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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 621 Documents
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Melanoma Detection and Classification in Dermoscopic Images using resnet50 and Hair removal feature K P, Akshaya; Phalgunan, Prafulla
International Journal of Artificial Intelligence Research Vol 8, No 2 (2024): December 2024
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v8i2.1300

Abstract

Melanoma is the most common skin cancer, and it is increasing widely. Automatic skin lesion detection from dermoscopic images remains a challenging task. Many efforts have been dedicated to this challenge using various methods, but due to its poor robustness, it is not good for the analysis of melanoma skin lesions. Propose a method for skin lesion detection and classification tasks simultaneously to make sure feature learning is successful. The base of feature pyramid networks and region proposal networks is ResNet50, which is used here. The network learns features more quickly using a three-phase cooperative training technique. Before entering this model, the hairs from the images are removed
The Influence of Internal Control Systems and Financial Managers' Competence on Local Government Financial Report Quality with Internal Transparency as a Mediator Darmono, Darmono; Ramdiska, Rizki; Sappewali, Badriah; Perdana Kusuma Putra, Aditya Halim
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.v8i1.1.1384

Abstract

This research aims to develop a model for improving the financial quality of local governments through internal transparency with independent variables of the internal control sistem and the competence of financial officials. This type of research is an explanatory research with data sources using primary and secondary data. The primary data in this study includes the perception of financial management officials related to the internal control sistem, the competence of financial management officials, internal transparency, and the quality of local government financial reports. Secondary data includes the identity of the respondents obtained from the SKPD of the Berau Regency Regional Government and literature review as a reference for literature related to the research. The population of this study is the Regional Apparatus Work Unit (SKPD) of the Regional Government of Berau Regency with 46 SKPDs. The sampling method of this study uses a saturated sample technique (census) with each SKPD represented by 3 respondents so that the total sample is 138 respondents. The analysis technique of this study uses an alternative method of Structural Equational Modelling (SEM) using AMOS Software. The results of this study show that  the internal control sistem and the competence of financial management officials have a significant positive effect on internal transparency. The internal control sistem has a positive and significant effect on the quality of local government financial reports and the competence of financial management officials has a positive but not significant effect on the quality of local government financial statements. Internal transparency has a significant positive effect on the quality of local government financial statements. The internal control sistem and the competence of financial management officials on the quality of local government financial reports through internal transparency have an indirect and significant influence.
Association Rule Mining System in Analyzing The Use Pattern of Drugs by Using Apriori Herlina Latipa Sari; Ila Yati Beti
International Journal of Artificial Intelligence Research Vol 6, No 2 (2022): Desember 2022
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v6i2.1411

Abstract

Data mining is a process to support decision making in finding information patterns in the data. In this study, Association Rule Mining will be implemented as one of the data mining techniques to analyze data and assist data of scientists in compiling raw data, formulating it and recognizing various patterns through a priori algorithms. The method used in this study is the Cross Industry Standard Process for Data Mining (CRISP-DM) Method by analyzing drug use patterns in health centers. The results of the study shows that by using the apriori algorithm, it found patterns and rules of widely used drugs that will provide recommendations in supporting decision making by health centers to submit drug procurement so that they can improve the quality of health services and minimize the risk of shortages or excess drug supplies and help health centers in optimizing drug inventory management.  The results of the analysis using the apriori algorithm on the combination pattern of 2 itemsets produced 2 association rules for drug use, they are "If using Amoxicillin caplets 500 mg, then you will use paracetamol" with a confidence value of 80% and "If using Dexamethasone tablets 0.5 mg, then you will use Ascorbic Acid (Vit C) tablets 50 mg" with a confidence value of 100%.
OVERVIEW OF THE PLANNING DOCUMENT STRUCTURE AS A TOOL FOR LOCAL GOVERNMENT PERFORMANCE MEASUREMENT AND RISK MANAGEMENT Erafat, Yasiir; Lestari, Winda Rika
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.v8i1.1.1353

