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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 256 Documents
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Effectiveness of the Sampean Application in Measuring Administrative Management Performance in Cirebon City Government Siswanto, Febiola Inanta; Rocky Tanaamah, Andeka; Banunaek, Frids Edward
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: 10.35314/8rsax831

Abstract

SAMPEAN Cirebon is a service portal for managing the administrative needs of Civil Servants (ASN) in the Cirebon City Government. Since its launch, the application has faced several technical issues, mainly because it has never been evaluated from the perspective of end users. This research aims to assess end-user satisfaction, identify areas for improvement, and determine the critical factors influencing user satisfaction with the SAMPEAN Cirebon application. The research applies the End-User Computing Satisfaction (EUCS) method, which consists of five independent variables: content, format, accuracy, ease of use, and timeliness. Data was collected with a voluntary sampling technique, gathering 692 respondents. The data was analyzed using the SEM-PLS method with the SmartPLS application. The results show an R-square value of 0.828, indicating that four variables content, accuracy, ease of use, and timeliness significantly influence ASN satisfaction with the SAMPEAN Cirebon application. In contrast, the format variable yielded a T-statistic of 1.746 and a P-value of 0.081, failing to meet the significance threshold. The practical implications of this study underscore the necessity for the Cirebon City Regional Government to conduct regular evaluations involving direct end-user feedback and to enhance the format aspects of the SAMPEAN Cirebon application.
Decade Rainfall Prediction Using Prophet Algorithm and LSTM (Case Study in Banjarnegara Regency) sulis, Sulistiyowati; Eri Zuliarso
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/j3mbxq89

Abstract

Hydrometeorological disasters such as floods and landslides in Banjarnegara Regency are closely related to fluctuating rainfall variability. This study aims to predict decadal (10-day) rainfall by comparing the performance of the Prophet algorithm and the Long Short-Term Memory (LSTM) model. The dataset comprises daily rainfall records from 14 observation stations spanning the period 2005–2024. The research stages included preprocessing, modelling, hyperparameter optimization using Optuna, and evaluation with Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The results indicate that the Prophet model outperformed LSTM in most locations, with an average RMSE of 69.55 and MAE of 53.05, lower than LSTM, which recorded 73.03 and 55.72, respectively. The ensemble averaging model produced competitive results at several locations, although it was less responsive to sharp fluctuations in rainfall. These findings confirm that Prophet is more effective in capturing seasonal patterns and long-term trends, thus providing significant potential to support climate-based disaster mitigation systems in vulnerable areas such as Banjarnegara
Implementation of IP SLA and Policy-Based Routing for Failover In a Multi-Homed Network Yusak, Dysan; Sulistyo, Wiwin
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/g2av9m56

Abstract

In the current digital era, stable and uninterrupted internet connectivity is the backbone of modern operations, demanding high availability and reliability. A key challenge is managing the inherent single point of failure associated with a single ISP connection. This study investigates the implementation and effectiveness of IP Service Level Agreement (IP SLA) and Policy-Based Routing (PBR) on a multi-homed network to achieve automated failover optimization. A virtual testbed was constructed using EVE-NG with a Cisco IOS C7200 image, and each test scenario was replicated five times to ensure data consistency. IP SLA was configured for proactive failure detection (parameters: timeout 5000 ms, threshold 500 ms, request-data-size 100, delay up 10, delay down 5), while PBR was used for VLAN-based traffic steering. The results indicate that this solution successfully steered traffic according to policy and achieved a consistent failover switchover time of 1.07–1.09 seconds (n=5), supported by Wireshark analysis, which documented up to 100% packet loss during the transition. The failure detection time, directly correlated with the IP SLA frequency, varied from 3.96 seconds (5-second frequency) to 45.63 seconds (60-second frequency). During the transition, router CPU load remained low at 3%, indicating high resource efficiency. This research concludes that the combination of IP SLA and PBR is an effective solution for enhancing the resilience and service continuity of multi-homed networks with minimal computational overhead.
Analysis of 5G Signal Quality on 2100 MHz and 2300 MHz Frequencies Based on RSRQ, RSRP, and SNR Parameters Tobmuti, Dito; Christianto, Eriwien
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/ef6wsn27

