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Jurnal Kecerdasan Buatan dan Teknologi Informasi
Published by CV. Ninety Media Publisher
ISSN : 29636191     EISSN : 29642922     DOI : https://doi.org/10.69916
Core Subject : Science,
Computer Science & IT
Jurnal Kecerdasan Buatan dan Teknologi Informasi or abbreviated JKBTI is a national journal published by the Ninety Media Publisher since 2022 with E-ISSN : 2964-2922 and P-ISSN : 2963-6191. JKBTI publishes articles on research results in the field of Artificial Intelligence and Information Technology. JKBTI is committed to becoming the best national journal by publishing quality articles in Indonesian and English and becoming the main reference for researchers. All submissions are blind and reviewed by peer reviewers. All papers can be submitted in BAHASA INDONESIA or ENGLISH. Scope : Neural Networks, Machine Learning, Deep Learning, Data Mining, Big Data, Decision-Making System, Information System, Mobile Application, Data Warehouses, Database, Internet of Thing, Expert System.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 79 Documents
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AUGMENTED REALITY AS AN INNOVATIVE LEARNING MEDIA FOR VERTEBRATE ANIMALS FOR ELEMENTARY SCHOOL STUDENTS Fikri Akbar Syah Putra Nasution; Imran Lubis
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 1 (2026): January 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i1.388

Abstract

The learning of vertebrate animals in elementary schools often faces challenges due to the limited availability of interactive media, resulting in reduced understanding and low student motivation. This study aims to design and implement an Augmented Reality (AR) application as an innovative learning medium capable of displaying 3D models of vertebrate animals in an interactive and realistic manner. The application was developed using Unity 3D and Vuforia SDK, with key features including AR Camera, Materials, Guide, Download Marker, and About. The learning materials cover various vertebrate categories such as fish, frogs, birds, lions, and elephants, with detailed information on their characteristics, behaviors, and classification. User testing demonstrated that the application runs smoothly on Android devices and successfully increases student engagement, motivation, and understanding of biological concepts. The integration of AR technology allows students to visualize animals directly in three-dimensional space, providing a more immersive and enjoyable learning experience compared to conventional methods. Additionally, the application overcomes the limitations of physical models or field visits, offering accessible and flexible learning within the classroom. The results indicate that AR can serve as an effective educational tool, enhancing both the quality and interactivity of biology learning. This study contributes to the development of technology-based learning methods in elementary education and demonstrates the potential of AR to improve students’ cognitive and perceptual understanding of vertebrate animals.
INTELLIGENT CHATBOT FOR ENHANCING ACADEMIC CONSULTATION SERVICES IN VOCATIONAL SCHOOLS USING NATURAL LANGUAGE PROCESSING Yolanda Estefania Hasibuan; Ahmad Zakir
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 1 (2026): January 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i1.389

Abstract

Academic consultation is essential in supporting students’ learning, personal development, and career planning in vocational schools. Traditional consultation services, however, often face challenges such as limited advisor availability, time constraints, and inefficient record-keeping, which reduce service effectiveness and accessibility. This study proposes the development of an intelligent chatbot to enhance academic consultation services at Vocational High School (SMK) Multi Karya using Natural Language Processing (NLP). The chatbot serves as a virtual assistant capable of understanding students’ queries in natural language, providing real-time guidance, and recording consultation history for further analysis. The system integrates modules for user authentication, account management, class and subject management, schedule organization, consultation history, and interactive chat. Evaluation results demonstrate that the chatbot improves accessibility by enabling students to consult anytime, enhances efficiency through automation of administrative tasks, and delivers context-aware, personalized responses. Interaction logs allow administrators to monitor and evaluate service quality, facilitating data-driven improvements. Despite limitations in handling ambiguous or complex queries, and the need to address ethical considerations such as data privacy and algorithmic bias, the chatbot represents a practical and innovative solution for modernizing academic consultation in vocational education. This study highlights the potential of AI-driven chatbots to provide inclusive, responsive, and effective student support, establishing a foundation for future advancements in educational technology and intelligent learning systems.
A RECURRENT NEURAL NETWORK–BASED SENTIMENT ANALYSIS OF MOBILE LEGENDS APP REVIEWS Naufal Ilmi Rangkuti; Imran Lubis
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 1 (2026): January 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i1.390

