Al'Adzkiya International of Computer Science and Information Technology Journal
Computer Science, Computer Engineering and Informatics: Data Science Artificial Intelligence, Machine Learning, Neural Network, Computer Architecture, Parallel and Distributed Computer, Pervasive Computing, Computer Network, Embedded System, Human—Computer Interaction, Virtual/Augmented Reality, Computer Security, Software Engineering (Software: Lifecycle, Management, Engineering Process, Engineering Tools and Methods), Programming (Programming Methodology and Paradigm), Data Engineering (Data and Knowledge level Modelling, Information Management (DB) practices, Knowledge Based Management System, Knowledge Discovery in Data), Network Traffic Modelling, Performance Modelling, Dependable Computing, High Performance Computing, Computer Security, , Networking Technology, Optical Communication Technology, Next Generation Media, Robotic Instrumentation, Information Search Engine, Multimedia Security, Computer Vision, Distributed Computing System, Mobile Processing, Next Network Generation, Computer Network Security, Natural Language Processing, Cognitive Systems. Management Informatics, Information System and developmental economics : Human-Machine Interface, Stochastic Systems, Information Theory, Intelligent Systems, IT Governance, Smart City, e-Learning, Business Intelligence, Information Retrieval, Business Process, Financial Technology (Fintech). Telecommunication and Information Technology: Modulation and Signal Processing for Telecommunication, Information Theory and Coding, Antenna and Wave Propagation, Wireless and Mobile Communications, Radio Communication, Communication Electronics and Microwave, Radar Imaging, Distributed Platform, Communication Network and Systems, Telematics Services and Security Network. Instrumentation and Mathematics: Optimal, Robust and Adaptive Controls, Non Linear and Stochastic Controls, Modelling and Identification, Robotics, Image Based Control, Hybrid and Switching Control, Process Optimization and Scheduling, Control and Intelligent Systems, Artificial Intelligent and Expert System, Fuzzy Logic and Neural Network, Complex Adaptive Systems.
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<![CDATA[IoT-Based Smart Class System ]]>
<![CDATA[Ramadhani, Fanny]]>;
<![CDATA[Satria, Andy]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 6, No 2 (2025) ]]>
Publisher : <![CDATA[Al'Adzkiya ]]>
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DOI: 10.55311/aiocsit.v6i2.352
<![CDATA[The rapid development of Internet of Things (IoT) technology has significantly transformed various sectors, including education. This study proposes an IoT-Based Smart Class System designed to enhance the effectiveness, efficiency, and interactivity of the learning environment. The proposed system integrates IoT devices such as sensors, microcontrollers, and networked actuators to monitor and control classroom conditions, including lighting, temperature, occupancy, and learning equipment usage in real time. Data collected from these devices are transmitted to a centralized platform for processing, visualization, and decision support. The system enables automated classroom management, improves energy efficiency, and supports data-driven decision-making for educators and administrators. Experimental results and system evaluation indicate that the implementation of the IoT-based smart classroom improves learning comfort, optimizes resource utilization, and provides a scalable solution for modern educational environments. The findings demonstrate that IoT technology has strong potential to support smart education initiatives and the development of intelligent learning spaces.]]>
<![CDATA[Application of Data Mining in Determining the Performance of Family Planning Field Officers Using the C4.5 Algorithm ]]>
<![CDATA[Sulaiman, Oris Krianto]]>;
<![CDATA[Siambaton, Muhammad Zulfan Syuri]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 6, No 2 (2025) ]]>
Publisher : <![CDATA[Al'Adzkiya ]]>
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DOI: 10.55311/aiocsit.v6i2.353
<![CDATA[The performance of Family Planning Field Officers plays a crucial role in the success of family planning programs. Accurate and objective performance evaluation is essential to support effective decision-making and policy formulation. This study applies data mining techniques to determine the performance of Family Planning Field Officers using the C4.5 decision tree algorithm. The dataset used in this research consists of officer performance indicators, including service coverage, counseling activities, reporting accuracy, and community participation. The C4.5 algorithm is employed to classify officer performance into predefined categories based on these attributes. The resulting decision tree provides interpretable classification rules that can support managerial decision-making. Experimental results show that the proposed model achieves satisfactory classification accuracy and demonstrates the effectiveness of the C4.5 algorithm in extracting meaningful patterns from performance data. This study highlights the potential of data mining approaches to enhance performance evaluation systems in public service institutions, particularly in the field of family planning management.]]>
