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
Articles
15 Documents
<![CDATA[Implementation of a Kalman Filter to Improve RSSI-Based Trilateration Accuracy Using the LoRa RFM95W Module ]]>
<![CDATA[Muhammad Rayhan Firmansyah Firmansyah]]>;
<![CDATA[Afif Zuhri Arfianto]]>;
<![CDATA[Dimas Pristovani Riananda]]>;
<![CDATA[Noorman Rinanto]]>;
<![CDATA[Muhammad Khoirul Hasin]]>;
<![CDATA[Mustika Kurnia Mayangsari]]>
<![CDATA[ Journal of Advanced Vocational Information and Communication Technology Vol. 1 No. 3 (2026) ]]>
Publisher : <![CDATA[ISAS ]]>
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DOI: 10.52158/javict.v1i3.1618
<![CDATA[Internet of Things (IoT)-based positioning has become increasingly important for monitoring and navigation applications. This study proposes a LoRa-based positioning system using Received Signal Strength Indicator (RSSI) measurements filtered by a Kalman Filter. The filtered RSSI values are converted into distance using the Log-Distance Path Loss model, while the target position is estimated through trilateration. Positioning accuracy is evaluated by comparing the estimated coordinates with GPS coordinates obtained from a u-blox NEO-6M module using the Haversine distance. Experimental results show that the Kalman Filter improves RSSI stability and reduces distance fluctuations, leading to more consistent position estimates. However, the positioning accuracy remains lower than GPS, particularly in dynamic environments. Despite this limitation, the proposed system demonstrates the potential of LoRa as a low-power, long-range positioning solution. Future work will focus on adaptive filtering methods to further improve positioning accuracy.]]>
<![CDATA[Comparative Evaluation of String-Similarity Algorithms for Keyword Classification in Mobile Library OCR Systems ]]>
<![CDATA[Damar Galih AJi Pradana]]>;
<![CDATA[Sritrusta Sukaridhoto]]>;
<![CDATA[Nirwana Haidar Hari]]>
<![CDATA[ Journal of Advanced Vocational Information and Communication Technology Vol. 1 No. 3 (2026) ]]>
Publisher : <![CDATA[ISAS ]]>
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DOI: 10.52158/javict.v1i3.1653
<![CDATA[Automated keyword classification is a critical step in OCR-based library metadata systems, where OCR-extracted synopsis terms must ultimately be mapped to standardized subject keywords despite character-level recognition noise. While prior mobile OCR pipelines for library metadata extraction have adopted Levenshtein-distance-based fuzzy matching for this task, no systematic comparison exists to justify this choice against alternative string-similarity algorithms. This study isolates the keyword-classification sub-task and empirically compares three algorithms — Levenshtein-based similarity ratio, Jaro-Winkler similarity, and TF-IDF with cosine similarity — using noisy keyword-level queries as a controlled proxy for OCR-corrupted terms, under simulated OCR-noise conditions (clean, light, and heavy character-level corruption). Evaluation uses a curated 20-keyword library subject database and 900 test queries per algorithm across five random seeds. Jaro-Winkler achieves the highest overall classification accuracy (97.8%) and the fastest average matching time (22.68 microseconds per query), compared with Levenshtein-based matching (96.4% accuracy, 34.45 microseconds) and TF-IDF with cosine similarity (74.2% accuracy, 581.01 microseconds). A paired t-test across seeds confirmed that Jaro-Winkler's accuracy advantage over TF-IDF was statistically significant, while its advantage over Levenshtein was not and instead rests on its markedly lower and more stable matching latency. The gap against TF-IDF widened sharply under heavy noise (95.3% vs. 34.0% accuracy), showing that TF-IDF-based matching, despite its popularity for document-level text similarity, is poorly suited to short-keyword matching under character-level noise. These findings, based on a 20-keyword benchmark, offer preliminary algorithm-selection guidance for developers of OCR-based metadata classification pipelines, pending validation on larger, real-world OCR-noise data.]]>
<![CDATA[Location Validation and Server Time Synchronization for iOS-Based Attendance to Mitigate ASN Fraud in Lamongan ]]>
<![CDATA[Pelangi Kartika Chandra Kirana]]>;
<![CDATA[Mohammad Robihul Mufid]]>;
<![CDATA[Agung Teguh Setyadi]]>;
<![CDATA[Saniyatul Mawaddah]]>
<![CDATA[ Journal of Advanced Vocational Information and Communication Technology Vol. 1 No. 3 (2026) ]]>
Publisher : <![CDATA[ISAS ]]>
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DOI: 10.52158/javict.v1i3.1687
