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International Journal of Artificial Intelligence Research
Published by STMIK Dharma Wacana
ISSN : -     EISSN : 25797298     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal Of Artificial Intelligence Research (IJAIR) is a peer-reviewed open-access journal. The journal invites scientists and engineers throughout the world to exchange and disseminate theoretical and practice-oriented topics of Artificial intelligent Research which covers four (4) majors areas of research that includes 1) Machine Learning and Soft Computing, 2) Data Mining & Big Data Analytics, 3) Computer Vision and Pattern Recognition, and 4) Automated reasoning. Submitted papers must be written in English for initial review stage by editors and further review process by minimum two international reviewers.
Arjuna Subject : -
Articles 625 Documents
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Data-Driven Insights Into Underdeveloped Regencies: SHAP-Based Explainable Artificial Intelligence Approach Oktora, Siskarossa Ika; Matualage, Dariani; Notodiputro, Khairil Anwar; Sartono, Bagus
International Journal of Artificial Intelligence Research Vol 9, No 1 (2025): June
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v9i1.1399

Abstract

Classification analysis in high-dimensional data presents significant challenges, particularly due to the presence of complex non-linear patterns that traditional methods, such as logistic regression, fail to capture effectively. This limitation is often reflected in relatively low model accuracy. One approach to addressing this issue is through machine learning-based classification methods, such as Random Forest and Support Vector Machine (SVM). While these models generally achieve higher accuracy than logistic regression, their black-box nature limits interpretability, making it difficult to explain their classification decisions. As machine learning models continue to advance, interpretability has become a crucial concern, especially in data-driven decision-making. Post-hoc explainable artificial intelligence (XAI) techniques offer a viable solution to enhance model transparency. This study applies SHAP to machine learning models to gain insights into the underdevelopment status of regencies in Indonesia. The results indicate that SVM outperforms both logistic regression and Random Forest. SHAP values estimated from SVM, using various permuted variable subsets, exhibit stability. Clustering analysis identifies five optimal clusters of underdeveloped regencies. Based on average SHAP values, underdevelopment alleviation strategies should focus on social factors (Cluster 1), infrastructure (Cluster 2), accessibility (Cluster 3), and a combination of infrastructure, accessibility, education, and healthcare (Cluster 4), while Cluster 5 requires improvements in accessibility and economic conditions.
Development of Eco-Charger with Solar Power in Airport Soleh, Asep Muhamad; Handayani, Ni Putu Heni
International Journal of Artificial Intelligence Research Vol 9, No 1.1 (2025)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v9i1.1.1461

Abstract

Renewable Alternative Energy is a very important issue due to global climate issues. In the 2021 United Nations General Assembly, the President of the Republic of Indonesia, in his speech, supported the development of renewable energy and stopped the development that uses coal as an energy source. Airports, as one of the infrastructures that use very large amounts of electrical energy, currently rely heavily on electrical energy, which still uses coal as fuel. The research method used is research and development (R&D), which has been carried out at the Politeknik Penerbangan Palembang since August 2021. The research we conducted produced an eco-charger with solar power as a power source and a battery as a medium for storing electrical energy controlled by a solar charge controller module. This research involved cadets in the development process so it also supports project-based learning. This eco charger's power source can be used for twenty-four hours non-stop because the source of electrical energy is stored in the battery. During the day, the battery will be charged with electrical energy from the solar panel and automatically stop charging if the battery is full. This eco charger is used to charge mobile phones at airports and can also be used in other places such as bus stops, bus terminals, and train stations.
Understanding Gen-Z Work Ethic and Leadership Management in the Digital Age Rahmawati, Devie; Anindhita, Wiratri; Lumakto, Giri; Viendyasari, Mila; Wisesa, Rangga
International Journal of Artificial Intelligence Research Vol 9, No 1.1 (2025)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v8i1.1.1315

Abstract

This research examines serious challenges faced by the modernprofessional environment. The phenomena discussed include a lack ofwork ethics, limited appreciation for work, and insufficient professionalexperience among Gen Z workers, as well as leadership managementchallenges among Gen Y leaders. This study employs an ethnographicapproach, involving direct observation and participation at PT X andNGO Y to analyze these phenomena. The findings indicate that Gen Zworkers exhibit minimal work ethics and professionalism, lowappreciation for their jobs, and reduced motivation and commitment. Toaddress these challenges, this research recommends strengthening softskills education programs, developing detailed professionalismguidelines, enhancing administrative systems, and fostering an inclusivework culture. Implementing these recommendations is expected toincrease organizational productivity and create a harmonious multigenerationalworkplace. This research aims to contribute to a deeperunderstanding of multi-generational dynamics and offer practicalstrategies for effectively managing Gen Z talent
The Influence of Product Design through (Online Customer Review) on Purchase Decisions at Korean Beauty Shop on the Shopee Platform DS, Yudha Mahrom; Herudiansyah, Gumar; Sary, Maretha Puspita
International Journal of Artificial Intelligence Research Vol 8, No 1.1 (2024)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v8i1.1.1336

