cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Bahtiar Imran
Contact Email
bahtiarimranlombok@gmail.com
Phone
+6285337626083
Journal Mail Official
bahtiarimranlombok@gmail.com
Editorial Address
Perumahan Green Asia Blok I2-04, Kecamatan Labuapi, Kabupaten Lombok Barat Nusa Tenggara Barat, Indonesia
Location
Kab. lombok barat,
Nusa tenggara barat
INDONESIA
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 126 Documents
 9   10   11   12   13 
XGBOOST-BASED FRAUD TRANSACTION CLASSIFICATION ANALYSIS IN ONLINE PAYMENT SYSTEMS Sri Diantika; Hiya Nalatissifa; Riki Supriyadi; Nurlaelatul Maulidah; Ahmad Fauzi
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 2 (2026): May 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i2.478

Abstract

The rapid development of online payment systems has significantly facilitated digital transactions; however, it has simultaneously increased the risk of fraudulent activities. Fraud detection has become a critical challenge due to the complex characteristics of transaction data and the imbalanced class distribution between legitimate and fraudulent transactions. This study aims to analyze the performance of the XGBoost algorithm in classifying fraudulent transactions within online payment systems. The research employs the Online Payments Fraud Detection Dataset obtained from the Kaggle platform. The research methodology consists of several stages, including dataset collection, data preprocessing, categorical data transformation using label encoding, feature engineering for the generation of new attributes, data partitioning through split validation with an 80:20 ratio, model development using the XGBoost algorithm, and performance evaluation using a confusion matrix, accuracy, precision, recall, F1-score, and Area Under the Curve (AUC). The experimental results demonstrate that the XGBoost model achieves excellent classification performance, with an accuracy of 99.98%, precision of 85%, recall of 100%, F1-score of 92%, and an AUC value of 0.9996. Furthermore, feature importance analysis reveals that errorOrig and newbalanceOrig are the most influential attributes in detecting fraudulent transactions. Based on these findings, it can be concluded that the XGBoost algorithm is highly effective for fraud transaction classification in online payment systems and exhibits strong potential for implementation in automated fraud detection systems to enhance the security of digital financial transactions.
DATA-DRIVEN CONSUMER SEGMENTATION APPROACH FOR JEANS RETAIL SALES USING FUZZY C-MEANS CLUSTERING Nana Suarna; Nining Rahaningsih; Annisa Annastia Suarna
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 2 (2026): May 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i2.479

Abstract

The fashion retail industry generates large volumes of sales transaction data containing valuable information regarding consumer purchasing behavior and preferences. However, extracting meaningful insights from heterogeneous retail data remains challenging when using conventional analytical approaches. This study aims to analyze jeans sales transaction data and identify consumer purchasing patterns using the Fuzzy C-Means (FCM) clustering algorithm. The proposed approach adopts the Knowledge Discovery in Databases (KDD) framework, consisting of data selection, preprocessing, transformation, data mining, and evaluation stages to ensure systematic analysis. The dataset used in this study consists of 799 jeans sales transaction records collected in 2024 from Shakila Collection, involving four attributes: product name, payment method, price, and purchase quantity. To improve clustering effectiveness, only price and purchase quantity were selected as the primary variables due to their relevance in representing consumer purchasing behavior. Clustering performance was evaluated using the Davies-Bouldin Index (DBI) to determine the optimal number of clusters. Experimental results show that the best clustering configuration was achieved at , producing three consumer segments consisting of 175 items in Cluster 0, 590 items in Cluster 1, and 34 items in Cluster 2. The findings indicate that medium-priced products tend to have higher purchasing intensity and more flexible purchase quantities, whereas premium-priced products exhibit relatively lower demand. The novelty of this study lies in integrating Fuzzy C-Means clustering with consumer preference analysis to generate practical business insights for pricing strategies, inventory optimization, and targeted marketing, thereby supporting more effective data-driven decision-making in fashion retail businesses.
CONSTITUTIONAL ACCOUNTABILITY OF THE GOVERNMENT FOR MACHINE LEARNING-BASED SYSTEM ERRORS IN DIGITAL PUBLIC SERVICES Wiredarme
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 3 No. 3 (2024): September 2024
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v3i3.480

