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Jurnal Teknologi Informatika dan Komputer
Published by Universitas Mohammad Husni Thamrin
ISSN : 26569957     EISSN : 26228475     DOI : https://doi.org/10.37012/jtik
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Jurnal Teknologi Informatika dan Komputer merupakan salah satu jurnal berbasis Open Journal System (OJS) yang dikelola oleh Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM) Universitas Mohammad Husni Thamrin (UMHT) yang berisi artikel-artikel dengan topik Teknologi Informasi yang menampung karya ilmiah para dosen Perguruan Tinggi di Indonesia. Diharapkan jurnal ini mampu memberikan motivasi dan kontribusi ilmiah bagi perkembangan ilmu pengetahuan dan teknologi.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 728 Documents
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Zero Trust Network Architecture Design For Mid-Scale Organizations Kamila, Nurul; Makhsun; Sudarno
Jurnal Teknologi Informatika dan Komputer Vol. 12 No. 1 (2026): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v12i1.3292

Abstract

The development of information technology, the adoption of cloud-based services, and the implementation of remote work patterns increase network security risks in medium-sized organizations. Traditional network security approaches that focus on the perimeter are considered no longer adequate in facing increasingly complex cyber threats. This study presents the design of a Zero Trust Network (ZTN) architectural blueprint specifically designed for medium-sized organizations. The research method used is a conceptual approach through literature review, network security requirements analysis, and the design of the ZTN logical architecture. The research results are a Zero Trust Network architectural blueprint that emphasizes continuous verification, identity-based access control, and the application of the principles of least privilege and micro-segmentation. The architectural design is arranged in a modular and phased manner and is aligned with the NIST SP 800-207 framework, so it remains realistic for adoption without requiring drastic infrastructure changes. The resulting ZTN architectural blueprint can be used as an initial reference for medium-sized organizations in designing a Zero Trust-based network security strategy. This research is conceptual in nature and does not include the implementation stage or empirical testing in a real operational environment. It is hoped that the results of this study can serve as an initial reference for medium-sized organizations in designing a more adaptive and sustainable network security strategy.
Comparison of Faster R-CNN and YOLO v12 on Passport Text Extraction Based on Optical Character Recognition Samosir, Masniari; Anggai, Sajarwo; Taryo, Taswanda
Jurnal Teknologi Informatika dan Komputer Vol. 12 No. 1 (2026): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v12i1.3307

Abstract

Current developments in information technology are driving the need for digitalization of official identity documents, including passports, to improve service efficiency and reduce reliance on manual processes. The digitalization of official identity documents such as passports still faces efficiency and accuracy challenges due to manual data entry processes. This study aims to compare the performance of Faster R-CNN and YOLO v12 in an automatic text extraction system based on Optical Character Recognition (OCR). The research employed an experimental method with a comparative approach using 31 preprocessed passport images. YOLO v12 was integrated with EasyOCR, while Faster R-CNN was combined with a PyTorch-based OCR module. The evaluation metrics included mAP, Character Accuracy Rate (CAR), Word Error Rate (WER), F1-score, and inference time. The results indicate that YOLO v12 outperforms Faster R-CNN in object detection, achieving an mAP@50 of 95.0% and mAP@50–95 of 90.0%, compared to 93.0% and 89.0%, respectively. In terms of text extraction accuracy, Faster R-CNN achieved a CAR of 50.01% and an F1-score of 55.75%, slightly higher than YOLO v12 with a CAR of 47.72% and an F1-score of 53.84%. However, YOLO v12 produced a lower WER and faster inference time of 2.4202 seconds (0.45 FPS). The findings suggest that YOLO v12 excels in efficiency and detection performance, while Faster R-CNN performs better in specific text extraction accuracy.
Implementation of Temporal Fusion Transformer (TFT) for Short-Term Sales Prediction of Telkomsel Data Packages in East Java Muhammad Azkiya Akmal; Trimono; Alfan Rizaldy Pratama
Jurnal Teknologi Informatika dan Komputer Vol. 12 No. 1 (2026): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v12i1.3268

Abstract

The development of the cellular telecommunications industry has driven an increasing demand for fast, stable, and affordable data services. Accurate forecasting of data package sales is a significant challenge for telecommunications operators due to high demand fluctuations and the complexity of time series patterns. This study aims to implement a Temporal Fusion Transformer (TFT) model based on Seasonal-Trend Decomposition using Loess (STL) to predict short-term sales of Telkomsel data packages in East Java. The data used are sales transactions with hourly time resolution from January to June 2024, focusing on the five data packages with the highest transaction volume. The STL method is applied in the pre-processing stage to separate the trend, seasonal, and residual components, which are then used as additional features in the TFT modeling. Model performance is evaluated using Mean Absolute Error (MAE) and Quantile Risk (q-Risk). The results show that the TFT model is able to produce accurate predictions with an MAE value of 3.6941 and an average q-Risk of 0.0808. Furthermore, interpretability analysis revealed that historical sales variables, seasonal components, and calendar variables significantly contributed to the prediction results. These findings indicate that the STL-based TFT approach is effective for short-term sales forecasting and has the potential to support data-driven operational decision-making in the telecommunications sector.
East Java Inflation Prediction Based on Exchange Rates and International Trade Using the ARIMAX Approach Zahrotun, Nafisah; Aditya Nugroho, Rizky; Andhyka, Awang
Jurnal Teknologi Informatika dan Komputer Vol. 12 No. 1 (2026): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v12i1.3287

