cover
Contact Name
M. Miftach Fakhri
Contact Email
fakhri.abcollab@gmail.com
Phone
+6281343505565
Journal Mail Official
dtcs@abcollab.id
Editorial Address
Jalan Cempaka Mekar Raya No. 10 Bandung, Jawa Barat, Indonesia
Location
Kota bandung,
Jawa barat
INDONESIA
Journal of Digital Technology and Computer Science
ISSN : 30310318     EISSN : 30308127     DOI : https://doi.org/10.66053/dtcs
Digital Technology and Socio-Technical Innovation, including the design, development, implementation, and evaluation of digital solutions, platforms, applications, and infrastructures that support modern socio-technical systems, digital transformation, and technology-enabled services. Computer Systems, Software, and Networking, encompassing distributed systems, computer networks, network architectures, communication protocols, network performance, next-generation connectivity, software systems, and integrated computing environments. Artificial Intelligence, Machine Learning, and Intelligent Systems, covering intelligent systems, machine learning algorithms, deep learning, natural language processing, expert systems, knowledge-based systems, computational intelligence, and applied AI across scientific, industrial, and societal domains. Decision Support, Fuzzy, and Evolutionary Systems, including decision support systems, fuzzy logic, fuzzy control, evolutionary computing, optimization algorithms, swarm intelligence, hybrid intelligent methods, and data-driven decision models. Image, Audio, and Multimedia Processing, including computer vision, image processing, sound and speech processing, multimedia analysis, signal processing, pattern recognition, and audio-visual computing applications. Information Security and Cybersecurity, focusing on information security, system security, network security, cybersecurity governance, cryptography, privacy protection, secure software engineering, threat detection, intrusion prevention, digital forensics, and cyber risk management. Cyber Crime and Digital Investigation, including cybercrime detection and analysis, cyber law and policy in digital environments, forensic investigation, online fraud, identity theft, malicious activity analysis, and digital evidence management. Social Network and Digital Security, covering security and trust in social media and online platforms, digital identity, misinformation and disinformation detection, privacy in social networks, human factors in cybersecurity, and safe digital interaction ecosystems. Operating Systems, Computer Architecture, and Embedded Computing, including operating systems, processor and memory architecture, virtualization, system-level optimization, embedded systems, real-time computing, firmware, and performance engineering. Cloud, Edge, and Ubiquitous Computing, covering cloud platforms, fog and edge computing, distributed intelligence, service orchestration, scalable infrastructures, reliability, resource management, and pervasive computing environments. Internet of Things (IoT), Sensor Networks, and Cyber-Physical Systems, including smart devices, wireless sensor networks, industrial IoT, IoT platforms, connected environments, cyber-physical systems, and real-world deployment challenges in intelligent sensing and control. Big Data, Analytics, and Data-Driven Computing, encompassing data engineering, data mining, large-scale data processing, predictive analytics, visual analytics, business intelligence, and advanced computational methods for complex datasets. Wearable Devices and Smart Sensing Technologies, including wearable computing, body-area networks, health and activity monitoring systems, smart textiles, mobile sensing, and human-centered intelligent devices. Embedded Robotics and Microcontroller Systems, including robotic systems, embedded robotics, autonomous control, low-level hardware-software integration, microcontroller-based applications, robotic sensing, and intelligent actuation systems. Micro and Nano Technology, including microelectronics, nanoelectronics, microsystems, nanosystems, MEMS/NEMS-related applications, miniaturized intelligent devices, and sensor-oriented micro/nano technological innovations. Renewable Energy and Intelligent Energy Systems, including digital technologies for renewable energy, smart energy monitoring, intelligent control systems for energy efficiency, IoT-enabled energy systems, sustainable computing, and computational methods for energy optimization. Software Engineering and Information Systems, including software design, software quality assurance, software testing, requirements engineering, enterprise systems, information systems development, human-centered software solutions, and digital service integration. Robotics, Automation, and Autonomous Systems, covering intelligent robotics, automation systems, control engineering, autonomous agents, robotic perception, human-robot interaction, and smart manufacturing applications. Human-Computer Interaction and Digital Experience, including user interface design, user experience, usability evaluation, interactive systems, accessibility, persuasive technologies, and digital behavior in technology-mediated environments. Green Computing and Sustainable Digital Systems, including energy-efficient computing, sustainable software and hardware design, green AI, carbon-aware digital infrastructures, smart resource management, and digital technologies for environmental sustainability.
Articles 25 Documents
Web-Based Tourism Recommendation System for South Sulawesi: Design, Implementation, and Evaluation Reza Fathurrahman; Dwi Putri Nadila; Nurfahmi Hidayat; Muhammad Nur Faiz; Ahmad Khairul Shiddiq
Journal of Digital Technology and Computer Science Vol. 3 No. 1 (2025): November 2025
Publisher : Academic Bright Collaboration

