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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 67 Documents
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Search results for , issue "Vol. 10 No. 2 (2025): July" : 67 Documents clear
Utilization of Satellite Imagery and GIS for Mapping Potential Anchovy Fishing Areas in East Lampung Rifki, Rifki Arif; Chairani, Chairani; Sriyanto, Sriyanto
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/t4fqfq25

Abstract

This study utilises Aqua MODIS satellite imagery from January to December 2023 to analyse Sea Surface Temperature (SST) and chlorophyll-a as primary indicators in mapping Potential Fishing Zones (PFZ) for anchovy in East Lampung. Images were filtered based on minimal cloud cover and seasonal completeness using Level 3 daily data with 1 km resolution. The spatial analysis was conducted using Geographic Information Systems (GIS) to identify areas with SST between 29–31°C and chlorophyll-a concentrations above 0.2 mg/m³, which are considered optimal for anchovy habitat. The results show dynamic seasonal shifts in fishing zones influenced by oceanographic conditions. Compared to previous studies, this research provides more detailed seasonal maps and incorporates local fishing data to strengthen relevance. Despite limitations in temporal continuity due to cloud coverage, the approach demonstrates potential for efficient and sustainable fisheries management in Lampung.
Schizophrenia Classification using Fuzzy K-Nearest Neighbour on Patient Data from RSJD Dr. Amino Gondohutomo Ozagastra Caluella Prambudi; Ajib Susanto; Christy Atika Sari
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/t2mfvf14

Abstract

Schizophrenia is a complex mental disorder with overlapping symptoms, making subtype diagnosis uncertain. This study aims to develop an automated classification method for schizophrenia subtypes using the Fuzzy K-Nearest Neighbour (FKNN) algorithm, which effectively handles uncertainty in medical data. The dataset includes 300 patients from RSJD Dr. Amino Gondohutomo, Central Java, aged 18–60 years, with balanced gender distribution. Four subtypes—paranoid, catatonic, hebephrenic, and undifferentiated—were classified. Symptom and demographic data were encoded and normalised using min-max scaling. The model was trained using k = 5 and evaluated via 10-fold cross-validation. The results achieved 94% accuracy with high precision and recall across all classes. However, limitations include a relatively small and single-source dataset and the lack of ROC/AUC analysis. These findings suggest that FKNN has strong potential as a data-driven decision support system for schizophrenia diagnosis, suitable for integration into psychiatric hospital information systems. Future research should explore oversampling techniques such as SMOTE and threshold tuning to improve model sensitivity.
Implementation of Convolutional Neural Network Algorithm in Recyclable Waste Recognition to Support Environmental Management Yuliana Fitriani; Evanita, Evanita; Akbar Riadi, Aditya
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/drcjhg64

Abstract

Waste remains one of the unresolved environmental problems, primarily due to ineffective waste management in sorting and recycling processes. Many individuals are unaware of or do not have the time to identify recyclable types of waste. This study aims to develop a web-based system capable of automatically classifying waste types to support raising public awareness of the importance of recycling. The method used is a CNN with a total of 1,800 images divided into six classes: glass, paper, metal, plastic, organic, and residual. The dataset is split into 1,296 images for training, 144 for validation, and 360 for testing. Unlike previous studies that classified only two to three types of waste or were not web-based, this system combines classification of six categories with an interactive web interface that can be directly used by the public. The results show that the developed model achieved an accuracy of 90%, with the best performance in classifying organic waste. However, the model still has limitations such as sensitivity to variations in lighting, varying image capture angles, and visual similarities among certain waste types that can affect classification accuracy. These findings indicate that the proposed system has the potential to help the community manage waste more effectively and sustainably.
Design of a Mobile Application for Real-Time Flood Information in North Aceh Region Based on GIS and Haversine Method Muhammad Naufal; Qamal, Mukti; LRosnita, Lidya
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/kwqt3q67

Abstract

This research focuses on the design and development of a mobile application for real-time flood information in the Aceh Utara region, utilizing Geographic Information Systems (GIS) and the Haversine method. The primary goal of this study is to provide an accessible and reliable tool for residents and local authorities to monitor flood events, allowing them to make timely and informed decisions. By integrating GIS technology, the application enables users to view flood-prone areas on an interactive map and receive real-time alerts based on proximity to flood locations. The Haversine method is applied to calculate distances between various flood points and user locations, ensuring the accuracy of the alerts. The methodology includes the design of a user-friendly interface and the implementation of real-time data processing. Results show that the application successfully integrates GIS and the Haversine method, providing accurate flood data and enhancing user experience in disaster management. The significance of this research lies in its potential to improve disaster preparedness and response in flood-prone regions, thus reducing the impact of floods on communities and infrastructure. This mobile application can be a crucial tool for managing flood risks and ensuring the safety of the population in Aceh Utara.
Development of Web-Based Multimedia Learning for Grade 3 Elementary School Mathematics Muharom, Ahmad; Rukhviyanti, Novi
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/sj1qng08

Abstract

The development of information technology has significantly contributed to the education sector, particularly in creating interactive and engaging learning media. Mathematics, as one of the core subjects, is often perceived as difficult and tedious by students. Therefore, there is a need for innovative learning media that can enhance students’ interest and understanding of the subject matter. This study aims to design and implement an interactive mathematics game website that presents basic math problems in an enjoyable and responsive format. The website consists of nine pages, including a landing page, login, dashboard, quiz selection, quiz display, and evaluation results. Each quiz contains 10 questions displayed in two horizontal rows (5 questions each), supported by a countdown timer and an automatic scoring system. The development methodology includes needs analysis, system design, implementation, and evaluation. The evaluation phase was conducted through internal testing and user observation targeting elementary school students.
Design of Android-Based Card Production Scheduling System Application using Rapid Application Development Method Barokah, Irma; Azrino Gustalika, Muhamad
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/9dksvc86