Abstract

East Java's macroeconomic stability is vulnerable to external shocks, particularly imported inflation, which impacts domestic price formation. This study aims to develop an inflation forecasting model using the AutoRegressive Integrated Moving Average with Exogenous Variables (ARIMAX) approach as an Early Warning System instrument for regional policymakers. This study uses monthly time series data for the 2015–2024 period. Exogenous variable selection was conducted through the Granger Causality Test, which showed that only import volume had a significant effect on inflation, while exchange rates and exports were insignificant. The estimation results show that the ARIMAX(1,0,1) model is the best model with a forecasting accuracy level based on the Mean Absolute Percentage Error (MAPE) value of 10.40%, which is categorized as good. East Java's inflation projection for the 2025–2029 period shows an increasing trend from 1.99% to 3.28%, indicating the need for vigilance for policymakers in strengthening import supply chain management to mitigate the risk of future price pressures. Based on the theoretical and empirical review, this study hypothesizes that the exchange rate and international trade indicators have a significant predictive relationship with the inflation rate in East Java Province. This study aims to develop an inflation forecasting model for East Java using the ARIMAX approach, considering the exchange rate and international trade variables as candidate exogenous variables.
Comparison of ResNet50, ResNet101, and ResNet152 Architectures in Image-Based Rice Leaf Disease Classification Ardi Setyiawan; Septiarini, Anindita; Andi Tejawati
Jurnal Teknologi Informatika dan Komputer Vol. 12 No. 1 (2026): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v12i1.3289

Abstract

Rice leaf diseases are one of the main threat that can reduce rice crop productivity especially if they are not detected at an early stage. Conventional disease identification still has limitations because it relies on visual observation and the experience of farmers. Therefore, this study proposes a rice leaf disease classification approach based on digital images using deep learning methods. This study aims to compare the performance of three Residual Network architectures, namely ResNet50, ResNet101, and ResNet152. The dataset used was collected from three public Kaggle datasets, consisting 7.322 images divided into four classes (healthy, hispa, sheath blight, and brown spot). The dataset was split into training, validation, and testing sets with a ratio of 70:20:10 and processed through image preprocessing and data augmentation. All models were trained using a transfer learning approach with the same training configuration to ensure a fair comparison. Model performance was evaluated with the test sets using loss, accuracy, and confusion matrix analysis. The experimental results show that ResNet101 achieved the best performance with a loss value of 0,0146 and an accuracy of 0,9973. Followed by ResNet50 with an accuracy of 0,9918, and ResNet152 with an accuracy of 0,9837. These results indicate that ResNet101 provides the best balance between network depth and classification performance.
Application of Data Mining to Analyze Sales Patterns of Merchandise in MSMEs in Sait Buttu Saribu Tourism Village Using the Apriori Algorithm Khofifah Fauzani; Ali Ikhwan
Jurnal Teknologi Informatika dan Komputer Vol. 12 No. 1 (2026): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v12i1.3291

Abstract

The development of information technology in the era of globalization has brought significant changes to various aspects of life, including business and trade activities. Information is a crucial component in supporting fast, precise, and accurate decision-making, both at the operational and strategic levels. This study aims to apply the Apriori algorithm to analyze the sales patterns of MSMEs in the Sait Buttu Saribu Tourism Village and to develop a web-based system that can support business decision-making. MSMEs play a vital role in the local economy, but sales data utilization is still suboptimal. Sales transaction data from 2023–2024 from 57 active MSMEs were used as the research object. The research method used is Research and Development (R&D) with the system development using the Waterfall method. The Apriori algorithm was applied to find association patterns between products based on support and confidence values. The results show that the Apriori algorithm is able to identify product combinations that are frequently purchased together so that they can be utilized for sales strategies such as product bundling, product arrangement, and inventory control. The developed system is expected to help MSMEs manage sales data more effectively and support data-driven decision-making. Therefore, this study applies the Apriori algorithm to analyze the sales patterns of MSME merchandise in Sait Buttu Saribu Tourism Village and builds a web-based system as a decision- making tool.
Implementation of Information System and Software Quality Testing in Company Operational Applications Based on ISO/IEC 25010 (Case Study: PT Snapdev Digital Indonesia) Anwar, Chairul; Rahmat Hartono
Jurnal Teknologi Informatika dan Komputer Vol. 12 No. 1 (2026): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v12i1.3294