Abstract

Abstract—The rapid growth of cellular communication technology necessitates fast and stable internet connections. This research addresses the limited studies on 5G network performance in Surakarta City, which is experiencing increased demand for reliable internet access. We employed a drive test method using the G-Net Track Pro application to measure 5G signal quality based on RSRP, RSRQ, and SINR parameters on 2100 MHz and 2300 MHz frequencies. The study aimed to compare signal quality between Telkomsel and XL across four key locations in Surakarta. Results indicate that Telkomsel generally shows excellent RSRP, while XL also provides competitive signal strength in specific areas. RSRQ for both operators consistently falls into the "Good" category. However, SINR values varied significantly, highlighting the impact of interference and noise on overall user experience, particularly in Jl. Kebangkitan Nasional for Telkomsel and Jl. Ronggowarsito for XL. This study emphasizes the importance of comprehensive signal parameter measurements for real-time network assessment.
Prediction of Bank NEO Commerce Stock Prices Using a Multiple Linear Regression Algorithm Harahap, Ulil Amri; Sriani
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/dxpvea41

Abstract

This study addresses the challenge of forecasting Bank Neo Commerce (BBYB) daily prices, where volatility and data leakage often bias results. We build a leakage-free pipeline to predict next-day Adjusted Close using multiple linear regression (OLS) with t−1 predictor lags and technical indicators: AdjCloset−1​, AdjCloset−5, Volt−1​, SMA5t−1​, EMA5t−1​, and RSI 14t−1. Daily BBYB.JK data from Yahoo Finance (12 March 2019–12 March 2025) are evaluated with a 5-fold rolling time-series split, and metrics are reported as mean ± SD. The goal is to assess OLS accuracy and its practical value against a persistence baseline. OLS attains MAE 25.15 ± 18.24, MSE 2,344.41 ± 2,956.78, R² 0.94 ± 0.06, while the baseline AdjCloset−1 yields MAE 22.40 ± 17.21, MSE 1,894.99 ± 2,420.42, R² 0.96 ± 0.04. A walk-forward long-only backtest (0.1% fee) delivers a final value of 1.04 versus 0.72 for buy-and-hold, with lower volatility and drawdown. The approach is interpretable, reproducible, and ready for extensions (feature reduction/regularization, non-linear models, and return/volatility features)
The use of FMADM and SAW Methods in Decision-Making in Selecting the Chairman of the Study Program Helpi Nopriandi; Elgamar Syam; Jasri; Erlinda; M. Yusfahmi; Sri Chairani
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/b3ext947

Abstract

The selection of Head of Study Program (Head of Study Program) in Higher Education is often still done subjectively through personal recommendations, without measurable assessment instruments and transparent evaluation reports. This study aims to design a decision support system based on Fuzzy Multiple Attribute Decision Making (FMADM) with the Simple Additive Weighting (SAW) method to improve the objectivity and accountability of the Head of Study Program selection process. The research data consists of 10 candidates for permanent lecturers in the Informatics Engineering Study Program at Kuantan Singingi Islamic University in 2025 with five assessment criteria: length of service (C1), functional position (C2), education (C3), performance (C4), and achievement (C5). The analysis process was carried out by converting the data into fuzzy numbers, normalizing according to attribute types, and calculating preference values ​​using the SAW method. The results showed that the top three candidates were Harianja, S.Pd., M.Kom and Elgamar, S.Kom., M.Kom with the highest V value of 2.75, followed by Febri Haswan, S.Kom., M.Kom with a value of 2.50. The main contribution of this research is to provide a Head of Study Program selection model that is consistent with other MADM methods (TOPSIS and VIKOR), in accordance with historical selection patterns, and is able to increase transparency, objectivity, and accountability through measurable evaluation reports that can be used as a basis for the SOP for selecting Heads of Study Programs.
Phishing Website Detection Using a Machine Learning Classification Approach Ibnu Arifin; Chairani
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/yja1d830

