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Journal of Artificial Intelligence and Engineering Applications (JAIEA)
Published by Yayasan Kita Menulis
ISSN : -     EISSN : 28084519     DOI : https://doi.org/10.53842/jaiea.v1i1
Core Subject : Science, Engineering,
Automotive Engineering Computer Science & IT Control & Systems Engineering
The Journal of Artificial Intelligence and Engineering Applications (JAIEA) is a peer-reviewed journal. The JAIEA welcomes papers on broad aspects of Artificial Intelligence and Engineering which is an always hot topic to study, but not limited to, cognition and AI applications, engineering applications, mechatronic engineering, medical engineering, chemical engineering, civil engineering, industrial engineering, energy engineering, manufacturing engineering, mechanical engineering, applied sciences, AI and Human Sciences, AI and education, AI and robotics, automated reasoning and inference, case-based reasoning, computer vision, constraint processing, heuristic search, machine learning, multi-agent systems, and natural language processing. Publications in this journal produce reports that can solve problems based on intelligence, which can be proven to be more effective.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 524 Documents
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Influencing the Success of SPBE Jambi Provincial Government Using the SEM Method Chandy Ophelia S; Lola Yorita Astri
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2321

Abstract

The Electronic-Based Government System (SPBE) is a strategic instrument for digital governance in Indonesia, but its success in local government remains uneven. The problem addressed in this study is the fluctuating SPBE performance of the Jambi Provincial Government, which is associated with network instability, changing application coordinators, overlapping data input, diverse user age groups, and uneven digital literacy among state civil apparatus (ASN) and service users. This study aims to identify the determinants of SPBE success from the ASN perspective and to explain how system quality and information quality shape perceived ease of use, perceived usefulness, user satisfaction, and net benefits. A quantitative explanatory survey was conducted with 385 ASN respondents who interact with SPBE services in the Jambi Provincial Government. The research model integrates constructs from technology acceptance and information system success perspectives and was tested using partial least squares structural equation modeling. The measurement results show that all indicators are valid, with outer loading values above 0.70, AVE values above 0.50, and Cronbach alpha values above 0.80. The structural results indicate that information quality has the strongest effect on perceived usefulness (beta = 0.861), followed by user satisfaction on net benefits (beta = 0.844) and system quality on perceived ease of use (beta = 0.834). Perceived usefulness also has a stronger effect on user satisfaction than perceived ease of use. These findings confirm that SPBE success in Jambi depends primarily on accurate, complete, timely, and relevant information that creates real work benefits and sustained user satisfaction.
Sentiment Analysis of SPayLater and SPinjam Features in the Shopee Application Using the Support Vector Machine (SVM) Algorithm Rahmad Rahmad Nawi Pane; Wilda Wilda Rina Hasibuan
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2322

Abstract

The rapid development of information technology and the increasing use of e-commerce applications have generated a large number of user reviews that can be used to measure user satisfaction. SPayLater and SPinjam, as features in the Shopee application, receive various responses in the form of positive, negative, and neutral sentiments, making automatic sentiment analysis necessary. This study aims to analyze user sentiment and implement the Support Vector Machine (SVM) algorithm to classify reviews. The data used consist of 500 user reviews obtained from the Google Play Store. The method includes preprocessing, labeling, and classification using SVM. The results show that there are 231 positive, 230 negative, and 39 neutral sentiments. Model evaluation yields an accuracy of 74%, precision of 0.78, and recall of 0.84, indicating that the model performs fairly well. The developed system is also capable of processing data automatically and displaying classification results effectively. Therefore, the SVM algorithm is effective for sentiment analysis of SPayLater and SPinjam services in the Shopee application.
Analysis of Green Computing Implementation Strategies for Energy Efficiency in Server Infrastructure Daniel Rionaldo; Alvin Leonardo Ishak
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2325

Abstract

The rapid development of information technology has increased the use of server infrastructure in various organizations and data centers, resulting in higher energy consumption and operational costs. Green computing is considered an effective approach to improve energy efficiency while reducing environmental impacts. This study aims to analyze green computing implementation strategies for improving energy efficiency in server infrastructure. The research used a descriptive qualitative method through literature studies and comparative analysis of energy management strategies in data centers. The strategies analyzed include server virtualization, server consolidation, energy-efficient hardware, and cooling system optimization. The results indicate that the implementation of green computing can significantly reduce energy consumption compared to conventional server systems. In addition, the implementation improves operational efficiency, reduces electricity usage, and supports environmentally sustainable data center management. Therefore, green computing can be considered an effective solution for developing efficient and environmentally friendly server infrastructure.
Implementation of Random Forest Algorithm for Classifying Land and Building Tax Arrears and Risk Factor Analysis Dashboard Risky Firmansyah Manik; A M H Pardede; Anton Sihombing
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2326