Abstract

The purpose of this research is to analyze Korean Beauty Shop's Shopee evaluations in order to draw conclusions about the impact of product design on consumers' final purchasing decisions. One hundred participants were chosen for this study using a purposive sampling method that does not rely on randomness. Numerous linear regressions are employed in the analysis. Research shows that Korean Beauty Shop's product design (as evaluated by online reviews) has a substantial impact on Shopee shoppers' decisions to buy Korean Beauty Shop products. A determination coefficient value of 65.4% indicates that product design (in the form of online customer evaluations) can influence changes in purchase decisions
Evaluation of VGG16 Performance in Multi-Input and Multi-Class Classification of Toraja Buffalo Breeds Manga’, Abdul Rachman; Nanda, As'syahrin; Salim, Yulita
International Journal of Artificial Intelligence Research Vol 8, No 1.1 (2024)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v8i1.1.1203

Abstract

Traditional image classification research has focused on single-input and multiclass approaches. However, these approaches often fail to capture the complexity and diversity of real-world image data. To address the complexity and more diverse variation in data, as well as to improve the classification accuracy of various categories, a multi-input image approach is utilized. With a multi-input multi-class approach, a Transfer Learning model based on VGG16 is trained to identify objects from various perspectives and classify them into one of many predefined classes. The VGG16 architecture in the multi-input and multi-class classification of Toraja Buffalo breeds demonstrates excellent results with an average accuracy of 93.33%. The "Kerbau Lotong Boko" and "Kerbau Bonga Ulu" classes achieved 100% accuracy, while other classes showed high precision, recall, and F1 scores. Despite fluctuations in accuracy and loss during training, the model successfully achieved good convergence and generalization. This research is significant in the field of image classification by introducing a multi-input method capable of capturing richer and more diverse information from complex objects such as Toraja buffalo. It demonstrates that CNN architectures like VGG16 can be adapted to handle more complex classification tasks using a multi-input approach.
Determining Quality of Service (QoS) of End-User Internet Networks with Data Sniffing and Classification Algorithms Rosyidin, Zulkham Umar; Muladi, Muladi; Handayani, Anik Nur
International Journal of Artificial Intelligence Research Vol 9, No 1 (2025): June
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v9i1.1444

Abstract

The development of telecommunications technology in this world has changed very rapidly. Changes are made to access technology using the transmission media, which uses fiber optic technology, which has the advantage of being free from interference, large and fast data delivery capacity. An Internet Service Provider (ISP) is a provider of construction services and management of network infrastructure that always meets customer needs. Customer satisfaction with the services provided by ISP is also important in the era of increasingly tight market competition. Quality of Service (QoS) testing in internet networks needs to be done so that customers get optimal service. This study analyzes the quality of internet networks with fiber optic media on the end user side with the data sniffing method using Wireshark software that records video data traffic on the YouTube platform. The results of the data recording are processed using the QoS method with Throughput, Packet Loss, Delay, and Jitter parameters. The QoS assessment index is divided into Excellent, Good, Fair, and Poor classes according to the TIPHON standard. Data from these parameters is classified using the Naive Bayes, KNN, and Decision Tree methods. The results of applying the algorithms show the highest Accuracy value in the Decision Tree algorithm of 97%, while the highest Precision and Recall are in the KNN algorithm with values of 94% and 85%.
Research on the Application of Artificial Intelligence in Hand Rehabilitation by Estimating Hand Grip Force using EMG Data Nguyen, Tien Manh; Takagi, Motoki; Nguyen, Trung Thanh; Tran, Hieu Huy; Dao, Khanh Viet Trong
International Journal of Artificial Intelligence Research Vol 9, No 1 (2025): June
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v9i1.1381