Abstract

Phishing is a form of cybercrime that is increasingly prevalent, with millions of attacks recorded annually. This study develops a phishing website detection model using a machine learning classification approach, employing a pipeline that includes data preprocessing, feature selection, and model validation. The dataset was obtained from the UCI Machine Learning Repository and consists of 235,795 URLs with a relatively balanced distribution between phishing (100,945) and non-phishing (134,850). After data cleaning and feature selection, 21 optimal features were retained, ensuring they were safe from potential data leakage. Two algorithms were evaluated: decision tree and random forest, using 10-fold cross-validation. The random forest algorithm achieved an average accuracy of 97.78%, while the decision tree was slightly higher at 98.02%. However, random forest outperformed in class discrimination, as measured by ROC-AUC (99.73%) and PR-AUC (99.78%), compared to decision tree values of 99.49% and 99.40%. The method also incorporated a 10-fold cross-validation procedure to minimize data leakage and ensure reliable model evaluation. The Wilcoxon test further confirmed that the performance difference between the two algorithms is statistically significant. Overall, although the decision tree demonstrates strong classification performance, random forest proves to be more consistent and reliable in detecting phishing websites, making it a superior choice in the context of cybersecurity.
Integration of K-Means Clustering and GPT-4.1 for an AI-Based Strategic Hotel Decision Support System Anasayyasy, Daffa; Whily Ambodo, Inov; Herwanto, Patah
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/rh6p1t14

Abstract

This research develops an artificial intelligence-based strategic decision support system for optimizing hotel revenue management, integrating K-Means Clustering and GPT-4.1. The novelty of this study lies in the combination of daily performance analysis using K-Means for segmentation and narrative-based recommendations generated by GPT-4.1, a novel approach not widely applied in hospitality contexts. This approach not only utilizes data segmentation techniques but also transforms the segmentation results into strategic recommendations that are practical and easily understood by hotel management. The theoretical contribution of this research is the development of an integration method between clustering algorithms and large language models, while its practical contribution is the improvement of operational decision-making efficiency based on data, which can enhance hotel performance and daily revenue. Thus, this research contributes to the development of AI-based systems that can be adapted to other service sectors with similar operational patterns.
Intelligent System for Monkeypox Disease Diagnosis Using Hybrid Certainty Factor and Fuzzy Logic Methods M. Agung Vafky Ideal; Tomy Nanda Putra
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/h13m0k54

Abstract

Monkeypox cases has the potential to spread rapidly, making early detection crucial to prevent wider transmission. Unfortunately, at the UPT Puskesmas where this study was conducted, there is no system available to assist medical personnel in performing fast and standardized diagnoses. To address this issue, this research developed a web-based intelligent system by combining the Certainty Factor (CF) and Fuzzy Logic methods. The system’s knowledge base was constructed from symptom data collected through expert interviews and literature studies. It was then tested using data from 30 patients with similar symptoms. The processing involved calculating certainty values with CF and mapping them into fuzzy membership degrees. The test results showed an accuracy of 86%, demonstrating that the combination of CF and Fuzzy Logic improves diagnostic accuracy while providing results that are easier to interpret. Therefore, the developed system can serve as a diagnostic aid for monkeypox in primary healthcare centers, particularly in situations with limited diagnostic facilities, and can also serve as a foundation for developing intelligent detection technologies for other infectious diseases.
Design of a Web-Based Church Notice Board System Using the Waterfall Method Pradhana, Bertrandus Iffan; Fiodinggo Tanaem, Penidas
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/hwnhzk87

Abstract

This study designs a web-based church announcement board system using the Waterfall method to improve communication effectiveness compared to physical bulletin boards. The system was developed using PHP, MySQL, HTML, CSS, and JavaScript through stages of requirement analysis, design, implementation, and black box testing. It introduces features for uploading weekly bulletins and dynamic announcement management, accessible directly by church members via a browser. The implementation results show a reduction in announcement publishing time from 2 hours to 4 minutes and a 75% decrease in administrative workload. Black box testing on 7 scenarios confirmed that all core features, such as login, announcement management, and bulletin uploads, functioned as expected. The page load time averaged 1.2 seconds, with responsive performance on mobile devices and a p95 response time of 480 ms for 100 concurrent users. This study contributes to the digitalization of church information, providing a more efficient, interactive, and real-time system, thereby enhancing information accessibility for the congregation.

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