Abstract

This study aims to develop a predictive model to identify the potential for land and building tax arrears and analyze the dominant risk factors contributing to non-compliance. The research utilizes the Random Forest classification algorithm applied to historical tax data from the Regional Financial and Revenue Management Agency of Binjai City. The approach involves data preprocessing, feature engineering including target encoding for geographical areas, and model training with hyperparameter tuning to optimize classification performance. Furthermore, a web-based interactive dashboard is developed using the Flask framework to visualize the predictions and risk factors. The results demonstrate that the Random Forest model achieves a robust and consistent accuracy of approximately 85% in classifying compliant and non-compliant taxpayers. Feature importance analysis reveals that land area is the most dominant risk factor influencing tax arrears, significantly outweighing other variables. In conclusion, the integration of the Random Forest algorithm with an interactive dashboard provides a highly accurate, efficient, and scalable solution for local governments to transition from reactive tax collection to proactive, data-driven risk management.
Design of a Multi-Tenant Waste Management System with Volume Estimation and Vehicle Trip Optimazation Intan Nur Sifa; Aulia Hamdi; Purnia Setiawati; Aulia Suryaning Tyas; Rizki Cahya Putri; Mayza Nurul Khasanatun Nisa; Sri Rahayu; Lina Nur Afifah
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2327

Abstract

Waste management at the village level still faces a number of challenges, such as unstructured waste volume recording, suboptimal collection scheduling, and a lack of transparency in cost management. This study aims to design a multi-user waste management system equipped with a volume estimation model and vehicle route optimization. The approach applied includes a literature review to analyze system requirements, followed by design using flowcharts, Data Flow Diagrams (DFDs), and Entity-Relationship Diagrams (ERDs). The research findings indicate that the developed system successfully integrates the management of waste source data, transportation processes, and cost calculations in a structured manner. The volume estimation model is used to estimate the amount of waste in the field, while route optimization determines the number of vehicle trips based on their carrying capacity. Additionally, the multi-tenant concept allows this system to be used by various regions simultaneously while ensuring data separation. Therefore, this system is expected to improve operational efficiency, management transparency, and the quality of waste transportation services.
Application of Data Mining using the Apriori Algorithm in Analyzing Subject Selection Patterns of Tutoring Students Rizky Ferdiansyah; Naufal renanda; Afriza Akhid Khoiruddin; Arya Subastian; Muhammad Arifin
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2328

Abstract

This study examines the application of data mining using the Apriori algorithm to analyze subject selection patterns among tutoring students in Kudus, Central Java. With the increasing number of students attending tutoring, understanding subject selection patterns is crucial to improve the effectiveness of educational services. The Apriori algorithm, a popular association rule mining technique, is used to identify relationships between frequently selected subjects. The research dataset consists of student subject selection transaction data, including information such as student name, student ID number, tutoring branch, and selected subjects. The analysis process included data preprocessing, data transformation into transaction format using Transaction Encoder, application of the Apriori algorithm with a minimum support of 0.05, and formation of association rules with a minimum confidence of 0.3. The results show frequent itemsets indicating the most popular subjects and association rules that describe students tendencies in selecting subject combinations. These findings can be utilized by tutoring managers to design more effective learning packages, optimize the allocation of teaching resources, and provide subject recommendations tailored to student needs. This research contributes to the development of educational data mining in the context of tutoring institutions in Indonesia.
Comparative Analysis of K-Means Clustering and K-Medoids Clustering Methods in Clustering Neonatal Infant Mortality Rates in West Java Province Intan Putri Septiyani
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2329

