezkiel Yanu Putranto Yohanes Suhari Yuli Fitrianto Zaenal Mustofa