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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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Participation in Tourism Village Development In Turgak Village Subdistrict Belalau West Lampung Asmaria Asmaria; Rini Setiawati; Arnila Rosimah Arnila Rosimah
International Journal of Artificial Intelligence Research Vol 7, No 1.1 (2023)
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i1.1.1184

Abstract

Lack of participant development tourism in Turgak Village, because That study This aim For study participation public in development of Turgak Village, with focus make village the as destination tour. Study This use design qualitative with method interviews and observations , meanwhile data analysis using technique interactive. Research result showing that participation public in development of Turgak Village increasingly low. Next, factors the barrier including deficiencies understanding about potential of tourist villages, reluctance a number of inhabitant For participation, and the lack of it innovation in development object tour. Although has There is effort self-help and mutual cooperation development, still required follow carry on from government local For increase more participation and management Good. Therefore that's important participation public in development of Tourism Villages recognized as key success.
Assessing Performance Across Various Machine Learning Algorithms with Integrated Feature Selection for Fetal Heart Classification Amanda, Laura Rizka; Anasanti, Mila Desi
International Journal of Artificial Intelligence Research Vol 8, No 1 (2024): June 2024
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v8i1.1110

Abstract

The global concern over declining perinatal death rates, particularly in low- and middle-income nations, underscores the importance of adopting Cardiotocography (CTG) as a vital fetal monitoring method. Recent strides in machine learning (ML) present promising opportunities to enhance the accuracy of assessing fetal health, providing a viable alternative to traditional approaches. This study aims to evaluate various ML methodologies and feature selection techniques for predicting fetal health using CTG data. The primary objective is to improve ML algorithms' accuracy, precision, recall, and F1 score while selecting the most critical features. The dataset includes 2,126 expectant mothers in the third trimester, with 35 variables related to fetal heart rate (FHR) and uterine contractions (UC). Preprocessing involves feature scaling, data balancing, and outlier elimination. Additionally, a 10-fold stratified cross-validation approach is employed to ensure robust evaluation and generalizability of the model's performance. Six ML algorithms—Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), Naive Bayes (NB), Logistic Regression (LR), and K-Nearest Neighbors (KNN)—are employed, optimized through grid search cross-validation. The RF algorithm outperforms with an impressive 99% accuracy, closely followed by DT at 98.7%. Optimizing 15 features from the original 35 using Simultaneous Perturbation Feature Selection and Ranking (spFSR) yields a remarkable accuracy of 99%, mirroring the full feature set. This underscores the vital role of selected features in improving predictive power and overall model performance. The study emphasizes the efficacy of tree-based classification algorithms, especially RF, in predicting fetal health and highlights the impact of preprocessing on model performance. These findings suggest avenues for future research, including exploring alternative feature engineering methods and assessing algorithm performance in diverse scenarios.
The Influence Of Transformational Leadership And Secretary Support On Employee Organizational Commitment Through Mediation: Psychological Empowerment And Moderation: Structural Distance On Bintan Regency In The New Normal Era Rahmawati, Putri; Indrayani, Indrayani; Kaddafi, Muamar
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.v8i1.1.1205

Abstract

Organizational commitment is very important for organizations in order to improve organizational performance. Employee organizational commitment can increase or decrease. Knowing the factors that influence organizational commitment is the key to solving the problem of decreasing employee organizational commitment. This research aims to determine the influence of transformational leadership and Secretary support on employee organizational commitment through empowering psychologists as an intervening agent and structural distance as a moderating variable. Data was obtained by distributing questionnaires to 276 civil servants who worked at the Regional Apparatus Organization of Bintan Regency, Riau Islands Province. The research uses a quantitative approach. The data analysis method used is a structural equation model using the Smart-PLS device. The research results show, 1) Transformational leadership and support from the Secretary directly have a positive and significant effect on psychological empowerment. 2) Transformational leadership and psychological empowerment directly have a positive and significant effect on Organizational Commitment, while 3) Secretary Support and Structural Distance do not have a significant effect on organizational commitment. 4) psychological empowerment fully mediates the influence of transformational leadership on organizational commitment, and also mediates the influence of Secretary support on organizational commitment. 5) Structural distance moderates the influence of transformational leadership on employee organizational commitment in the Bintan Regency Regional Apparatus Organization. And also moderates Psychological Empowerment of Organizational Commitment, but does not moderate Secretary Support for Organizational Commitment. The results of this research recommend that practitioners and leaders in the Bintan Regency Regional Apparatus Organization be able to improve transformational leadership competence in inspiring followers, and encourage the Secretary to accommodate opinions from subordinates, include subordinates in the planning process and increase employee organizational commitment.   
THE ROLE OF RETURN ON ASSETS AND DEBT TO EQUITY RATIOS AS A BASIS FOR DETERMINING STOCK RETURNS Albart, Nicko; purnomo, hadi
International Journal of Artificial Intelligence Research Vol 7, No 1.1 (2023)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i1.1.1046