<![CDATA[Comparative Analysis of Radix Sort, Quick Sort, and Bubble Sort Algorithms in Data Sorting Based on Array Size and Time ]]>
<![CDATA[Fadhillah, Kurnia Wati]]>;
<![CDATA[Ulga, Nandy Thaher]]>;
<![CDATA[Oktaviansyah, Raffi Ramadhan]]>;
<![CDATA[Sulistia, Farah]]>;
<![CDATA[Amanda, Jeni]]>;
<![CDATA[Jayadi, Akhmad]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 6, No 2 (2025) ]]>
Publisher : <![CDATA[Al'Adzkiya ]]>
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DOI: 10.55311/aiocsit.v6i2.354
<![CDATA[An algorithm is a series of logical actions used to solve important problems in contemporary programming and data processing. The purpose of this study is to compare the time efficiency of three sorting algorithms: Bubble Sort, Radix Sort, and Quick Sort. All algorithms are used on small (10-100 elements), medium (1,000-10,000 elements), and large (more than 100,000 elements) arrays, with execution time using Java. The results show that Radix Sort and Quick Sort are generally more efficient and scalable than Bubble Sort, especially for large arrays and random or semi-sorted data. Radix Sort excels on small and medium arrays under various conditions, while Quick Sort excels on large arrays in the average and nearly sorted cases. Although Bubble Sort can be the fastest in the best case for large arrays, its performance drops drastically in the average and nearly sorted cases. In conclusion, the selection of the best sorting algorithm depends heavily on the type of input data, such as its size and the degree of initial sorting.]]>
<![CDATA[Development of an Android-Based Smart Health Monitoring Device for Heartbeat Detection ]]>
<![CDATA[Zulherry, Andi]]>;
<![CDATA[Gunawan, Muhammad]]>;
<![CDATA[Sari, Indah Purnama]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 6, No 2 (2025) ]]>
Publisher : <![CDATA[Al'Adzkiya ]]>
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DOI: 10.55311/aiocsit.v6i2.355
<![CDATA[This research presents the development of a smart health monitoring system designed to detect and monitor heartbeat patterns using Android-based technology. The increasing prevalence of cardiovascular diseases necessitates accessible and user-friendly monitoring solutions for early detection and continuous health assessment. This study aims to design and implement a portable heartbeat detection device integrated with an Android application, enabling real-time monitoring and data analysis. The system utilizes pulse sensor technology to capture heartbeat signals, which are then processed by a microcontroller and transmitted wirelessly to an Android smartphone via Bluetooth connectivity. The developed application features an intuitive user interface that displays heart rate measurements, stores historical data, and provides alert notifications when abnormal patterns are detected. System testing was conducted to evaluate accuracy, reliability, and user experience across various conditions. Results demonstrate that the device achieves accurate heartbeat detection with minimal deviation from standard medical equipment, offering a practical and cost-effective solution for personal health monitoring. This research contributes to the advancement of mobile health (mHealth) technology, providing individuals with greater autonomy in managing their cardiovascular health while facilitating early intervention opportunities. The system's portability, affordability, and ease of use make it particularly suitable for home-based health monitoring and remote patient care applications.]]>
<![CDATA[Development of A Smart Monitoring System for IoT – Based Tide Observation ]]>
<![CDATA[Sari, Indah Purnama]]>;
<![CDATA[Zulherry, Andi]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 6, No 2 (2025) ]]>
Publisher : <![CDATA[Al'Adzkiya ]]>
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DOI: 10.55311/aiocsit.v6i2.351
<![CDATA[This research presents the development of a smart monitoring system for real-time tide observation using Internet of Things (IoT) technology. The system is designed to monitor sea level fluctuations continuously and transmit data wirelessly to a cloud-based platform for remote access and analysis. The hardware consists of ultrasonic sensors for water level measurement, a microcontroller for data processing, and wireless communication modules for data transmission. The collected data can be accessed through a web-based dashboard or mobile application, enabling users to monitor tidal patterns from anywhere at any time. The system also incorporates alert notifications when water levels reach predetermined thresholds, providing early warning capabilities for coastal communities. Testing results demonstrate that the system can accurately measure tidal changes with minimal error and successfully transmit data in real-time. This IoT-based tide monitoring system offers a cost-effective and efficient solution for oceanographic observation, coastal management, and disaster mitigation applications. The implementation of this technology contributes to improved maritime safety, fishing activities planning, and environmental monitoring in coastal areas.]]>