Abstract

With the rapid growth of mobile applications, user reviews have become a valuable source of feedback for developers. This study investigates the use of a Recurrent Neural Network (RNN) for sentiment analysis of Mobile Legends user reviews. The textual data were preprocessed through cleaning, tokenization, and padding, while sentiment scores were converted into categorical labels. A Sequential RNN model, consisting of an Embedding layer, a SimpleRNN layer, and a Dense output layer with softmax activation, was constructed to classify reviews into three sentiment categories: negative, neutral, and positive. During training, the model achieved approximately 75% accuracy, and the Mean Squared Error (MSE) was 0.1354. However, evaluation using the classification report and confusion matrix revealed that the model was biased toward the negative class due to class imbalance, failing to correctly classify neutral and positive reviews. The high overall accuracy was misleading, as the model’s performance was limited by the dominance of the negative class. These results highlight the limitations of using a simple RNN architecture for multi-class sentiment classification in imbalanced datasets. To improve performance, future work should consider balancing the dataset through resampling or synthetic data generation and employing more advanced sequential models, such as LSTM or GRU, possibly combined with attention mechanisms or pretrained language models, to better capture the characteristics of all sentiment classes.
IMPLEMENTATION OF THE WATERSHED METHOD FOR SEGMENTING PADANG TRADITIONAL CUISINE IMAGES TO IMPROVE CULINARY OBJECT RECOGNITION ACCURACY Akbar Adam Pratama; Ilham Faisal
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 1 (2026): January 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i1.391

Abstract

This study examines the implementation of the Watershed method for segmenting images of traditional Padang cuisine with the aim of improving culinary object recognition accuracy. Padang dishes possess complex visual characteristics, where multiple food components such as rice, side dishes, chili sauce, and vegetables are presented on a single plate. These elements often overlap and exhibit similar colors and textures, making image segmentation challenging when using conventional methods. Therefore, the Watershed algorithm was selected due to its ability to separate objects based on intensity variations and object contours, even when boundaries are unclear or blurred. The research process begins with image data collection from a publicly available Kaggle dataset containing various Padang food images. The preprocessing stage includes RGB to grayscale conversion, Gaussian blur filtering, and histogram equalization to enhance image quality and reduce noise. Subsequently, thresholding is applied to produce binary images, followed by distance transform to identify object cores. Marker determination is then performed to distinguish foreground and background regions, which serve as the basis for the Watershed segmentation process. The Watershed algorithm operates by simulating water flooding from predefined markers until meeting points form object boundaries. Experimental results show that the method can generate clear separation lines between food objects in visually complex scenes. However, quantitative evaluation reveals that the segmented foreground area remains relatively small, indicating that further optimization is required. Overall, the Watershed method demonstrates potential for handling overlapping objects and unclear boundaries, and can serve as a foundation for future culinary image analysis systems.
IMPLEMENTATION OF THE ARIMA ALGORITHM FOR ENHANCING AND FORECASTING COMPANY REVENUE Nanang Prayugo; Ilham Faisal
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 1 (2026): January 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i1.392

Abstract

In an increasingly competitive business environment, accurate revenue forecasting is crucial for strategic decision-making. This study implements the ARIMA (AutoRegressive Integrated Moving Average) model to predict the monthly revenue of CV. Yusindo Mega Persada using historical data from January to December 2024. The ARIMA(1,1,1) model was selected based on stationarity tests and analysis of Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) plots. Diagnostic tests confirmed that the model met key assumptions, including normality of residuals and absence of significant autocorrelation, ensuring reliable predictions. The forecasting results for January to March 2025 indicated a relatively stable revenue trend, with values ranging from IDR 483 million to IDR 489 million. Model accuracy was evaluated using the Mean Absolute Percentage Error (MAPE), which resulted in 9.41%, suggesting reasonable predictive performance. The findings demonstrate that ARIMA is capable of capturing trends and fluctuations in dynamic revenue data, providing actionable insights for management in financial planning, resource allocation, and risk mitigation. Despite the model’s effectiveness, external factors such as market fluctuations and seasonal events may influence actual revenue, indicating the need to combine quantitative forecasts with expert judgment. Overall, this study confirms that the ARIMA(1,1,1) model is a practical and reliable tool for revenue forecasting in a dynamic business environment.
DIGITAL TRANSFORMATION OF LOGISTICS MANAGEMENT THROUGH A WEB-BASED BARCODE-INTEGRATED SHIPMENT INFORMATION SYSTEM Nadila Muliana; Edy Rahman Syahputra
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 1 (2026): January 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i1.393

Abstract

This study aims to design and implement a web-based shipment information system integrated with barcode technology to improve the efficiency and accuracy of goods delivery management at PT. Anugerah Fajar. The existing shipment management process relied heavily on manual recording methods, which resulted in data entry errors, delays in updating shipment status, and limited visibility of goods in transit. To address these issues, a barcode-based information system was developed to automate shipment identification, tracking, and reporting processes. The system was developed using the Rapid Application Development (RAD) methodology, which emphasizes iterative development and active user involvement. Data were collected through direct observation, interviews with administrative and field personnel, documentation analysis, and literature review. The proposed system includes core features such as user authentication, shipment data management, barcode scanning using one-dimensional (1D) barcodes, real-time shipment status updates, report generation, and system configuration. The results show that the implemented system successfully improves operational efficiency by reducing manual data entry and minimizing human errors in shipment recording. Real-time barcode scanning enables faster and more accurate shipment status updates, enhancing transparency and control throughout the distribution process. Additionally, the dashboard and reporting features support effective monitoring, documentation, and managerial decision-making. The findings indicate that integrating barcode technology into a web-based shipment information system provides a practical and scalable solution for modern logistics management. This research contributes to the field of information systems by demonstrating the effectiveness of barcode-based digital solutions in improving logistics operations within distribution companies.
WEB-BASED CHURCH WORSHIP SERVICE INFORMATION SYSTEM USING THE SPIRAL MODEL: A CASE STUDY OF GKPI AIR BERSIH Wijaya Sipahutar; Fahrul Rozi Lubis
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 1 (2026): January 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i1.394