Abstract

Financial ratios are relative and can provide a more in-depth view of the financial condition of a business entity. The study examines the effect of Return on assets (ROA) and Debt to Equity Ratio (DER) on Stock Returns in Food and Beverage Sub-Sector Manufacturing Companies listed on the Indonesia Stock Exchange. The population in this study were food and beverage sub-sector manufacturing companies listed on the IDX during the 2018-2022 period. Sampling was done by purposive sampling method with a sample of 11 companies. The type of data used is secondary data obtained from company financial reports and annual reports, which can be accessed through the official website of the Indonesia Stock Exchange (www.idx.co.id) or the official website of the company. The data analysis technique used is multiple linear regression. The results show that ROA has an effect on stock returns with coefficient of 0,64, meaning that if ROA increases by 1%, it will increase stock returns by 0.64%. Furthermore, DER has an affect on stock returns with coefficient of -0.057, meaning that if DER increases by 1%, it will decrease stock returns by 0.057% in Food and Beverage Sub-Sector Manufacturing Companies listed on the Indonesia Stock Exchange.
Machine Design and Development of CoreXY FDM 3D Printer for Learning Mustaqim, Ilmawan; Prianto, Eko; Husna, Amelia Fauziah; Pramono, Herlambang Sigit; Fattah, Husain Abdul
International Journal of Artificial Intelligence Research Vol 8, No 1 (2024): June 2024
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v8i1.1186

Abstract

This research aims to design and develop CoreXY FDM 3D Printer that can be optimized for learning purposes. By detailing aspects of design, hardware, and software, this research is expected to make a significant contribution in improving the quality of learning. Research using the Research and Development method, carried out based on the Machine Learning System Development model with stages in the form of Problem Understanding, Data Handling, Model Building, and Model Monitoring. The results showed that the lowest average depreciation value in the 3D printer developed was smaller than the 3D Printer machine from the previous study. The best print quality was produced in experiment number 3 where the print results were almost flat and smooth. So that the best print parameters are produced at a layer thickness of 0.1 mm and a print speed of 60 mm / minute. Blackbox Test results show that all components of the 3D printer machine have been able to function properly. The results of the user trial questionnaire showed that the average value of all aspects received a value of 3.55 from a range of values 1-4, indicating that this machine is very good to be used as a medium in the learning process. Comparison of FDM CoreXY 3D Print printing process time after development shows shorter print time than FDM CoreXY 3D Printer machine before development.
Automatic water level controlling and monitoring system using IoT application muliadi, muliadi; Isminarti, Isminarti
International Journal of Artificial Intelligence Research Vol 7, No 2 (2023): December 2023
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i1.1.1044

Abstract

Water tanks have recently been widely used in many applications in households or industry. It is essential to control the water level of a tank to regulate the filling process so that the tank does not overflow or empty without being noticed. This study aims to design an automatic water level control system using an IoT application to monitor and control processes. The sensor used in this study is a water level sensor, which detects the height of the water level. It works by the principle that the more water hitting the sensor, the smaller the resistance. The sensor can see whether the reservoir has reached a certain level or is complete. The sensor will inform the Wmos R1 board ESP8266 module to turn off the water pump engine and activate it again when the water level sensor reaches a certain level. The results show that the sensor worked correctly and accurately. When the water level sensor shows a whole height level in the filling process, which is 80% filled with water, the water level sensor will inform the Wmos R1 board ESP8266 module to change the relay to the OFF condition so that the water pump engine is also OFF. Upon detecting a specific height, when 50% of the tank has been filled with water, the pump engine restarts. The real-time ON/OFF status of the water pump monitoring the water using Telegram on a smartphone
Marketing Information Systems in the Context of Building WOM Marketing Through Service Quality, Institutional Image and Customer Satisfaction in Higher Education Yani, Tri Endang; Santoso, Aprih; Wibisono, Totok; Kuswardani, Diah Cori
International Journal of Artificial Intelligence Research Vol 7, No 1.1 (2023)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i1.1.1079