Abstract

PT. Cazh Teknologi Inovasi is a company focused on delivering excellent customer service. However, the current card production scheduling process, which is still managed manually through social media, has led to several issues, including a high risk of human error, product backlog, and long customer waiting times. These problems negatively impact service quality and customer satisfaction. To address this, an Android-based card production scheduling system was developed using the Rapid Application Development (RAD) method, which enables fast and flexible application development tailored to the company's needs. The system was tested using the black box method to ensure that each feature functions according to its specifications. The test results indicate that the system is feasible for use and can improve production efficiency while reducing customer waiting time.
Application of ARIMA and ARIMAX Methods to Predict the Number of Visitors to Hotel XYZ Pekanbaru Vernando, Julio; Insani, Fitri; Okfalisa, Okfalisa; Kurnia, Fitra
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/enrfna19

Abstract

Predicting the number of visitors to Hotel XYZ is one of the steps that can be taken by the hotel to find out how many visitors will increase in each upcoming holiday season. The purpose of this study is to forecast the number of visitors to Hotel XYZ from June 2023 to July 2024 using the ARIMA and ARIMAX comparison methods. The research methodology encompasses problem identification, data collection, data processing, and ARIMA and ARIMAX analysis, which involves testing the parameters (p, d, q) selected based on the ACF and PACF using the AIC Model. Based on the test results, ARIMAX (5, 0, 3) has the lowest AIC, which is 3495.2, followed by ARIMAX (3, 0, 5), which has a slightly higher AIC. The results showed that the ARIMAX (5, 0, 3) model is the most accurate model for predicting data (eg the number of hotel guests, room demand, or income), with an RMSE value of 15.80% and a MAPE of 18.90%. Therefore, research that applies the ARIMAX model can provide real benefits in supporting operational efficiency, resource management, and hotel business strategy, ultimately increasing the competitiveness and profitability of the hotel.
Virtual Tour Application for Cultural Heritage in North Aceh Regency using Augmented Reality Technology Melly, Melly Yani; Darnila, Eva; Maryana
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/3s7wyh46

Abstract

Cultural heritage refers to historical objects that must be preserved through protection, development, and utilisation. In North Aceh Regency, cultural heritage preservation faces challenges such as low interest among younger generations and the lack of interactive learning media. This study aims to design a virtual tour application using Augmented Reality (AR) and Geographic Information System (GIS) technologies as an interactive medium to digitally introduce cultural heritage sites. Data were collected from the Department of Education and Culture of North Aceh and through direct observation and documentation in the field. The application integrates AR features to display 3D cultural objects and GIS to present the geographical locations accurately. The development includes user interface design, motion-based navigation, and historical information panels. Testing results show that all markers successfully displayed 3D objects with an average detection time of 3.58 seconds, a detection distance of 75.71 cm, and a rotation angle of up to 360°. The objects appeared stable, and the historical information was well presented. The main contribution of this study is the implementation of AR technology in the local context of North Aceh, which has rarely been applied. Limitations include the small number of heritage sites and testing limited to a few AR devices. Future research is recommended to expand site coverage, improve device compatibility, and add gamification features to enhance user engagement.
Sentiment Analysis of Telegram Application User Satisfaction on Google Play Store Using Naïve Bayes, Logistic Regression and SVM Putri, Adellia Septiani; Fauzan Rozi, Anief
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/r6cyb589

Abstract

Sentiment analysis is a technique for finding out how people feel about something and putting the polarity of text into groups of documents or words so that they can be labeled neutral, positive, or negative. We will use the Naïve Bayes algorithm, logistic regression, and SVM to conduct sentiment analysis on how happy Telegram app users are. The purpose of this study is to see what people who use the app think and group their thoughts into three groups: neutral, positive, and negative. The three methods' results will be compared to see which is most accurate for this study. The results of this sentiment analysis show that many users are dissatisfied with the verification code they need to register or log in to their accounts. This makes it difficult for new users to get the verification code because the app itself sends it. The SVM approach has an accuracy value of 89.73%, which means it is more accurate in this study. The Naïve Bayes approach is accurate by 75.61%, while the logistic regression method is accurate by 87.49%.
Diabetes Detection Using Stacking Technique: A Combination of XGBoost, Gradient Boosting, and Meta Model Aden Rahmat, Aden Rahmat; Wahyu Utomo, Danang
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/48asdy77

Abstract

Type 2 diabetes mellitus is a chronic and progressively increasing global health issue that necessitates early detection to mitigate serious complications such as kidney failure, neuropathy, and cardiovascular disorders. While numerous studies have developed predictive models using machine learning techniques, many are limited by their reliance on single algorithms and inadequate handling of class imbalance. This research introduces a novel strategy by employing an ensemble stacking method that integrates Gradient Boosting, XGBoost, and Random Forest, with Random Forest acting as the meta-learner. The dataset, comprising 100,000 patient records, underwent preprocessing and was balanced using the SMOTE-Tomek approach to correct class distribution disparities. The stacking process is implemented in two phases: base models generate preliminary predictions, which are subsequently used as input for the meta-model to refine the final outcomes. The evaluation demonstrates that the stacking model achieves superior performance, recording 98% accuracy and an F1-score of 0.98, outperforming the individual models. The key distinction of this study lies in the effective application of ensemble stacking to enhance prediction accuracy, especially in dealing with imbalanced and complex medical data. This methodology has the potential to improve clinical decision support systems, making them more accurate and responsive.  

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