Abstract

Local governments have a noble role in providing direct services felt by the community regarding basic needs such as civil registration services for primary and secondary education, health care, etc. by paying attention to the synchronization of policies at the central and provincial government levels. To ensure the effectiveness of the execution of these functions, local governments should adopt a performance management and risk management approach as formulated in applicable laws and regulations to improve the quality of strategic management in line with the principles of good governance. Based on these matters, by taking into account the applicable laws and regulations and taking into account the span of control of local government organizations, it is very necessary to identify detailed activities and/or end products documented in the annual planning document, especially at the Regional Apparatus Organization (OPD) level, detailed activities and/or end products describe in detail the sub-activities and sub-activity indicators, the identification and documentation can improve the quality of the OPD annual planning document as a living document, because it is not only used as a basis for measuring performance, but also as an input in identifying and analyzing risks at the operational level in achieving performance objectives at the sub-activity level, and can be used as an input in ensuring the cascade preparation of performance agreements from both the strategic level and the operational level. The methodology of this research uses a descriptive qualitative approach focusing on the Statute Approach and the Conceptual Approach
STRATEGIC MODEL OF LEARNING IMPLEMENTATION OF MISSION-BASED MBKM, ACADEMIC LEADERSHIP, COLLABORATION, COMMITMENT, AND SUSTAINABILITY WITH THE INFLUENCE OF INFORMATION TECHNOLOGY IN HIGH SCHOOLS Dunan, Hendri; Sanusi, Anuar; AA, Iskandar; Hairani, Tuti
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.v9i1.1.1473

Abstract

This research aims to develop and analyze a strategy model for implementing MBKM learning, namely university mission, academic leadership, collaboration, commitment, and sustainability, as well as the impact of the use of information technology. The research results show that leadership and information technology variables are strategic variablesfor improving learning strategies. This is because the research results of these variables have a significant influence. Meanwhile, information technology variables are not effective as moderatorvariablesontherelationshipbetweencommitmentandlearningstrategiesbecause the research results have a weak and negative influence. Collaboration and commitment variables are appropriate variables for learning strategies. This collaboration variable has a positive and significant influence on learning strategies in the context of this research, meaning that collaboration plays an important role in influencing learning strategies. Commitment is a very important factor in influencing learning strategies. Learning strategy variableshaveasignificantpositiveinfluenceonsustainabilityinthiscasethroughlearning strategies, which have been proven to have a significant positive impact on sustainability however,itisimportanttocontinuetocarryoutfurtherresearchanddevelopmenttosupport sustainability efforts on an ongoing basis. The information technology variable has a significant influence as a moderator on the relationship between learning strategies and sustainability, meaning that the interaction between learning strategies and information technologyappearstohaveastrongandnegativeinfluenceonsustainability.Thekeyfactors are mission, academic leadership, collaboration, commitment, and sustainability, and it can help universities to more effectively adapt and implement MBKM policies to increase autonomy and flexibility in highereducation
Priority Strategy for Goat and Sheep Farming Development using IPA Sulistya, Danang Wicaksana; Asnawi, Yudha Hermawan; Saptono, Imam Teguh
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.v9i1.1.1426

Abstract

Designing a business model for sustainable goat and sheep  farming is one of the keys to increasing productivity and competitiveness of the livestock sector in Indonesia. This article examines the formulation of a business model based on upstream-downstream integration using the Importance Performance Analysis (IPA) tool to identify priorities that need more attention in the development of goat and sheep farming. The IPA matrix is used to evaluate important components based on the Grand Design for National Goat and Sheep Development 2045 and the Guidelines for the Implementation of the Goat and Sheep Corporation Development Program of the Directorate General of PKH, Ministry of Agriculture. The results of the analysis show that aspects of providing quality feed, strengthening cultivation management, and developing market communication and education are priority areas that need to be optimized. In addition, market demand analysis and logistics systems also need to be improved to support efficient and timely product distribution. Formulating a business model that integrates the entire agribusiness chain can increase efficiency, strengthen competitiveness, and support national food security.
Prediction Modeling of Capacity Factor of Rembang Coal-Fired Steam Power Plant Based on Machine Learning to Improve the Accuracy of Primary Energy Planning Perdana, Ery; Sulardjaka, Sulardjaka; Warsito, Budi
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.v9i1.1394

Abstract

The Rembang Coal-Fired Power Plant (PLTU Rembang), with a capacity of 2 x 315 MW, is a key power plant in Central Java, where fuel expenses represent the largest cost component. Accurate fuel procurement planning, which relies on projecting electricity sales, is essential to reduce these costs. This study develops and compares four machine learning-based Capacity Factor (CF) prediction models: random forest regression, support vector regression, multiple polynomial regression, and multiple linear regression. The independent variables are selected from internal and external sources using F-tests and t-tests. Among the four models, the multiple linear regression model demonstrated the smallest Mean Absolute Percentage Error (MAPE) of 7.83%. Using this model, the annual CF for PLTU Rembang in 2024-2026 is predicted to be between 82% and 84%, while the CF for February-June 2024 is expected to range from 87% to 91%. With a monthly CF prediction accuracy classified as very good (MAPE of 2.35%), these predictions are valuable for optimizing monthly fuel purchase allocations, considering initial fuel stock and target inventory age (17-30 Days of Plant Operation).
Optimizing Microstrip Antenna Miniaturization Using U-Slot and L-Slot Techniques for Enhanced L-Band Performance Harianto, Bambang Bagus; Suprapto, Yuyun; Pambudiyatno, Nyaris; Irfansyah, Ade
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.v9i1.1.1466