Abstract

This study examines the constitutional accountability of the government for machine learning-based system errors in Indonesia’s digital public services. The objective is to analyze how state responsibility should be formulated when digital systems misread data, reject applications, delay access, produce inaccurate classifications, or incorrectly process citizens’ rights. This research applies a qualitative legal method with normative-juridical, conceptual, and socio-legal approaches. The analysis is based on constitutional norms, public service law, government administration law, personal data protection law, electronic-based government regulations, and recent scholarly debates on automated decision-making and public-sector AI governance. The findings show that machine learning-based errors cannot be treated as ordinary technical failures when they affect citizens’ access to public services. Such errors must be understood as failures of public authority because the system operates within the institutional responsibility of the state. Indonesia already has legal foundations for public service, administrative responsibility, digital government, and personal data protection, but it lacks a specific accountability framework for machine learning-based public service errors. This study proposes the concept of state constitutional responsibility for governmental technology failure, consisting of preventive, explanatory, corrective, institutional, and remedial accountability. The contribution of this study lies in framing machine learning errors in public services as constitutional accountability issues, not merely as technical, administrative, or contractual problems.
CONSTITUTIONAL IMPLICATIONS OF THE USE OF MACHINE LEARNING IN INDONESIA’S SOCIAL ASSISTANCE SELECTION AND DISTRIBUTION SYSTEM Erfan Wahyudi; Wiredarme
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 2 No. 3 (2023): September 2023
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v2i3.481

Abstract

This study examines the constitutional implications of using machine learning in Indonesia’s social assistance selection and distribution system. The main objective is to analyze how algorithmic decision-making may affect citizens’ constitutional rights to social security, welfare, equality before the law, legal certainty, and protection from discrimination. This research applies a qualitative legal method with normative-juridical and socio-legal approaches. The analysis is based on constitutional provisions, statutory regulations, social welfare data governance, and policy documents related to Indonesia’s social assistance system, particularly DTKS and SIKS-NG. The findings show that machine learning may improve targeting accuracy and administrative efficiency in social assistance distribution. At the same time, it may reproduce or intensify existing problems in welfare data, especially when the system relies on incomplete, outdated, biased, or unevenly collected information. Algorithmic discrimination may occur indirectly through proxy variables such as residence, housing condition, employment status, digital access, and household composition. This study argues that machine learning should be positioned only as a decision-support tool, not as an autonomous decision-maker. Its constitutional legitimacy depends on data quality, explainability, meaningful human oversight, contestability, independent audit, and clear institutional accountability. The contribution of this study lies in framing machine learning-based social assistance as a constitutional issue, not merely as a technical matter of prediction accuracy or administrative efficiency.
STATE DIGITAL SOVEREIGNTY IN THE GOVERNANCE OF ARTIFICIAL INTELLIGENCE WITHIN INDONESIA’S GOVERNMENT SYSTEM Wiredarme
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 2 No. 3 (2023): September 2023
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v2i3.482

Abstract

This study examines state digital sovereignty in the governance of artificial intelligence within Indonesia’s government system. The main objective is to analyze how the state can maintain effective control over AI infrastructure, public-sector data, and government AI systems while preserving constitutional democracy, citizens’ rights, and public accountability. This research applies a qualitative legal method with normative-juridical, conceptual, and socio-legal approaches. The analysis is based on constitutional principles, statutory regulations, policy documents, and recent scholarly debates on AI governance, digital sovereignty, data sovereignty, and public-sector digital transformation. The findings show that Indonesia has developed important foundations for digital government through the Electronic-Based Government System, One Data Indonesia, the Personal Data Protection Law, and the National Strategy for Artificial Intelligence 2020–2045. Yet these instruments have not fully established a comprehensive framework for sovereign AI governance. The main risks include infrastructure dependency, weak control over public-sector data, vendor dominance, limited algorithmic accountability, and unclear responsibility for AI-based administrative decisions. This study argues that state digital sovereignty in AI governance requires strategic infrastructure control, public-sector data sovereignty, algorithmic accountability, meaningful human authority, and democratic oversight. The contribution of this study lies in framing AI governance not merely as a matter of technological innovation or administrative efficiency, but as a constitutional issue concerning the state’s capacity to govern digital power in the public interest.
THE APPLICATION OF ARTIFICIAL INTELLIGENCE IN ELECTION SUPERVISION: BETWEEN DIGITAL EFFECTIVENESS AND THE PROTECTION OF CITIZENS’ POLITICAL RIGHTS Erfan Wahyudi; Wiredarme
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 3 No. 3 (2024): September 2024
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v3i3.483

