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All Journal CESS (Journal of Computer Engineering, System and Science) EXPLORE Technologia: Jurnal Ilmiah International Journal of Informatics and Computation Jurnal Teknimedia: Teknologi Informasi dan Multimedia Jurnal Pengembangan Sistem Informasi dan Informatika Jurnal Teknologi Kharisma Tech EXPLORE Computing and Education Technology Journal Coreid Journal Jurnal Inovasi Teknologi Terapan JURNAL FLOBAMORATA MENGABDI International Journal of Informatics Engineering and Computing
M. Hizbul Wathan
Politeknik Manufaktur Negeri Bangka Belitung, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Mechanical Engineering Social Sciences Other

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Journal : kharisma tech

 1 
EFEKTIVITAS PENERAPAN SISTEM ABSENSI GURU BERBASIS GEOLOKASI MENGGUNAKAN METODE FEATURE DRIVEN DEVELOPMENT (FDD) DI SMP NEGERI 2 RIAU SILIP deswita, deswita; Irwan; Wathan, M Hizbul
KHARISMA Tech Vol 20 No 2 (2025): KHARISMATech Journal
Publisher : STMIK KHARISMA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55645/kharismatech.v20i2.645

Abstract

The supervision of teacher attendance plays a crucial role in ensuring the smooth implementation of the learning process. However, the manual attendance system used at SMP Negeri 2 Riau Silip often leads to recording errors, time inefficiency, and data manipulation. This study aims to implement and evaluate the effectiveness of a teacher attendance system based on geolocation using the Feature Driven Development (FDD) method. The system was developed with the Flutter framework for the mobile application and Laravel for the backend, integrated through an API and supported by a MySQL database. The main features include GPS-based attendance validation, photo-based activity verification, attendance history, and real-time monitoring by administrators. The development process followed five stages of FDD, ensuring a structured and feature-oriented approach. System testing using black box testing and User Acceptance Testing (UAT) resulted in an average feasibility score of 89.73%, categorized as highly feasible. The results indicate that the implementation of the geolocation-based attendance system effectively improves efficiency, accuracy, and transparency in managing teacher attendance at SMP Negeri 2 Riau Silip.
Design and Development of a QR Code-Based Ordering System and Mobile Cashier Application at Rumah Seduh Coffee Shop Fadhilah, Indirokan; Rindri, Yang Agita; Wathan, M. Hizbul
KHARISMA Tech Vol 20 No 2 (2025): KHARISMATech Journal
Publisher : STMIK KHARISMA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55645/kharismatech.v20i2.636

Abstract

This research was carried out with the aim of designing and developing a QR Code–based ordering system integrated with a mobile cashier application at Warung Kopi Rumah Seduh. The previously manual process created several issues, including long queues, delayed service, and frequent transaction recording errors that disrupted operational efficiency. To address these challenges, a digital system was introduced that allows customers to place orders independently by scanning a QR Code, with the orders being automatically recorded in the cashier system. The mobile cashier application supports real-time order processing, transaction management, and structured sales data storage. The system was developed using a prototyping approach, beginning with requirements analysis through field observations and user interviews. The implementation results demonstrate that this solution improves service efficiency, accelerates the ordering process, reduces input errors, and enhances the organization of sales data. Ultimately, this study is expected to provide practical contributions for MSMEs in adapting to the challenges of service digitalization.
EXPLAINABLE MACHINE LEARNING FOR PHISHING URL DETECTION USING SHAP INTERPRETATION M. Hizbul Wathan; Indra Irawan; Better Swengky; Tri Agusti Farma; Satria Agus Darma
KHARISMA Tech Vol 21 No 2 (2026): KHARISMATech Journal
Publisher : STMIK KHARISMA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55645/kharismatech.v21i2.696

Abstract

Phishing attacks delivered through malicious URLs represent an increasingly prevalent cyber threat capable of causing significant harm to users. Although machine-learning–based phishing detection has been widely explored, most existing models still operate as black boxes, making their classification decisions difficult to interpret. This study proposes an Explainable Machine Learning framework for phishing URL detection by integrating five algorithms—XGBoost, Random Forest, Gradient Boosting, Decision Tree, and K-Nearest Neighbors—augmented with SHAP (SHapley Additive Explanations) for interpretability. The dataset includes structural URL features such as character length, special symbol counts, number of subdomains, and string entropy. Model performance was evaluated using accuracy, precision, recall, F1-score, and confusion matrix to enable comparative assessment among algorithms. The results show that XGBoost achieves the best performance, obtaining 97.8% accuracy, an F1-score of 0.976, and stable predictions across all classes. Random Forest ranks second with 96.4% accuracy, followed by Gradient Boosting at 95.7%. Meanwhile, Decision Tree and KNN exhibit lower performance due to their higher sensitivity to data variation. SHAP analysis reveals that the most influential features in phishing prediction include URL length, special character frequency, entropy levels, and the number of subdomains. These findings demonstrate that integrating XAI not only enhances model transparency but also ensures that phishing detection systems remain accurate, interpretable, and accountable.
Co-Authors Ahmat Josi Ali, Hendrik Aulia, Rosaura Better Swengky Better Swengky Bradika Almandin Wisesa Cahyadi, Irsan Dede Hamdani Deswita Deswita Deswita Syahrani Efendi, Muhamad Masjun Evvin Faristasari Fadhilah, Indirokan Fadli, Sofiansyah Fadli Fatir Atthariq Zami Indra Irawan Indra Irawan Indra Irawan Irwan Irwan Irwan Ivansius Nahak Khemal Fasyah Ishaq Lesta, Lesta LINDA FUJIYANTI Md Safaet Hossain Moh. Aziz Muhammad Kalam Sabili Oktaviani, Ajeng Prayogi, M. Bagus Ramadani, Ardi Rani Laple Satria Rani Laple Satria Putra Riki Afriyansyah Riski Meliya Ningsih Satria Agus Darma Silvia Agustin Sirlus Andreanto Jasman Duli Sofiansyah Fadli Tegar Priyadi Tri Agusti Farma Wardianto, Wardianto Yang Agita Rindri Zain, M Syafrizal