Abstract

The human hand is a complex and functionally significant anatomical structure, playing a critical role in daily activities, communication, and professional tasks. Any impairment due to injury, neurological disorders, or musculoskeletal diseases can severely affect an individual's quality of life. Conditions such as stroke-induced hemiparesis, arthritis, carpal tunnel syndrome, and tendon injuries often necessitate rehabilitation to restore function, minimize pain, and prevent secondary complications. Traditional rehabilitation approaches, while beneficial, generally follow a standardized methodology, failing to account for individual variations in muscle strength, neuroplasticity, and adaptive capacity.Modern rehabilitation methods leverage advanced technologies such as electromyography (EMG) and hand grip force measurement to enhance therapy effectiveness. Additionally, artificial intelligence (AI) applications, particularly Long Short-Term Memory (LSTM) networks and Transformer models, have emerged as promising tools for personalized rehabilitation. These models analyze EMG signals to predict hand movement intentions, enabling adaptive rehabilitation strategies tailored to individual needs.  This study focuses on the construction of a real-time EMG signal acquisition system and uses them as input to LSTM and Transformer models to compare and analyze the performance of the two types of models. By demonstrating the superiority of applying AI for personalization over the general AI approach, this study highlights the potential of AI in hand rehabilitation in particular and healthcare in general with its ability to specialize for each individual patient.
Internet of Things (IoT) Platform Using Web Services-Based The Laravel Framework in Wind Turbines Yunior, Yudhis Thiro Kabul
International Journal of Artificial Intelligence Research Vol 9, No 1.1 (2025)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v9i1.1.1468

Abstract

The increasing need for sustainable electrical energy has driven the development of various renewable energy sources, one of which is wind power plants (wind turbines). The development of the Internet of Things (IoT) is a solution for monitoring and managing wind power plants remotely, in real time so that it is more efficient and centralized. The integration method on the Internet of Things (IoT) platform is to build a sensor system installed on the wind turbine output so that it can send operational data in real time. The background of this study will design and implement a power monitoring system on a wind turbine using an Internet of Things-based web service platform. The development of an Internet of Things-based power monitoring system on web services will be built using the Laravel framework which will be integrated with the power output of the wind power plant. This platform is expected to simplify the process of monitoring, controlling, and analyzing wind turbine performance in real time, so that it can increase operational efficiency and support the development of sustainable renewable energy. 
Facing The Modern Era By Developing Digital Technology Innovation For Sustainable Green Tourism Sari, Novita; Desfiandi, Andi; Santi, Faurani I; Saputra, Muhammad
International Journal of Artificial Intelligence Research Vol 9, No 1.1 (2025)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v9i1.1.1440

Abstract

Sustainable green tourism development is one of the priorities in supporting economic growth while preserving the environment. This study discusses the development of digital technology innovation in facing the modern era to support sustainable green tourism. In an increasingly digitalized global context, the tourism sector must adapt to technology to improve operational efficiency and minimize negative impacts on the environment. This study uses a qualitative approach by analyzing cases of technology implementation in various environmentally friendly tourist destinations in Indonesia. The results of the study show that the use of technology such as IoT-based management systems, digital promotions, and real-time data analytics contribute significantly to reducing carbon footprints and energy efficiency. However, challenges such as lack of digital infrastructure and limited technological literacy still need to be overcome. This study offers important insights for stakeholders to formulate innovative strategies that integrate technology to create sustainable and environmentally friendly tourism.
THE INFLUENCE OF BUDGET SYSTEM ACCOUNTABILITY AND ACCOUNTANCY PROFESIONAL TO EVALUATION OF BUDGET GOVERNANCE Dewi, Kurnia Sari
International Journal of Artificial Intelligence Research Vol 9, No 1.1 (2025)
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v9i1.1.1485

Abstract

In the rapidly changing uncertain and dynamic environment characterized by limited resources, the global economic crisis imposed a new attitude to budgetary control and made it one of the leading functions of management. The management function "control" invariably includes evaluation as an element of feedback. In this regard, a number of authors consider the procedure for evaluating the implementation of budgets by the centers of responsibilities in the budget control process. The purpose of this publication is to identify some basic problems in enterprise valuation related to budgetary control, which are known in the Indonesian  scientific literature. The article reviews the Indonesian  scientific literature indexed in the Google Scholar scientific database until the end of July 2023. The study was conducted in three stages, including developing the search protocol, conducting the search, and reporting the results. Methodologically, a systematic approach was applied, based on eleven scientific publications in Bulgarian, which correspond to the research problem under study. As a result of the review, problems were identified in the assessment of the enterprise's budgetary control process. Some authors bring to the fore as a problem the ineffective internal control in business organizations, presupposed by the lack of a good level of availability of information. To solve it, a modern toolkit is applied, which enables the evaluation and successful management of internal risk. In the conditions of the global economic crisis, the authors most often recommend the concepts and approaches of "assessing achievements in budgetary control", BSC(Balanced Scorecards) and controlling as particularly attractive and successful. These concepts and approaches imply qualitatively new requirements for the necessary information. Another major estimation problem in the budgetary control process is accounting for the interrelationships between variances. Also, most authors do not discuss the managerial issues related to the methodology for evaluating responsibility centers. In the conclusion, recommendations for future research on the topic are given. In the opinion of the author, the results of this scientific development can be useful for making informed decisions in the field of internal control. Despite the theoretical nature of the study, it can be used by both researchers and management practice

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