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Journal of Information Technology
Published by Universitas Bhinneka Nusantara
ISSN : 23031425     EISSN : 2580720X     DOI : https://doi.org/10.32664/j-intech
Core Subject : Science,
Computer Science & IT
Journal of Information and Technology is a journal published by Bhinneka Nusantara University, Malang. The scope of this journal includes IT Governance, IS Strategic Planning, IS Theory and Practices, Management Information System, IT Project Management, Distance Learning, E-Government, Information Security and IT Risk Management, E-Business / E-Commerce, Big Data Research, and other related topics.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 347 Documents
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Development of an Integrated Web-Based Academic and Administrative Information System with E-Learning and Student Interest Recommendation Ahmad Hasan Faqih Aulia; Muhammad Raihan Zaldiputra; Ardien Ferdinand Putra Setiawan; Ridho Putra Pratama; Sofiyanti Indriasari; Medhanita Dewi Renanti
J-INTECH ( Journal of Information and Technology) Vol 14 No 02 (2026): Journal of Information and Technology
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v14i02.2323

Abstract

The advancement of information technology in the education sector has driven the need for digital transformation in managing academic and administrative processes, including in Early Childhood Education (ECE) institutions. However, many ECE institutions, such as BKB PAUD Bougenville, still rely on manual and fragmented systems for managing student data, attendance, assessments, and learning materials, which often leads to inefficiencies, data inconsistencies, and delays in information processing. This study aims to develop an integrated web-based academic and administrative information system that incorporates e-learning features and student interest recommendations to support more effective and structured educational management. The system is developed using the Agile methodology, which emphasizes iterative development, continuous user involvement, and adaptive improvements based on user feedback to ensure alignment with real operational needs. The proposed system integrates several core modules, including student data management, attendance recording, e-learning through digital materials (e-books), assessment processing, and a data-driven student interest recommendation feature. The implementation results indicate that the system is able to improve data management efficiency, facilitate real-time access to academic and administrative information, and reduce the risk of data inconsistencies. In addition, the interest recommendation feature provides practical benefits by assisting teachers in identifying student potential and supporting more informed decision-making processes. Therefore, this research contributes to the development of an integrated, user-friendly, and adaptive digital platform that enhances the quality of academic and administrative services in the PAUD environment.
Lexicon-Based Approach for Sentiment Analysis of Technology Students in the City of Tegal toward AI Adoption in Learning Dzulchan Abror; Angga Ardiansyah
J-INTECH ( Journal of Information and Technology) Vol 14 No 02 (2026): Journal of Information and Technology
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v14i02.2335

Abstract

This study aims to analyze the sentiment of technology students in Tegal City toward the adoption of Artificial Intelligence (AI) in learning. The explicit novelty of this research lies in its empirical focus on a localized tech-cluster student cohort within a regional urban area (Tegal City) who display uniquely high frequencies of digital-tool interaction, coupled with a specialized lexicon-based computational framework optimized for Indonesian academic linguistics. The research employs a descriptive quantitative approach combined with text mining techniques. Data were collected through an online survey involving 158 respondents using a questionnaire consisting of closed and open-ended questions. Sentiment analysis was conducted using a lexicon-based method to classify opinions into positive, neutral, and negative categories. The results indicate that students’ experiences with AI are dominated by positive sentiment (56.96%), reflecting its benefits in improving efficiency and understanding of learning materials. However, in terms of future expectations, there is an increase in neutral (44.94%) and negative (8.86%) sentiments, indicating a more critical perspective. The main concerns include overdependence on AI and the accuracy of AI-generated information. This study concludes that AI has significant potential to support learning, but its use should be balanced with the development of critical thinking skills and the improvement of reliable and accurate AI systems.
PENGEMBANGAN SISTEM KASIR PRINT COLOR ANALYSIS PADA PERCETAKAN PENJILIDAN EXPRESS TULUNGAGUNG MENGGUNAKAN FRAMEWORK LARAVEL DENGAN KERANGKA KERJA SCRUM Lailatul Musyarofa; Yayak Kartika Sari; Joko Iskandar
J-INTECH ( Journal of Information and Technology) Vol 14 No 02 (2026): Journal of Information and Technology
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v14i02.2341

