Journal of Advanced Vocational Information and Communication Technology (JAVICT)
Journal of Advanced Vocational Information and Communication Technology (JAVICT) is a triannual, peer-reviewed international journal published by the Indonesian Society of Applied Science (ISAS). JAVICT provides a scholarly platform for researchers, educators, and industry practitioners to disseminate rigorous and relevant contributions in vocational and applied Information and Communication Technology (ICT). The journal welcomes original research articles and applied studies that advance the design, development, implementation, and evaluation of ICT solutions with clear relevance to vocational education, engineering practice, and industry needs. JAVICT prioritizes manuscripts demonstrating both technical rigor and practical significance, including validated prototypes, system implementations, performance evaluations, and field-based investigations. JAVICT covers key areas of vocational and applied ICT, including computer networking and communication, Internet of Things, embedded and enterprise computing, software engineering and information systems, security and cryptography, data science, intelligent systems and machine learning, database systems, parallel and distributed systems, and graphics and multimedia. Full details are available in the Aims and Scope section. JAVICT is published three times a year (January, May, and September). All submissions undergo editorial screening and peer review to ensure relevance, quality, and research integrity. Currently, JAVICT does not charge any Article Processing Charges (APCs) or submission fees. ISSN (Online): 3124-0437 DOI Prefix: https://doi.org/10.52158/javict Publisher: Indonesian Society of Applied Science (ISAS) Editor-in-Chief: Prof. M. Udin Harun Al Rasyid, Ph.D. Address: Jl. Raya ITS, Sukolilo, Surabaya 60111, Indonesia
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<![CDATA[Web-Based Monitoring and Control System for Aquaponics Using IoT and Fuzzy Logic ]]>
<![CDATA[Ranu Arga Noor Yuusufa]]>;
<![CDATA[Nirwana Haidar Hari]]>;
<![CDATA[Yudha Dwi Putra Negara]]>;
<![CDATA[Khotibul Umam]]>
<![CDATA[ Journal of Advanced Vocational Information and Communication Technology Vol. 1 No. 2 (2026) ]]>
Publisher : <![CDATA[ISAS ]]>
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DOI: 10.52158/javict.v1i2.1494
<![CDATA[Aquaponics integrates aquaculture and hydroponic cultivation to improve resource efficiency and support food security under constraints of limited land and water. Water quality is a critical determinant of aquaponics productivity; however, many small-scale systems still rely on manual and periodic monitoring, which limits timely intervention. This study proposes an Internet of Things (IoT)–enabled, web-based aquaponics monitoring and control system for catfish (Clarias gariepinus) cultivation integrated with water spinach (Ipomoea aquatica). The system acquires water quality parameters including temperature, pH, dissolved oxygen, and ammonia using multiple sensors connected to an Arduino Mega. Sensor data are transmitted in real time via an ESP communication module using the MQTT protocol through the HiveMQ broker and stored in a MongoDB database for real-time visualization and historical analysis. In addition, pump actuator control is implemented using fuzzy logic based on water temperature and ammonia concentration to regulate water circulation and provide an interpretable qualitative assessment of water quality. Experimental validation confirms reliable sensing, transmission, storage, and web-based monitoring in an aquaponics pond scenario. The end-to-end transmission delay from the microcontroller to the web application achieves an average of 0.369 s (369 ms), indicating near real-time performance suitable for continuous monitoring and control.]]>
<![CDATA[IoT and Cloud System Implementation Based on FIWARE for Smart Home Application ]]>
<![CDATA[Angga Pradipta Kurnia Putra]]>;
<![CDATA[Zaky Oktavianto Wahyu]]>;
<![CDATA[Reksa Prastama Putra]]>
<![CDATA[ Journal of Advanced Vocational Information and Communication Technology Vol. 1 No. 2 (2026) ]]>
Publisher : <![CDATA[ISAS ]]>
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DOI: 10.52158/javict.v1i2.1533
<![CDATA[Third-party smart home platforms raise significant security and privacy concerns due to their centralized hosting models. This study develops a decentralized, easily deployable smart home platform using the FIWARE IoT framework that enables users to host systems on private servers. The platform integrates FIWARE Generic Enablers (Orion, Keyrock, Wilma, IoT Agent) with custom web, mobile, and desktop applications, containerized using Docker Compose. Hardware nodes (NodeMCU ESP8266 with DHT11 sensors and relay modules) operate without a central gateway. The system successfully achieved full CRUD functionality across client applications, with automated Arduino sketch compilation and upload. However, performance testing revealed critical latency anomalies, with the Orion Context Broker exhibiting rare but severe response delays up to 10 seconds. While the platform successfully addresses privacy concerns and simplifies deployment, FIWARE's resource consumption and occasional latency spikes present optimization challenges requiring future work.]]>