Abstract

Implementation of information system quality testing is an important factor in supporting the effectiveness and efficiency of company operations. This study aims to implement an information system and conduct software quality testing based on the ISO/IEC 25010 standard at PT Snapdev Digital Indonesia. Quality testing is carried out by measuring seven main characteristics, namely Performance Efficiency, Compatibility, Usability, Reliability, Security, Maintainability, and Portability. The research methods used include observation, data collection, and analysis of test results based on indicators in each ISO/IEC 25010 characteristic. The measurement results show that the percentage value for each aspect of system quality is in the range of 79%–83%, which indicates that the system has met most of the established quality criteria. The overall average value of 80.97% places the system quality in the very good category. This indicates that the system has efficient performance, adequate levels of security and reliability, good ease of use, and can be maintained and run in various environments. However, there are still opportunities for improvement in several aspects to improve system quality to be more optimal. Overall, the implemented information system is considered suitable for use and complies with international software quality standards.
Application of Transfer Learning Method on Convolutional Neural Network (CNN) to Identify Genuine and Fake Diplomas Awaludin, Rifa; Anggun Fergina; Gina Purnama Insany
Jurnal Teknologi Informatika dan Komputer Vol. 12 No. 1 (2026): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v12i1.3295

Abstract

The authenticity of diplomas plays a crucial role in maintaining the integrity of the education system and ensuring that recognized academic competencies align with an individual's actual achievements. Diplomas are not merely administrative documents, but strategic instruments in job recruitment and professional qualification assessment. However, with increasing educational mobility, document misuse through diploma forgery is becoming increasingly prevalent, potentially undermining public trust in educational institutions. Currently, the verification process is still largely carried out manually through visual inspection of document elements such as layout and stamps. The reliance on the examiner's experience makes this method vulnerable to inconsistencies and human error, especially when dealing with fake diplomas with visual qualities that increasingly resemble genuine documents. Diploma forgery is a problem that impacts the credibility of educational institutions and the validity of academic data. Manual inspection is often inconsistent and time-consuming. This study develops a model for classifying genuine and fake diplomas using a Convolutional Neural Network (CNN) with a transfer learning scheme. The performance of the ResNet50, VGG16, and MobileNetV2 architectures is comparatively analyzed. Data preprocessing included resizing, normalization, and augmentation. Test results showed the ResNet50 architecture achieved optimal performance with 92.63% accuracy, 92.16% precision, 94.00% recall, and 93.07% F1-score. The system was implemented in a Streamlit-based web application to facilitate the verification process.
Design of Web-Based Warehouse: A Case Study of Web-Based Project Equipment Inventory System Using Waterfall Method Gustiawan, Handa; Rian, Hesti; Irfan, Akbar Muhamad
Jurnal Teknologi Informatika dan Komputer Vol. 12 No. 1 (2026): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v12i1.3310

Abstract

Inventory is crucial for a company. The warehouse still uses books to record receipts, expenditures, and stock. Manual inventory management often leads to various problems, such as data accumulation, inconsistencies in stock quantities, late reporting, and the risk of data loss. This study aims to design and build a web-based inventory information system to replace manual recording and improve warehouse management efficiency in a contractor company to address these issues. The research method used is the waterfall method, which includes requirements analysis, design, coding, and testing. The system was developed using the PHP programming language with a MySQL database and an easy-to-use web-based interface. The results show that the system was successfully built with features for managing incoming and outgoing goods, suppliers, customers, and monthly reports. Black Box Testing on the login form produced all valid scenarios as expected. This system has been proven to accelerate the process of recording and generating inventory reports accurately and efficiently.
Android-Based Car Rental System with Customer Risk Management for MSMEs Ridwansyah
Jurnal Teknologi Informatika dan Komputer Vol. 12 No. 1 (2026): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v12i1.3221

Abstract

The development of information technology has become a major factor in driving digital transformation in various business sectors, including Micro, Small, and Medium Enterprises (MSMEs). Digital transformation through the use of information systems has been proven to improve organizational performance, support innovation, and improve data-based decision-making processes at the small and medium business scale.  Manual recording is still frequently used by Micro, Small, and Medium Enterprises (MSMEs), including those engaged in the car rental sector. This practice can create vulnerabilities to recording errors, resulting in inaccurate information. To address this problem, this study developed an Android-based car rental system to assist business owners in managing their operational activities. The research stages referred to the System Development Life Cycle (SDLC) method, using the Waterfall model. The resulting system includes customer data management, rental transactions, and rental duration. In addition, the system is equipped with a blacklist feature. This feature is a customer risk management feature that blocks problematic customers based on their previous transaction history. To ensure the suitability of the system's functions, Black Box Testing was conducted. The test results showed that all the system features functioned as expected. The results of this study are expected to help car rental business owners monitor daily operational activities, including avoiding the risk of car loss due to problematic customers.

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