<![CDATA[The rapid advancement of information technology has driven government institutions to adopt digital attendance systems to improve the effectiveness of attendance management for Civil Servants (ASN). The Lamongan Regency Government has implemented an Android-based attendance application, but no equivalent service is available for iOS users, creating unequal access to digital attendance services among employees who use different devices. This study designs and implements an iOS-based attendance application equipped with geofencing-based location validation and server time synchronization to improve attendance-data accuracy and reduce the risk of fraud such as location or time manipulation. The application was developed using the Flutter framework and integrated with a Laravel REST API and a MySQL database for authentication, data storage, and real-time communication. Testing results show that the application successfully performs authentication, location validation, server time synchronization, and check-in/check-out processes according to the defined rules. Black-box testing confirmed that all functions operated as expected, geofencing testing verified that attendance could only be recorded within the designated work area, and GPS-spoofing testing showed that spoofed locations outside the designated radius were rejected, while spoofed coordinates placed inside the radius were accepted, indicating that the current geofencing mechanism validates reported coordinates rather than detecting spoofing itself. A System Usability Scale (SUS) evaluation yielded a score of 77.02 (Good), indicating that the application is easy to use. These results demonstrate that the proposed application supports more accurate, secure, and consistent attendance recording for Civil Servants.]]>
<![CDATA[IoT-Based Greenhouse Monitoring and Control System Using NodeMCU ESP8266 and the EMQX Platform ]]>
<![CDATA[Muhammad Yafi Rifdah Zayyan]]>;
<![CDATA[Ahmad Syauqi Ahsan]]>;
<![CDATA[Grezio Arifiyan Primajaya]]>;
<![CDATA[Nur Rosyid Mubtadai]]>
<![CDATA[ Journal of Advanced Vocational Information and Communication Technology Vol. 1 No. 3 (2026) ]]>
Publisher : <![CDATA[ISAS ]]>
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DOI: 10.52158/javict.v1i3.1695
<![CDATA[The advancement of Internet of Things (IoT) technology has enabled the automation of greenhouse management to improve agricultural productivity. However, conventional greenhouse systems in Indonesia still rely on manual monitoring, making it difficult to detect changes in environmental conditions promptly. This study develops an IoT-based greenhouse monitoring and automatic control system using a NodeMCU ESP8266 integrated with EMQX Cloud for secure and reliable MQTT communication. The prototype consists of irrigation, plant-monitoring, and climate-control zones. Environmental data from DHT22, YL-69, and BH1750 sensors are transmitted to a Node.js (Express.js) backend, stored in a Supabase PostgreSQL database, and displayed on a real-time Next.js dashboard using Socket.IO. Automatic control of irrigation and cooling systems is implemented through threshold and hysteresis logic. System evaluation included one week of laboratory testing and one month of field testing. The results show that the system successfully provides real-time environmental monitoring, stable automatic control, instant dashboard updates, and reliable device status monitoring, demonstrating its effectiveness as a smart greenhouse management solution.]]>
<![CDATA[Development of a Water Tank Monitoring and Pump Control System Using ESP32 and the ThingsBoard Platform with Telegram Notifications at PDAM Kota Surabaya ]]>
<![CDATA[Selma Humayra]]>;
<![CDATA[Saniyatul Mawwadah]]>;
<![CDATA[Much Chafid]]>
<![CDATA[ Journal of Advanced Vocational Information and Communication Technology Vol. 1 No. 3 (2026) ]]>
Publisher : <![CDATA[ISAS ]]>
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DOI: 10.52158/javict.v1i3.1703
<![CDATA[Conventional water tank monitoring at PDAM Surya Sembada Kota Surabaya causes delayed information and risks of overflow or underflow. This study develops an IoT-based monitoring and automatic pump control system utilizing an ESP32 microcontroller, an HC-SR04 ultrasonic sensor, the ThingsBoard platform via MQTT, and Telegram notifications. A single ultrasonic sensor simultaneously derives water level, cylindrical volume, and flow rate (Q = ΔV/Δt), eliminating physical flowmeters. Pump control is automated using two-threshold hysteresis logic. Experimental results demonstrate a water level measurement accuracy of 98.63% (MAE = 0.14 cm, R² = 0.9998). The derived flow rate was empirically validated against manual measurements, achieving 99.26% accuracy with an error of only 0.06 L/min. Telemetry latency averaged 0.53 seconds on ThingsBoard, while Telegram early warning alerts were delivered within 2.38 seconds. Furthermore, a three-layer security architecture successfully thwarted unauthorized access scenarios, and expert validation confirmed a 92.0% feasibility rate (Highly Feasible). Thus, the proposed system provides an accurate, robust, and cost-effective solution for municipal water distribution facilities.]]>
