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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.
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Articles 64 Documents
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Search results for , issue "Vol 9, No 1.1 (2025)" : 64 Documents clear
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
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
AI-Driven Personalized Design: Adapting Building Interior Design Based on User Preferences Irwan, Dede
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.v9i1.1.1486

Abstract

The adoption of Artificial Intelligence (AI) increases efficiency in the design industry. However, the implementation of AI is not entirely received positively by designers. This study aims to explore the application of AI technology in personalizing building interior design based on user preferences. A qualitative approach was employed using the design thinking method. Data were collected through in-depth interviews with product and graphic designers and subsequently validated by experts in the field of AI. The results of this study indicate that the integration of AI in interior design based on user preferences can assist designers in generating more personalized, efficient, and client-specific design recommendations. AI has proven capable of processing both explicit and implicit preference data to predict optimal layouts, color selections, materials, and lighting. However, this study also found several significant challenges, such as inconsistent data quality, limitations of algorithms in understanding subjective and emotional aspects, and concerns regarding user data privacy. Nonetheless, the use of AI in interior design still offers great opportunities to create spaces that are more functional, innovative, and adaptive to the evolving lifestyles of their occupants.
The Comparison Organizational Theory and Organization Performance on The Process of Enriching Organizational Culture on The Implementation of The Principles Government Organizations In Indonesia Hartanto, Beni; Rahmat, Basuki
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.v9i1.1.1491

Abstract

The purpose of this study is to determine and analyze Comparison Organizational Theory and Organization Performance on The Process of Enriching Organizational Culture on The Implementation of The Principles  Government Organizations In Indonesia.. The research sample consisted of 104 State Civil Apparatus whose duties were related to those studied. The research method used is an explanatory survey approach to explain the relationship between variables through hypothesis testing in the field. Research that uses descriptive surveys and explanatory survey methods is carried out by collecting information from samples directly at the scene of the incident (empirical) through questionnaires with the aim of finding out the opinions of the samples regarding the research problem. And this research uses the Partial Least Squares Structural Equation Modeling analysis technique (PLS-SEM), to model many variables in research  Results and Discussion: To examine the influence of mediator variables, Partial Least Squares Structural Equation Modeling analysis technique (PLS-SEM),to estimate the causal relationship between variables (causal model) that has been determined previously based on the theory. Answering research questions requires correct statistical data processing. This is based on the results of hypothesis testing, the t-statistics results obtained were 3,287 and the significance results (pvalue) obtained were 0.000 (0.000<0.05), so Ho was rejected and Ha was accepted. The test results prove the Comparison Organizational Theory and Organization Performance on The Process of Enriching Organizational Culture This is based on the results of hypothesis testing, the t-statistics results obtained were 2.845 and the significance results (pvalue) obtained were 0.001 (0.001<0.05), so Ho was rejected and Ha was accepted. The test results the the Comparison Organizational Theory and Organization Performance on The Process of Enriching Organizational Culture
ANALYSIS OF PALM PRODUCTION FACTORS AND BIODIESEL PRODUCTION OPPORTUNITIES IN JAMBI PROVINCE Irmanelly, Irmanelly; Afrizal, Ardi
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.v9i1.1.1484

Abstract

Research using secondary data with a quantitative descriptive analysis method which aims to analyze the land area for oil palm commodities in Jambi Province with the finding of an average calculation result of 6.24%. The average number of oil palm commodity farmers is 5.01%. The average price of palm oil commodities is 4.98%. Then for 1 hectare of oil palm the average production amount is 2.03 tons with a production value of IDR 2,732 (million) per month. Then the average land area of oil palm farmers in Jambi Province is 4 hectares with an income of oil palm farmers of IDR 10,290 (million) per month. Then the biodiesel production is 1,644,885 kg on average year
The Influence of Organizational Culture, Self-Confidence, and Gender on Employee Performance with Employee Involvement as a Mediator Jamika, Dodik; Nurdin, 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.v9i1.1.1478

Abstract

This study investigates the impact of organizational culture, self-confidence, and gender on employee performance, with employee engagement serving as a mediating variable. The research employs a quantitative approach, collecting data through questionnaires distributed to employees of financing companies registered with the Financial Services Authority (OJK) in Purwakarta Regency, resulting in a sample of 257 respondents. Path analysis is used to examine the direct and indirect relationships between variables. The findings reveal that organizational culture has a significant positive impact on both employee performance and employee engagement. A robust organizational culture fosters a supportive work environment, enhancing motivation, a sense of community, and engagement through effective communication and shared positive values. Self-confidence also positively influences employee performance; however, it does not directly affect employee engagement, highlighting the role of other factors like organizational culture and workplace relationships. Gender positively impacts both performance and engagement, showcasing the benefits of diverse perspectives, collaboration, and inclusivity in the workplace. Furthermore, employee engagement significantly enhances employee performance, as emotionally and professionally engaged employees tend to perform at higher levels. As a mediating variable, employee engagement strengthens the influence of organizational culture, self-confidence, and gender on employee performance, underscoring the critical role of fostering diversity, motivation, and workplace support to drive better outcomes.
GLCM Texture Feature Selection for Alzheimer's Detection: A Combination of Statistical Tests, Decision Tree, and Random Forest Cindyawati, Cindyawati; Suryantari, Risti; Sulungbudi, Janto V.
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.v9i1.1.1509

Abstract

Alzheimer’s disease is a progressive neurodegenerative disorder that leads to a gradual decline in memory and cognitive function, most commonly affecting individuals over the age of 65. Early detection is essential to enable timely interventions, slow disease progression, and improve quality of life. This study aimed to identify the most dominant texture features from brain MRI images using the Gray Level Co-occurrence Matrix (GLCM) for feature extraction. The extracted features were analyzed through non-parametric statistical tests and machine learning algorithms, including Decision Tree and Random Forest, and validated with cross-validation procedures to ensure robustness. The findings revealed that contrast at 90° consistently emerged as the most significant feature, capturing vertical texture variations associated with brain atrophy, while correlation at 135° provided additional discriminatory power by representing disrupted pixel intensity relationships. In combination, these features enhanced the accuracy of classification models, outperforming other GLCM parameters. The results emphasize that careful selection of texture features improves both accuracy and stability in distinguishing between Alzheimer’s and non-Alzheimer’s brains. This study demonstrates that image-based machine learning frameworks can serve as reliable tools to support early detection of Alzheimer’s disease, offering valuable implications for clinical practice and guiding future research on efficient, non-invasive diagnostic approaches.

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