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INOVTEK Polbeng - Seri Informatika
Published by Politeknik Negeri Bengkalis
ISSN : 25279866     EISSN : -     DOI : https://doi.org/10.35314
Core Subject : Science,
Computer Science & IT
The Journal of Innovation and Technology (INOVTEK Polbeng—Seri Informatika) is a distinguished publication hosted by the State Polytechnic of Bengkalis. Dedicated to advancing the field of informatics, this scientific research journal serves as a vital platform for academics, researchers, and practitioners to disseminate their insightful findings and theoretical developments. Scope and Focus: INOVTEK Polbeng - Seri Informatika focuses on a broad spectrum of topics within informatics, including but not limited to Web and Mobile Computing, Image Processing, Machine Learning, Artificial Intelligence (AI), Intelligent Systems, Information Systems, Databases, Decision Support Systems (DSS), IT Project Management, Geographic Information Systems, Information Technology, Computer Networks and Security, and Wireless Sensor Networks. By covering such a wide range of subjects, the journal ensures its relevance to a diverse readership interested in both the practical and theoretical aspects of informatics.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 66 Documents
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Search results for , issue "Vol. 10 No. 3 (2025): November" : 66 Documents clear
An Indonesian Chatbot for Disease Diagnosis Using Retrieval-Augmented Generation Muhammad Adrinta Abdurrazzaq; Edwin Lesmana Tjiong; Aulia Fasya; Michelle Hiu; Joses Tanuwidjaya
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/9nnkn955

Abstract

The rapid advancement of Large Language Models (LLMs) has enabled their use in medical information systems, although challenges such as hallucinations, domain mismatches, and the lack of a verified knowledge base remain significant, particularly in low-source languages ​​like Indonesian. This study introduces an Indonesian-language medical chatbot based on the open-source GPT-OSS-20B model enhanced through a Retrieval-Augmented Generation (RAG) pipeline. The system combines semantic retrieval using jina-embeddings-v3, lexical re-ranking with the BM25 algorithm, and a lightweight Logistic Regression-based domain filter as an initial filter to prevent out-of-domain LLM usage. Evaluation using Indonesian medical articles and annotated patient-doctor conversations shows that the domain filter works well on synthetic data but results in misclassification of natural queries. A hybrid weighted reranker (FAISS L2 + BM25) performed the best with a Top-30 accuracy of 0.699. Black-box testing indicates that the system flow functions as designed, although the response quality has not been validated by clinical experts. These findings suggest that RAG-based open-source LLMs can improve access to Indonesian-language medical information, but still have important limitations such as the lack of clinical validation, potential errors in scraped data, and suboptimal robustness of domain filters.
Early Warning and Real-Time Ship Tracking using AIS Data and Smartphone GPS Supria, Supria; Wahyat, Wahyat; Ryci Rahmatil Fiska, Ryci Rahmatil Fiska
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/t62fpe35

Abstract

The high risk of maritime accidents in congested waters such as the Malacca Strait requires an affordable safety system specifically for small fishing vessels. This research proposes and evaluates a mobile-based early warning framework that integrates shore-based AIS data with fishermen’s smartphone GPS. The system was tested under 3 operational scenarios using 4G cellular networks over a coastal area of Bengkalis, involving 60 collision simulation events and 180 API requests. Performance evaluation shows an average system latency of 2.3 seconds with a maximum latency of 4.8 seconds. The early warning mechanism successfully detected dangerous proximity (≤50 meters) with an accuracy of 93.3% and an error rate of 6.7%. Position logging via JSON POST achieved a success rate of 96.1% during continuous operation for 2 hours. Although this study demonstrates improved situational awareness and reliable last-known position recording, the system currently uses distance-based detection and does not yet implement CPA/TCPA prediction, which remains future work. The framework contributes as a low-cost monitoring and early warning solution with potential support for SAR operations through reliable historical position data.
Residual-Gated Attention U-Net with Channel Recalibration for Polyp Segmentation in Colonoscopy Images Tanuwijaya, William; Yohannes
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/4qmfa987