Abstract

This study examines the application of artificial intelligence in Indonesian election supervision, focusing on the balance between digital effectiveness and the protection of citizens’ political rights. The objective is to analyze how AI can support the monitoring of electoral violations, hoaxes, deepfakes, digital campaigns, and voter-data risks without weakening democratic principles. This research applies a qualitative legal method with normative-juridical, conceptual, and socio-legal approaches. The analysis is based on constitutional principles, election law, campaign regulations, personal data protection law, election supervisory regulations, and recent scholarly debates on AI, disinformation, deepfakes, and electoral integrity. The findings show that AI may strengthen election supervision by improving the speed, scale, and accuracy of digital monitoring. Yet AI may also create constitutional risks, including wrongful content classification, suppression of legitimate political expression, unequal enforcement, excessive surveillance, privacy violations, and wrongful voter-data profiling. This study argues that AI-based election supervision is constitutionally legitimate only when it is governed by legality, proportionality, transparency, accountability, and meaningful human oversight. The contribution of this study lies in framing AI in election supervision as a constitutional issue concerning political rights, democratic accountability, and electoral integrity, rather than merely as a technological tool for detecting violations.
INVESTIGATING COMMUNITY READINESS THROUGH IT INFRASTRUCTURE, ONLINE TRANSACTIONS, AND COMMUNITY BEHAVIOR FOR URBAN VILLAGE DIGITAL TRANSFORMATION IN PALEMBANG Berliana Inasti; Darius Antoni; Agustina Heryati
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 2 (2026): May 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i2.484

Abstract

The rapid development of information technology has encouraged digital transformation in various sectors, including public administrative services at the urban village level. However, the successful implementation of digital transformation depends not only on government readiness and technological infrastructure but also on the readiness of the community as the primary users of digital services. This study aims to evaluate community readiness toward digital transformation and design a web-based digital administrative service architecture for Sukamaju Urban Village, Palembang City, using the TOGAF ADM framework. The study employed a descriptive quantitative approach involving 395 respondents selected using the Slovin formula with a 5% margin of error. Data were collected through closed-ended questionnaires based on a 5-point Likert scale and analyzed using the E-Readiness approach through three main variables: Information Technology Infrastructure, Online Transactions, and Community Behavior. The results indicate that the Information Technology Infrastructure variable achieved the highest mean score of 4.32 (Very Ready), followed by Community Behavior with a mean score of 4.20 (Ready), and Online Transactions with a mean score of 4.11 (Ready). These findings suggest that the Sukamaju Urban Village community possesses a high level of readiness to support digital transformation in administrative services. Based on these findings, a web-based digital administrative service architecture was proposed using TOGAF ADM phases, including Architecture Vision, Business Architecture, Information Systems Architecture, and Technology Architecture. The proposed system is expected to improve service efficiency, reduce manual administrative processes, and support sustainable digital transformation at the urban village level.
DESIGN OF A PRELOVED MARKETPLACE WEBSITE APPLICATION FOR UNIVERSITY STUDENTS Alfi Mahgfiro; Avissya Febrian; Riski Tri Maulana; Nurlaila Syafitri; M. Reddy Syahputra; Frimus Susanto Elianda; Miftahul Jannah
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 2 (2026): May 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i2.489

Abstract

The rapid development of information and communication technology has significantly influenced commercial activities, including buying and selling transactions conducted through digital platforms. Among university students, the increasing demand for affordable products has encouraged the growth of preloved or second-hand goods trading. However, existing general marketplace platforms do not specifically accommodate the needs of university students in conducting preloved transactions within campus environments, resulting in inefficiencies in product searching, limited transaction relevance, and concerns regarding security and trust. This study aims to design a website-based Preloved Marketplace application specifically intended for university students to facilitate secure, efficient, and affordable buying and selling activities for second-hand usable goods. The research employed a qualitative approach through observation, interviews, surveys, literature review, and system requirement analysis. The design process included problem identification, UI/UX design using Figma, prototype implementation, and system evaluation. The developed application provides various features, including user registration, login, product listings, product search and filtering, shopping cart, checkout, payment confirmation, live chat, sales reports, and dashboard monitoring. Black Box Testing was conducted to evaluate system functionality based on user input and output behavior. The testing results indicate that all system features operated successfully according to expected requirements, demonstrating functional consistency and usability. The developed platform is expected to support university students in selling unused but still usable products while helping other students obtain affordable necessities. Therefore, the proposed Preloved Marketplace has strong potential to improve transaction efficiency, support sustainable consumption, and encourage digital transformation within campus communities.
USER INTERFACE DESIGN OF E-COMMERCE WEBSITES FOR MICRO, SMALL, AND MEDIUM ENTERPRISES (MSMEs) IN THE CULINARY INDUSTRY Malisa Putri; M. Bagastya Rasyid; Jihan Salsabila; Muhammad Riski Saputra; Syahrul Isyam; Oki Wibowo; Miftahul Jannah
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 2 (2026): May 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i2.490