Abstract

Neonatal mortality rate is an important indicator in assessing public health conditions. This study aims to cluster neonatal mortality data in West Java Province using the K-Means Clustering and K-Medoids Clustering methods, as well as compare the performance of both methods in producing the best clusters. The study used secondary data obtained from Open Data West Java. The research stages included data selection, preprocessing, clustering, and evaluation using the Davies-Bouldin Index (DBI). The experiments were conducted using cluster variations (k) from 2 to 8. The results showed that the K-Means Clustering method produced the best performance with a DBI value of 0.430 at k = 3. The clustering results generated three categories: low-risk cluster with 408 data points, medium-risk cluster with 65 data points, and high-risk cluster with 13 data points. The differences in cluster characteristics indicate variations in neonatal mortality risk levels among regions in West Java Province. The findings of this study are expected to support decision-making and more targeted health policy planning.   Keywords: K-Means Clustering, K-Medoids Clustering, Davies-Bouldin Index, Neonatal Mortality.
Analysis and Design of the Nusa Graha Module for Village Asset Management and Facility Booking on the NUSAEKA Multi-Tenant SaaS Platform Purnia Setiawati; Azhari Shouni Barkah; Rizki Cahya Putri; Intan Nur Sifa; Aulia Suryaning Tyas; Mayza Nurul Khasanatun Nisa; Sri Rahayu; Lina Nur Afifah
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2331

Abstract

In most regions of Indonesia, village asset management and the process of booking village facilities are still carried out manually, which can lead to disorganized record-keeping, data loss, and a lack of access for village residents. This study was conducted to analyze and evaluate the Nusa Graha module as a component of the Nusaeka multi-tenant SaaS platform, focusing on village inventory management, automatic asset depreciation, and web-based village booking services. This research was conductes through a literature review and system analysis obtained through consultation with supervising lecturer as well as document analysis. The analysis results include business flowcharts, Data Flow Diagrams (DFDs) at levels 0 and 1, and Entity-Relationship Diagrams (ERDs), which consist of several main tables. The research findings indicate that the Nusa Graha module can support and streamline asset management and the structured process of facility rentals using multi-tenant data via tenant_id and a modular language. Additionally, the Nusa Graha module facilitates integration with the Nusa Artha financial module if the village subscribes to it.
Customers’ Loss of Confidence in Banking Security Systems: A Case Study of the Loss of BRI Customers’ Funds Aisyah Safitri; Sitti Nur Aini; Moh. Ali Fajar Sidiq; Achmarul Fajar
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2333

Abstract

The phenomenon of customer funds going missing in the banking sector, particularly in the case of Bank Rakyat Indonesia (BRI), has raised concerns about the security of the digital banking system and has led to a decline in public confidence. This study aims to analyse the crisis of customer confidence in banking security systems by examining influencing factors, such as cyber risk, risk perception, and the role of social media. The research method employed is a qualitative approach using case studies, utilising secondary data obtained from academic journals, institutional reports, and case documentation.The research findings indicate that the loss of customer funds is influenced by vulnerabilities in digital security systems and the rise in cybercrime, such as phishing and social engineering. Furthermore, these incidents have led to a decline in customer trust, a trend exacerbated by the dissemination of information via social media. This study concludes that the crisis of customer trust is caused not only by technical factors, but also by risk perceptions and the dynamics of public information. Therefore, improvements in banking system security, strengthened consumer protection, and effective communication strategies are required to maintain customer trust.
Design of a Web Based Population Data Information System at Matawai Atu Village Office Jesika Prince Piri; Arini Aha Pekuwali
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2334

Abstract

The development of information technology has greatly influenced many sectors, including village administration. The Matawai Atu Village Office, located in Umalulu Subdistrict, East Sumba Regency, still uses a manual system to record population data such as births, deaths, new residents, and relocations. Data is recorded in a main register book and then processed using Microsoft Word to create reports. This method causes several problems, including the risk of data loss, data entry errors, slow data searching, and delays in report preparation. To solve these problems, this study aims to design a web-based population data information system that is effective and efficient. The study uses the Waterfall method, which includes the stages of requirements analysis, system design, implementation, testing, and maintenance. The system is developed using PHP and a MySQL database. Data collection is carried out through interviews, direct observation at the research location, and literature study. System testing is conducted using Black Box Testing to ensure that all features work properly, and the System Usability Scale (SUS) to measure how easy the system is for users. The results show that the developed system can manage population data more accurately, quickly, and securely. The system also makes it easier for staff to search data, manage documents, and prepare reports. With this system, it is expected that public services at the Matawai Atu Village Office will improve and better support the work of village staff.

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