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bit-Tech
Published by Komunitas Dosen Indonesia
ISSN : 2622271X     EISSN : 26222728     DOI : https://doi.org/10.32877/bt
Core Subject : Science,
Computer Science & IT
The bit-Tech journal was developed with the aim of accommodating the scientific work of Lecturers and Students, both the results of scientific papers and research in the form of literature study results. It is hoped that this journal will increase the knowledge and exchange of scientific information, especially scientific papers and research that will be useful as a reference for the progress of the State together.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 114 Documents
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Search results for , issue "Vol. 8 No. 1 (2025): bit-Tech" : 114 Documents clear
Development of an Android Application for Recipe Management Using Flutter and API Sutono, Eko; Muiz, Adam; Pratama, Muhammad Hafiz
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2890

Abstract

The advancement of digital technology encourages micro, small, and medium enterprises (MSMEs) to adapt their operational systems, including food recipe management. Many culinary businesses still rely on manual methods, which are prone to data loss, ingredient inconsistency, and inefficiencies. This condition often leads to increased operational costs, food waste, and inconsistency in product quality, which ultimately affects customer satisfaction and business sustainability. Digital solutions, especially those that support real-time recipe standardization, have the potential to streamline operations, minimize errors, and improve production consistency. This study aims to design and develop an Android-based food recipe management application using Flutter and REST API to support the digital transformation of MSMEs in the culinary sector. The Research and Development (R&D) approach with a prototyping model was applied, involving iterative stages: literature review, needs analysis, interface design using Figma, implementation using Flutter and REST API, and Black Box Testing involving real users for functional evaluation. The results show that all core features login, recipe search, categorization, and recipe data management (add, edit, delete) functioned properly as intended. User feedback indicated increased operational efficiency, reduced manual effort, and improved consistency in recipe handling, particularly in onboarding new staff and ensuring product uniformity. In conclusion, the developed application contributes practically to improving recipe management efficiency and supporting the digital transformation of MSMEs. This system also lays the groundwork for future development of AI-powered features, automatic nutrition analysis, and cross-platform expansion to iOS and web.
Design and Development of a Counseling Service System Using Extreme Programming Methodology Nobrian, Ikhsan; Nurlaili, Afina Lina; Aditiawan, Firza Prima
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2928

Abstract

This study addresses the inefficiency and error-prone nature of manual counseling and student violation point recording processes in schools, which often result in delays and inaccuracies. To overcome these challenges, we propose the development of a digital guidance and counseling service system designed to improve data management and enhance service accessibility for school administrators and counselors. The innovation lies in the creation of an integrated, browser-accessible application built using the MERN (MongoDB, Express.js, React, Node.js) stack, which ensures robust functionality and scalability. By applying modern development and testing methodologies, the system is designed to be both reliable and user-friendly. The core objective of this system is to streamline processes such as counseling appointment scheduling, alumni tracking, certificate submission, and student behavior reporting. It was developed using the Extreme Programming (XP) methodology, which encourages flexibility and iterative planning through close collaboration with end users. White Box Testing techniques, including cyclomatic complexity analysis and independent path testing, were employed to validate the system's internal logic. The system’s usability was assessed using the System Usability Scale (SUS), achieving an excellent score of 93.25, indicating high user satisfaction. Furthermore, the Lighthouse performance test yielded a perfect score of 100, confirming the system's high responsiveness. These results demonstrate that the developed system significantly enhances the efficiency, accuracy, and accessibility of guidance services, reduces administrative burdens, and enables better monitoring of student development, making it ideal for deployment in real-world school environments.
Development of Digital Information Systems for Operational Efficiency of Savings and Loan Cooperatives Saputra, Heru; Stephane, Ilfa; Putri, Nency Extise; Edison, Elisa Daniati; Yanto, Gusrino
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2931

Abstract

Savings and loan cooperatives are essential for advancing financial inclusion, especially in rural communities. However, many cooperatives still rely on manual or semi digital systems such as spreadsheets to manage member data and financial transactions. This condition results in low efficiency, delayed reporting, limited transparency, and frequent recording errors. This study aims to design and implement a web based cooperative information system to address operational inefficiencies at Korong Gadang Cooperative in West Sumatra, Indonesia, which serves over 120 active members. The system was developed using the Rapid Application Development (RAD) method, which emphasizes iterative prototyping and user involvement to accelerate development. The process consisted of three stages: requirements planning, system design and construction, and implementation. Modules include member management, savings and loan transactions, financial reporting, and an interactive dashboard. Black Box Testing was used to validate functionality, and user feedback was collected from 12 cooperative staff through questionnaires. The results show significant improvements in performance. Report preparation time decreased from 3–5 days to just 1 day. The system also enhanced data accuracy and transparency, enabling members and staff to access transaction information in real time. In conclusion, the web based cooperative information system developed with the RAD method has proven effective in improving efficiency and accountability. The system can be adopted by similar small-scale cooperatives with basic digital infrastructure. Future development may include mobile access, integration with payment systems, and analytical features to support data driven decisions.
Optimizing Book Genre Classification through AI on a Web Platform Dermawan, Fariz; Latifah, Noor
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.3001

Abstract

In the rapidly evolving digital era, the exponential growth of online book collections poses challenges in efficiently classifying literature according to genre. Manual classification methods are often time-consuming, subjective, and inconsistent, necessitating the adoption of advanced, automated approaches. This study aims to develop and implement an Artificial Intelligence (AI)-based genre classification system integrated into a web platform to enhance the accuracy, efficiency, and user experience in book discovery. Leveraging Machine Learning (ML) algorithms—particularly Support Vector Machine (SVM), Naïve Bayes, Decision Tree, Random Forest, and Deep Learning—alongside Natural Language Processing (NLP) techniques such as tokenization, stemming, and TF-IDF, the system analyzes book descriptions and synopses to determine the most appropriate genre. The research follows a qualitative and literature study approach, utilizing a dataset sourced from Kaggle, with preprocessing steps to remove noise and convert text into numerical representations. Experimental results demonstrate that the SVM model achieved the highest accuracy, precision, recall, and F1-score compared to other tested algorithms, effectively handling high-dimensional and non-linear data. The developed web application features an interactive dashboard, real-time classification, and a hybrid recommendation system. This work confirms the feasibility and advantages of AI-driven genre classification for large-scale digital libraries and online bookstores. While limitations such as data imbalance and overlapping genre semantics remain, the findings provide a strong foundation for future research employing larger, more diverse datasets and advanced deep learning architectures to further improve classification performance.

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