Abstract

This study proposed a modification to the Attention U-Net architecture by integrating a Residual-Gated mechanism and Squeeze-and-Excitation (SE) Block-based channel recalibration within the Attention Gate to enhance feature selectivity in polyp segmentation. This integration reinforces both spatial and channel attention, enabling the model to better highlight polyp regions while suppressing irrelevant background features. Experiments were conducted on three colonoscopy datasets, CVC-ClinicDB, CVC-ColonDB, and CVC-300, using IoU and DSC metrics. Compared to the Attention U-Net baseline, the proposed model achieves noticeable improvements, with performance gains of mIoU 0.0043 and mDSC 0.0094 on CVC-ClinicDB, mIoU 0.0012 on CVC-ColonDB, and a larger margin of mIoU 0.0224 and mDSC 0.0127 on CVC-300. The best results were obtained on CVC-ClinicDB (mIoU 0.8889, mDSC 0.9412). Although the absolute scores on CVC-ClinicDB and CVC-ColonDB are lower than those reported in several recent studies, these datasets contain higher variability in polyp size, boundary ambiguity, and illumination, contributing to more challenging segmentation conditions. Visual evaluation further shows smoother and more coherent boundaries, especially on small or low-contrast polyps. Overall, the integration of the residual-gated mechanism and SE block within the attention gate effectively improves model accuracy and generalization, particularly in challenging scenarios.
Implementation of Concurrency Control to Prevent Race Condition in a Web-Based Billiard Table Reservation System Hermawan, Mohammad Luthfi; Suharso, Wildan
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/vrnggg84

Abstract

The development of information technology has driven the digitalization of various services, including web-based billiard table reservation systems. However, web systems that operate in real time are prone to race conditions when multiple users attempt to book the same table simultaneously, potentially leading to double booking. This study aims to implement a Concurrency Control mechanism using the Firebase Transaction feature to prevent such booking conflicts. The research method adopts a Research and Development (R&D) approach with the ADDIE model, which consists of the stages of Analysis, Design, Development, Implementation, and Evaluation. Furthermore, testing was conducted through pre-test and post-test simulations across 10 trials with concurrent users ranging from 2 to 11 individuals. In the pre-test stage, all users were able to successfully book the same resource simultaneously, resulting in 100% double booking across all trials. In the post-test stage, after implementing the Concurrency Control mechanism using Firebase Transaction, only one request was accepted out of the same 10 trials, while all other requests were automatically rejected, resulting in 0% double booking. These findings demonstrate that the applied concurrency control mechanism is effective in maintaining data consistency and preventing race conditions in the web-based billiard table reservation system.
Optimization of Household Energy use Prediction Using Random Forest with Genetic Algorithm Feature Selection Nisrinaa Kamilah, Nyimas; Rahman, Abdul
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/zedpkg51

Abstract

Electrical energy consumption continues to increase every year, so accurate prediction models are needed to support household electrical energy efficiency. This study analyzed high-resolution household electricity consumption data using the Random Forest (RF) algorithm and evaluated the influence of feature selection based on Genetic Algorithms (GA) in improving the performance of RF predictions. The base RF model achieves an RMSE of 0.6148, a MAE of 0.3478, and an R² of 0.5047. After implementing GA-based feature selection, the RF model with GA yields an RMSE of 0.6125 and an R² of 0.5084, indicating a marginal performance improvement. However, the MAE value increased slightly to 0.3503, which suggests that the increase was not uniform across the evaluation metrics. Overall, the RF approach with GA offers a modest improvement in prediction stability but with very limited accuracy gains, which highlights its potential and limitations in optimizing household energy consumption prediction.
Arduino UNO Application for Temperature Control Chicken Eggs Incubator Machine Nainggolan, Rufinus; Kamil, Idham; Qadry, Al; Pangihutan Sibarani, Marlon Tua; Sinabutar, Dohar; Br. Ginting, Berta
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/h94a3q23

Abstract

Poultry animals such as chickens incubate their eggs in three weeks to hatch their eggs, which sometimes the egg yields are not optimal so that a poultry egg incubator and its system are needed to optimize the results of hatching in which this built-in incubator with a capacity of 300 eggs with a rack system that rotates automatically based on Arduino Uno, using a digital temperature and hygrometer sensor so that the temperature can be set at 38-39 0C and the humidity can be set at 55-70% according to the egg hatching temperature and humidity, and from the test results obtained, the number of eggs that do not hatch and hatch both that hatch normally, defective, and die, the research conducted, for chicken eggs, which originally amounted to 300 eggs to be hatched, 291 eggs that hatched well, 5 defective eggs, and 3 eggs that died and 1 egg that does not have any embryos, and the result that this chicken egg incubator machine is capable of hatching eggs 97%.

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