<![CDATA[Virtual Lab Module Feature Development on ETHOL System for PHP Learning ]]>
<![CDATA[Sherly Maya Salsabilla]]>;
<![CDATA[Mirta Chadhirotin Nachlah]]>
<![CDATA[ Journal of Advanced Vocational Information and Communication Technology Vol. 1 No. 2 (2026) ]]>
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DOI: 10.52158/javict.v1i2.1541
<![CDATA[Information technology in education has rapidly evolved, particularly in supporting distance learning systems. However, conventional e-learning platforms often lack practical components, limiting students’ ability to develop hands-on skills. This study addresses the need for an interactive learning environment by developing a virtual laboratory focused on PHP programming. The proposed system enables students to perform practical exercises in a web-based environment, simulating real laboratory activities. The virtual lab is integrated with the existing Learning Management System through web services, specifically ETHOL (Enterprise Technology Hybrid Online Learning) at EEPIS. The implementation of this system provides flexibility for students to access learning materials and conduct experiments anytime and anywhere. The results indicate that the virtual lab enhances students’ understanding of programming concepts and supports independent learning. Load testing demonstrated that the system handles 4,638 requests within 3 minutes with an average response time of 26 ms and a throughput of 27 requests per second on minimal cloud hardware (1 GB RAM, 1 vCPU). Responsiveness testing confirmed that the website functions properly on 100% of tested devices (2 desktop and 1 mobile resolutions). Therefore, the developed virtual lab can serve as an effective complementary tool in e-learning environments.]]>
<![CDATA[Voice Command Smart Home Control on Single-board Computer Using Google Speech API and Cosine Similarity ]]>
<![CDATA[Mochammad Ilham Maulana]]>;
<![CDATA[Reksa Prastama Putra]]>;
<![CDATA[Zaky Wahyu Oktavianto]]>
<![CDATA[ Journal of Advanced Vocational Information and Communication Technology Vol. 1 No. 2 (2026) ]]>
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DOI: 10.52158/javict.v1i2.1545
<![CDATA[The development of technology today is very fast and sophisticated. One example of technological developments is the smart home. A smart home is a house or building equipped with high technology that allows various systems and devices in the home to communicate with one another. This technology is very helpful for parents and people with disabilities in activities at home. One way of controlling smart homes currently being developed is voice control. However, some smart home devices do not yet have control features using voice commands in Indonesian. This study aims to create and test a smart home device that can be controlled by voice commands using the Google Speech-to-Text Application Programming Interface (API) as a medium for capturing and converting voice commands from users into text. The results of the conversion are processed using the Cosine Similarity method to determine what commands are given and which devices the user wants to control. This process is carried out on a Single Board Computer (SBC), specifically the Raspberry Pi. The system achieves up to 100% accuracy in quiet conditions with an average response time of 1001.4 ms. However, this accuracy drops to approximately 80% in noisy environments above 65dB, indicating limitations of the Google Speech API under high noise conditions.]]>
<![CDATA[Surrogate Assisted Multi Objective Optimization of a 2.4 GHz Yagi Antenna Using Gaussian Process Regression and MOPSO ]]>
<![CDATA[Joko Prasetyo]]>;
<![CDATA[Ahmad Khairul Umam]]>;
<![CDATA[Khoironi]]>
<![CDATA[ Journal of Advanced Vocational Information and Communication Technology Vol. 1 No. 2 (2026) ]]>
Publisher : <![CDATA[ISAS ]]>
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DOI: 10.52158/javict.v1i2.1567
<![CDATA[This paper presents a surrogate‑assisted multi‑objective optimization approach for a 2.4 GHz Yagi–Uda antenna using Gaussian Process Regression (GPR) and Multi‑Objective Particle Swarm Optimization (MOPSO). The antenna performance is evaluated in terms of maximum gain and minimum Voltage Standing Wave Ratio (VSWR). Three key physical parameters—inter‑element spacing (gap), director length, and element diameter—are parametrically swept using CST Microwave Studio to generate training data. GPR models are employed as surrogate fitness estimators to approximate the nonlinear relationship between antenna geometry and performance metrics. These surrogate models are integrated into the MOPSO framework to efficiently explore the design space and obtain Pareto‑optimal solutions. The results demonstrate that the proposed method effectively identifying optimal pareto front trade‑offs between gain and VSWR, validating the effectiveness of the proposed approach.]]>