Abstract

The manual and subjective process of determining color printing costs and recording sales transactions at Penjilidan Express, which resulted in inconsistent pricing, recording errors, and reduced operational efficiency. This research focuses on developing a web-based cashier system equipped with a Print Color Analysis feature to support more objective and consistent printing cost estimation and streamline transaction management. The system was developed using the Scrum framework and implemented with the Laravel framework based on the Model-View-Controller (MVC) architecture. The Print Color Analysis feature calculates the percentage of RGB/CMYK color composition from digital files in JPG, PNG, and PDF formats to automatically estimate printing costs. The developed system was evaluated through Black Box Testing across seven core functional features. The results demonstrated that every tested feature performed as expected, achieving a 100% success rate and confirming that the system fulfilled all predefined functional requirements.The developed system is expected to improve the consistency of printing cost calculations, streamline transaction processing, and minimize the risk of errors in sales data recording. Therefore, the proposed system can serve as an effective solution to support operational efficiency, pricing transparency, and business digitalization in printing service companies.  
Analysis of E-Business Strategy at PT Damri: PEST, SWOT, Porter's Five Forces, and Value Chain Approach Riska Suryani; Rosyid R Al-Hakim; Sumardiono
J-INTECH ( Journal of Information and Technology) Vol 14 No 02 (2026): Journal of Information and Technology
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v14i02.2347

Abstract

This study aims to analyze the e-business strategy implemented by PT Damri, a state-owned transportation company in Indonesia. Using a qualitative case study approach, data were collected through literature studies and analyzed using PEST, SWOT, Porter's Five Forces, and Value Chain analysis. The results show four key findings: (1) PEST analysis identifies technological factors (4G/5G, cloud computing, IoT) as the primary drivers of digital opportunity, while social barriers (digital divide, low literacy) remain the main challenges; (2) Porter's Five Forces reveals high buyer bargaining power and high competitive rivalry as the most critical external pressures requiring digital differentiation; (3) SWOT analysis positions PT Damri in the SO (Strengths-Opportunities) quadrant, indicating that brand strength and extensive route networks should be leveraged to capitalize on growing smartphone penetration; (4) Value Chain analysis shows that marketing & sales and customer service activities derive the highest benefit from e-business integration. Based on these findings, the study recommends strengthening the digital platform, strategic partnerships with travel and fintech platforms, digital training for employees, and phased digital transformation to minimize disruption.
IMPLEMENTASI K-MEANS CLUSTERING PADA SISTEM PENGADUAN MASYARAKAT BERBASIS WEB UNTUK MENINGKATKAN EFISIENSI DAN TRANSPARANSI Lalu Yazid Adnan; Ahmad Heru Mujianto
J-INTECH ( Journal of Information and Technology) Vol 14 No 02 (2026): Journal of Information and Technology
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v14i02.2350