Abstract

Micro, Small, and Medium Enterprises (MSMEs) in the culinary sector play a strategic role in supporting economic growth, increasing employment opportunities, and strengthening local economies. However, many culinary MSMEs still experience challenges in adopting digital technology, including limited digital literacy, inadequate technological infrastructure, and manual sales and transaction management. These limitations hinder market expansion and reduce operational efficiency, making digital transformation increasingly necessary. This study aims to design a responsive and user-friendly user interface for a web-based e-commerce platform specifically intended for culinary MSMEs. The research method involved requirement analysis through observation, literature review, user needs identification, product data collection, order workflow analysis, and transaction management analysis. The interface design process was carried out using Figma to develop a prototype representing the overall system workflow, including customer and administrator interactions. The resulting design includes several key features such as the home page, login and registration page, product menu, payment system, order history, best seller recommendations, contact information, and logout functionality, as well as administrative features for product and transaction management. Black Box Testing was conducted to evaluate the functionality of each feature and ensure compliance with system requirements. The testing results demonstrated that all system functionalities operated successfully and consistently according to expected outcomes. The developed interface design is expected to support culinary MSMEs in improving digital marketing activities, simplifying transaction management, and increasing operational efficiency. Therefore, the proposed web-based e-commerce interface has strong potential to support the digital transformation and sustainability of culinary MSMEs in Indonesia.
CONSTITUTIONAL LIMITS ON GOVERNMENT USE OF FACIAL RECOGNITION TECHNOLOGY IN PUBLIC SERVICES AND PUBLIC SECURITY Wiredarme
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 4 No. 3 (2025): September 2025
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v4i3.491

Abstract

This study aims to examine the constitutional limits of government use of facial recognition technology in public services, public security, and citizen identification. The central issue addressed in this article is the tension between state interests in security and administrative efficiency on the one hand, and the protection of privacy, civil liberties, equality, due process, and constitutional rights on the other. This study employs a qualitative legal research method with a normative-doctrinal approach. The analysis is conducted through statutory, conceptual, and comparative approaches by examining constitutional principles, legal norms, regulatory frameworks, human rights standards, and recent academic literature on facial recognition, biometric governance, digital identity, and public-sector surveillance. The findings show that facial recognition is not merely a technical instrument, but a form of constitutional state action because it enables the government to collect, process, store, and act upon citizens’ biometric identity. In public services, the technology may improve verification and administrative efficiency, but it may also create forced consent and exclusion from essential services. In public security, facial recognition may support lawful identification, but it may also enable mass surveillance, chilling effects, discriminatory outcomes, and unchallengeable decisions. This study contributes a constitutional boundary framework based on legality, legitimate aim, necessity, proportionality, transparency, accountability, non-discrimination, meaningful human review, and effective remedy. The study implies that facial recognition may only be constitutionally justified when technological capability remains subject to strict rights-based legal control.

Page 12 of 13 | Total Record : 126

 9   10   11   12   13 

Filter by Year

2022 2026


Reset
Filter By Issues
All Issue Vol. 5 No. 2 (2026): May 2026 Vol. 5 No. 1 (2026): January 2026 Vol. 4 No. 3 (2025): September 2025 Vol. 4 No. 2 (2025): May 2025 Vol. 4 No. 1 (2025): January 2025 Vol. 3 No. 3 (2024): September 2024 Vol. 3 No. 2 (2024): May 2024 Vol. 3 No. 1 (2024): January 2024 Vol. 2 No. 3 (2023): September 2023 Vol. 2 No. 2 (2023): May 2023 Vol. 2 No. 1 (2023): January 2023 Vol. 1 No. 3 (2022): Desember 2022 More Issue