Abstract

The church as a religious institution requires effective management to support worship activities, congregation administration, and financial accountability in complex organizational and technological environments today. At GKPI Air Bersih Church, manual recording practices cause data inaccuracies, reporting delays, limited information access, and difficulties in monitoring congregation finances across sectors effectively. This study aims to design and implement a web-based church worship service management information system using the Spiral development model for integrated digital administration. The research employs a system development methodology involving requirement analysis, iterative design, implementation, evaluation, and continuous user feedback throughout multiple development cycles within the church environment. Data were collected through observation, interviews, and document analysis to identify operational needs, workflow limitations, and technical risks within the church context during system planning. The developed system integrates congregation management, worship scheduling, church bulletins, financial transactions, reporting, user management, and website configuration modules into a single centralized web platform. System evaluation using user acceptance testing indicates improved administrative efficiency, higher data accuracy, and increased transparency compared to manual processes previously used by church administrators. Real-time dashboards, automated calculations, and reporting features support informed decision-making, strengthen accountability, and enhance service quality for administrators and congregation stakeholders effectively overall. The application of the Spiral model enables adaptive development, risk mitigation, usability improvement, and alignment between system functionality and user requirements through iterative evaluation cycles. This research demonstrates the effectiveness of web-based information systems in supporting digital transformation within religious institutions and community organizations with limited technical resources available.
INVENTORY FORECASTING INFORMATION SYSTEM USING THE WEIGHTED MOVING AVERAGE METHOD AT TITA'S STORE Amuharnis; Iswandi; Rahmi, Lidya; Adriyendi
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 1 (2026): January 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i1.419

Abstract

Inventory management is a crucial factor in retail operations as it influences cost efficiency, sales continuity, and customer satisfaction. In small-scale retail businesses, inventory planning is often performed manually, increasing the risk of overstock and stockout conditions. This study aims to develop a web-based inventory forecasting information system using the Weighted Moving Average (WMA) method to support effective inventory planning. The system integrates item data management, sales transaction recording, and demand forecasting within a single platform. The WMA method is applied to 12 months of historical monthly sales data using a three-period forecasting window with an optimized weight configuration of 5–1–7 to emphasize recent demand patterns. Forecasting accuracy is evaluated using Mean Absolute Deviation (MAD), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE). A case study conducted at Toko Tita shows that the WMA method outperforms the Simple Moving Average method by producing lower MAD and MAPE values, indicating better responsiveness to short-term demand fluctuations. The results demonstrate that the proposed system provides reliable quantitative information to support inventory procurement decisions, reduces manual calculation errors, and improves operational efficiency. Although forecasting errors increase during extreme demand changes, the system is practical and effective for daily inventory management in small retail businesses.
A SECURE DIGITAL TRADING PLATFORM FOR ONLINE GAME ACCOUNTS USING DUAL AUTHENTICATION AND SMART PAYMENT INTEGRATION Nurkholis, Lalu Moh.; Sudirman, San; Maspaeni; Said, Muhammad
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 1 (2026): January 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i1.422

Abstract

The rapid growth of online gaming has increased the economic value of game accounts, leading to the emergence of online game account trading. However, most transactions are still conducted through informal channels, such as social media and online forums, which lack security, transparency, and reliable transaction records. This study aims to design and implement a web-based information system for online game account buying and selling by integrating OTP-based dual authentication and a payment gateway to improve security and transaction efficiency. The system was developed using the Waterfall method, consisting of requirement analysis, system design, implementation, testing, and maintenance stages. UML diagrams and an Entity Relationship Diagram were used to model system functionality and database structure. The system was implemented using PHP and MySQL and supports key features such as user management, game account management, secure login with OTP, transaction processing, payment gateway integration, reviews, and complaints. Black-box testing results indicate that all system functions operate according to the defined requirements. The implementation of OTP-based authentication improves access security by reducing the risk of unauthorized account use, while payment gateway integration ensures accurate and automated payment verification. The system also enhances transaction transparency through digital transaction records and purchase history. The results show that the proposed system provides a secure, efficient, and practical solution for online game account trading in a local business environment, supporting digital transformation and service professionalism for small-scale enterprises.

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