Abstract

The community complaint system in Sumengko Village still relies on conventional methods such as direct visits to the village office and deliberation forums, making it difficult for village officials to systematically categorize complaints and determine the appropriate handling priorities. This research aims to design and develop a web-based community complaint system integrated with the K-Means Clustering algorithm to automatically group complaints based on the similarity of text characteristics. The system is built using the Laravel framework based on PHP with a MySQL database, and applies text preprocessing stages including case folding, tokenizing, stopword removal, and stemming, followed by TF-IDF weighting to convert the text into a numerical representation before the clustering process is performed. The dataset used consists of 15 complaint documents representing three dominant topics: infrastructure, environment, and health. Validation of the number of clusters using the Elbow Method shows k=3 as the optimal point with the lowest significant SSE value. The clustering results show that the K-Means algorithm converges at the 2nd iteration with the following cluster distribution: C₁ Infrastructure (60%), C₂ Environment (33.3%), and C₃ Health (6.7%), indicating that infrastructure-related complaints are the dominant issue reported by residents. Usability evaluation using the System Usability Scale (SUS) yielded an overall mean score of 79.25, categorized as "Good" with an acceptability level of "Acceptable," confirming that the system is well-received by both village administrators and community members. This system not only serves as a medium for submitting complaints digitally but also as an automatic analysis tool that helps village officials prioritize complaint handling more efficiently and transparently.
Deteksi dan Klasifikasi Sampah Organik dan Anorganik Menggunakan Algoritma Yolo di Solo Technopark Rafel Fernando; Afu Ichsan Pradana; Sopingi
J-INTECH ( Journal of Information and Technology) Vol 14 No 02 (2026): Journal of Information and Technology
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v14i02.2362

Abstract

The advancement of artificial intelligence (AI) technology, particularly in the area of computer vision, has encouraged the use of automatic object detection methods for various needs, including the classification of organic and inorganic waste. The problem of waste management in the Solo Technopark area which is still carried out manually causes the waste sorting process to not run optimally. This research focuses on developing and evaluating the performance of several YOLO models for detecting and classifying organic and inorganic waste types in real-time. The research dataset contains 6,758 waste images categorized into 10 object classes, obtained from Roboflow. The preprocessing stages include annotation, auto-orientation, and image resizing to 640×640 pixels. The dataset is then divided into 70% training data, 20% validation, and 10% testing. This study used three YOLO models, namely YOLOv11, YOLOv12, and YOLOv26 with epoch variations of 10, 30, 50, and 100. Model evaluation was carried out using precision, recall, mAP50, mAP50-95, and inference time metrics. The results showed that the best model was obtained on YOLOv26 epoch 100 with a precision value of 0.92, recall of 0.847, mAP50 of 0.892, mAP50-95 of 0.741, and inference time of 3.0 ms. These findings indicate that the YOLOv26 model has good capabilities in detecting and classifying organic and inorganic waste accurately and quickly, so it has the potential to be used as a basis for developing a real-time waste detection system.
Clustering HIV Screening Data in Teluk Bintuni Using K-Means Yuliana Manobi; Alex De Kweldju; Julius Panda Putra Naibaho
J-INTECH ( Journal of Information and Technology) Vol 14 No 02 (2026): Journal of Information and Technology
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v14i02.2368

Abstract

Human Immunodeficiency Virus (HIV) remains a major public health challenge in Papua, Indonesia, where geographical barriers and limited resources complicate service delivery. This study applies clustering methods to HIV screening data from 22 Health Service Units (UPK) in Teluk Bintuni Regency during 2024–2025. The final dataset consisted of 29 valid unit-year observations containing variables related to total tests, HIV-positive cases, and sex-disaggregated distributions. Data preprocessing followed the Knowledge Discovery in Database (KDD) framework, including data selection, cleaning, log transformation, normalization, and the construction of derived variables such as positivity rate and gender ratios. Four clustering algorithms were compared, namely K-Means, Hierarchical Clustering, Fuzzy C-Means, and DBSCAN, using Silhouette Score, Davies-Bouldin Index, and Calinski-Harabasz Index. The results indicate that K-Means produced the most stable and interpretable clustering structure, forming three groups of UPKs: intermediate screening units with moderate coverage and low positivity, priority units with limited testing but high positivity rates, and active screening units with the highest testing volume and case detection. These findings reveal heterogeneity in HIV screening performance across UPKs and support differentiated intervention strategies. Units with high apparent positivity but low testing coverage require expanded outreach, field verification, and improved access to HIV screening services, while active screening units should be strengthened through counseling, referral, and follow-up services. This study demonstrates the usefulness of clustering analysis in identifying service gaps and supporting evidence-based HIV intervention planning at the local level.

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