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Abstract

Tourism information delivery in South Sulawesi remains constrained by the absence of a digital platform that provides comprehensive and personalized data. Previous studies generally present only basic information without recommendation features that align with user interests. This study develops a web-based application named Sering-Sering, designed to provide both tourism information and personalized recommendations according to user needs. The application was developed using the Waterfall model, a structured and sequential software engineering methodology, and its functionality was evaluated through white-box and black-box testing to ensure completeness and reliability. Results demonstrate that Sering-Sering was successfully implemented through systematic stages of planning, analysis, design, implementation, and testing. The final system is stable, user-friendly, and capable of delivering informative outputs. Black-box testing across 15 scenarios, including login, registration, destination search, profile management, and deletion of favorites and notifications, produced a 100 percent functional success rate. These findings indicate that the application effectively supports tourists in identifying suitable destinations quickly and conveniently while also contributing to regional tourism promotion. Future research is recommended to expand the system by integrating online ticket booking and artificial intelligence-based recommendation features, thereby strengthening its potential contribution to smart tourism development in South Sulawesi.
WIKAMA: A Web-Based Tourism Information System for Maros Regency Using the Waterfall Method Paula Vebrianti Kewa Payon Riantobi; Nurhalisa; Muh. Kahlil Gibran; Ahmad Khairul Shiddiq; Muhammad Nur Faiz
Journal of Digital Technology and Computer Science Vol. 3 No. 1 (2025): November 2025
Publisher : Academic Bright Collaboration

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Abstract

The Web-Based Tourism Information System of Maros Regency (WIKAMA) was developed to provide an efficient platform for promoting tourist destinations and delivering accessible visitor information. The system enhances the tourism experience by offering real-time details on attractions, facilities, and services. Development followed the Waterfall methodology, incorporating modules for destination management, gallery updates, and user interaction. Evaluation employed both functional and non-functional testing to assess performance, security, and usability. Black Box testing confirmed that all seven core functionalities operated successfully and complied fully with the specified requirements. While the system has met its initial objectives, further enhancements are recommended, including online ticketing, integration with social media for broader outreach, and optimization for improved performance. These improvements are expected to strengthen WIKAMA’s role as a digital tool for tourism promotion and regional economic development in Maros Regency.
Web Based Sales Information System Using the Waterfall Method for Cashier and Product Management Awaluddin; Muhammad Fadhil Mu’min; Riandy; Syahril Ramadhan; Muhammad Nur Faiz; Ahmad Khairul Shiddiq
Journal of Digital Technology and Computer Science Vol. 3 No. 1 (2025): November 2025
Publisher : Academic Bright Collaboration

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Abstract

This article presents the development of a web based sales information system for e commerce named Comerch using the Waterfall method. E commerce offers convenient online transactions yet imposes challenges in managing complex sales processes. The study aims to design and implement a system that supports transaction processing, product management, and an accessible and efficient platform. The Waterfall stages applied include requirements analysis, system design, coding, integration, and testing. Findings show that Waterfall enabled a structured and efficient development pipeline and smooth integration of system components. The resulting system provides core functions including product management, payment transactions, and real time reporting which improve operational efficiency and user experience. Scenario based testing confirms that the system performs as expected. Black box testing across forty six scenarios achieved one hundred percent functional validation. The study contributes a practical reference for developing sales information systems for small and medium enterprises and for practitioners seeking predictable and well documented development cycles.
Classify: Classroom Reservation Mobile Application for Students Based on Agile Development Joy Febrianto Hale; Muhammad Taufiq Alhidayah Syah; Surya Radi Ramdhani. S
Journal of Digital Technology and Computer Science Vol. 3 No. 1 (2025): November 2025
Publisher : Academic Bright Collaboration

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Abstract

Classroom management in higher education often suffers from inefficiencies and scheduling conflicts as the reservation process is still carried out manually. To address these issues, this research developed Classify, an Android-based mobile application designed to help students reserve classrooms in a structured, efficient and digital way. The development followed the agile method using the Scrum framework, which was divided into three iterative sprints, including system planning, interface design with Figma, backend integration through Firebase and implementation of the main functions such as login, class list per floor, booking system and user profile management. System modeling is done with the Unified Modeling Language (UML), including Use Case Diagram and Activity Diagram. The tests are carried out using black-box and white-box methods to ensure the reliability of the system and the correctness of the program logic. The test results show that all functions work as expected and meet user requirements. Classify is thus able to improve the efficiency of the classroom reservation process, reduce the administrative burden and contribute to the digitalization of academic services in higher education.
KNN Vs Naive Bayes: An Innovative Comparison in Predictive AI Learning With Association Data Support Devi Miftahul Jannah; Aprilianti Nirmala S
Journal of Digital Technology and Computer Science Vol. 3 No. 1 (2025): November 2025
Publisher : Academic Bright Collaboration

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Abstract

This study analyzes how Naive Bayes and K-Nearest Neighbor (KNN) predict learning outcomes based on artificial intelligence (AI). The main focus of this study is the difficulty of algorithms in handling complex learning data and the contribution of Association Rule Mining (ARM) attribute features in improving prediction accuracy. The methods applied include two classification algorithms (KNN and Naive Bayes) in an exploratory-comparative quantitative research design, as well as the application of ARM to uncover hidden patterns among variables using the apriori algorithm. Data for 368 students with prior experience in artificial intelligence technology was collected through an online survey. Although KNN outperforms in recall, the study results show that Naive Bayes has higher precision. By detecting hidden correlation patterns that cannot be identified by conventional classification methods, ARM improves classification results. The discussion emphasizes that the selection of the best algorithm depends on the application's objectives, namely whether the priority is on classification accuracy or the range of relevant results. Based on these findings, a hybrid technique combining KNN, Naive Bayes, and ARM is highly recommended for creating a more efficient and accurate prediction system to support AI-based education.

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