Abstract

Rapid advances in wireless communication systems have increased the demand for compact and efficient antennas. This study presents the design and analysis of miniature microstrip antennas intended for applications in L-band frequencies. The antenna structure is based on a rectangular patch with modifications in the form of U-shaped slot (MRDPU) and L- shaped slot (MRDPL) configurations that aim to reduce the size of the antenna without sacrificing performance. The proposed antenna operates in the frequency range of 1,064 GHz to 1,562 GHz, with significant improvements in return loss values, bandwidth, and overall efficiency. Comparative analysis shows that the design with U-shaped slots (MRDPU) provides better miniaturization and performance compared to L-shaped slot designs (MRDPL). The U- shaped slot design achieves a return loss of -11.15 dB at 1.064 GHz, while the L-shaped slot design has a return loss of -10.907 dB at 1.206 GHz. Both configurations offer an effective solution for L-band frequency applications. The study highlights the potential of slot-based modifications in achieving antenna miniaturization without sacrificing important performance parameters.
Evaluating the Impact of Ai-Generated Outputs on Student Assessment: Educator's Perspective Dolba, Sammy Q.; Inoncillo, Frederick A; Nunez, Jayrome L.
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.v9i1.1347

Abstract

This study investigates educators' perceptions of the impact of artificial intelligence (AI)-)-generated outputs on student assessment in the Philippine educational context. With the rapid integration of AI technologies in education, understanding how educators view these tools is crucial for effective implementation. A descriptive quantitative research design was employed, utilizing a structured survey distributed to a diverse group of 93 educators across various disciplines. The findings reveal a generally positive perception of AI's role in enhancing teaching practices, with a mean score of M = 3.42 indicating high perceived value. However, concerns regarding the reliability and fairness of AI-generated output were noted, with mean scores of M = 3.30 and M = 3.28, respectively. Additionally, educators expressed moderate confidence in using AI tools, reflected by a mean score of M = 3.24. Qualitative responses highlighted ethical considerations and the need for continuous professional development to equip teachers with the necessary skills to effectively integrate AI into their assessments. This research underscores the potential benefits and challenges associated with AI in education, emphasizing the importance of addressing educators' concerns to maximize the advantages of AI technologies in student learning outcomes.
The Influence Of Corporate Social Entrepreneurship (CSE) Program And Mentoring On Community Competence Through Community Development As An Intervening Variable In The Baduga Community In The Sports Sector Hilman, Ahmad Arief; Karunia, R Luki; Marwan, Jubery
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.v9i1.1.1475

Abstract

This  study  investigates   The Influence of corporate Social  Entrepreneurship (CSE) Program And Mentoring on Community Competence Through Community Develeopment as an Intervening variable in The Baduga Community In The Sports Sector Indonesia. The concept of Corporate Social Entrepreneurship (CSE) has a role in encouraging the improvement of the economic welfare of the community, such as through the provision of competition programs and training in improving skills. In addition, it can encourage sustainable social innovation, increase community involvement and empowerment, accelerate social and infrastructure development and improve the reputation and sustainability of the company. The place of implementation of the research was carried out in the Baduga Sumedang Community environment, Sumedang Regency, West Java Province, which received the benefits of the Corporate Social Entrepreneurship (CSE) program of PT RPN. This research is classified into the type of explanatory research, namely research that intends to test and explain the relationship between independent variables (exogenous variables) and dependent variables (endogenous variables) (Sugiono, 2016). This study uses a hypothesis testing research design (Hypotheses Testing). This design was chosen because it will empirically test the influence between research variables. The sampling technique with the purposive sampling method was used to collect samples from the community. This method was chosen because it requires the determination of certain criteria for the sample to be targeted when distributing the research questionnaire (Taherdoost, 2016). The Isaac and Michael formula is used to determine the number of samples in purposive sampling with a tolerance of 10% error. This formula is used to calculate the number of samples needed. Based on the calculation of the Isaac and Michael formula mentioned above, the sample used for this study was 270 people who answered the questionnaire. Multiple regression analysis is used by researchers who intend to predict how the condition (rise and fall) of the dependent variable (criterion), where two or more independent variables as predictor factors are manipulated (increased or decreased in value). Multiple regression analysis is used by researchers who intend to predict the condition (up and down) of the dependent variable (criterium), where two or more independent variables are manipulated predictor factors (increasing and decreasing their values).

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