Abstract

This study aims to construct word of mouth (WOM) marketing through service quality, institutional image, and customer satisfaction as variables influencing higher education institutions. The utility of the research is to help universities create word of mouth to support the sustainability and competitiveness of higher education. The population of this study are still active students at Semarang University. The number of samples is 100 and the selection of the sample ofis a conscious selection based on the criterion of respondents who are studying at least in the 4th semester. The analysis technique used is multiple linear regression and trajectory analysis.The results of the study indicate that the quality of the service and the image of the facility have a partially positive effect on customer satisfaction. The journey analysis, on the other hand, shows that customer satisfaction can neither reflect the relationship between service quality and PTO nor the relationship between image and PTO
Employee Information System (SIP): The role of work motivation, communication and coordination in improving employee performance Silitonga, Witler Slamat Halomoan; Madiistriyatno, Harries
International Journal of Artificial Intelligence Research Vol 7, No 1.1 (2023)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i2.1036

Abstract

Employee Information System (SIP) is a system designed to manage information related to employees in an organisation or company. The main purpose of the Employee Information System is to assist in managing employee data efficiently and effectively. The aim of the study was to determine the effect of work motivation, communication and coordination partially on performance and to determine the effect of work motivation, communication and coordination simultaneously on the performance of employees of the Bekasi City Sharia Cooperative. The method used is data collection methods and data analysis methods using statistical calculations. The regression coefficient value of Work Motivation b1 = 0.137, has a tcount value of 1.237 and probability Sig = 0.223 ˃ 0.05, then the value of the regression coefficient of work motivation is said to be insignificant and can be interpreted that if work motivation increases by one unit, employee performance increases by 0.137 units assuming constant communication and coordination. Communication regression coefficient b2 = 0.314, has a t-count value of 2.362 and probability Sig = 0.023˃0.05, then the value of the communication regression coefficient is said to be insignificant and can be interpreted that if communication increases by one unit, employee performance increases by 0.314 units with assumption of constant work motivation and communication. The value of the coordination regression coefficient b3 = 0.387, has a t-count value of 3.147 and the probability Sig = 0.003 ˃ 0.05, then the value of the coordination regression coefficient is said to be significant and can be interpretednamely if coordination increases by one unit, employee performance increases by 0.387 units with the assumption constant work motivation and communication. This study contributes to work motivation, communication and coordination simultaneously on employee performance. The effect of work motivation, communication and coordination on performance simultaneously is shown by the results of the analysis, that the effect of work motivation, communication and coordination is shown by the value of the regression coefficient b1 = 0.137; b2 = 0.314; and b3 = 0.387. Significant value at the 5% test level because it has F count ˃ F table (16.184˃2.833) and sig ɑ (0.000˂0.05). The consequences of this study are limited to the research variables of work motivation, communication, coordination, and employee performance. In addition, the object of research is only within the scope of the Bekasi City Sharia Cooperative. 
The Distribution of Legal Research Topics on Artificial Intelligence: A Bibliometric Study Muhammad Asrul Maulana; Savira Aristi
International Journal of Artificial Intelligence Research Vol 8, No 2 (2024): December 2024
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v8i2.1237

Abstract

This study aims to determine the distribution of legal research topics related to Artificial Intelligence. This study uses the lens of an indexing institution, to find raw data on the research distribution. The method used is Bibliometric analysis. The results of the research found that this study showed the keywords (Co-Occurrence) were divided into 3 clusters which had a total of 49 topics. Based on the collaboration of authors (Co-Authorship) has 1 cluster which includes 194 authors. Out of a total of 385,943 search results for scientific work, the most prolific author is Wei Wang with 361 documents created by journal articles. Meanwhile, research with the keyword Artificial Intelligence experienced fluctuating developments and the most publications occurred in 2022 with a total of 42,483 publications.
Knowledge Graph Construction for Rice Pests and Diseases Furqon, Muhammad Ariful; Bukhori, Saiful
International Journal of Artificial Intelligence Research Vol 7, No 1 (2023): June 2023
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i1.1022

Abstract

The agricultural industry in Indonesia confronts the simultaneous task of augmenting food production to satisfy escalating demand while proficiently handling crop losses caused by pests and diseases.  This study introduces a novel approach that leverages knowledge graphs to transform traditional, expert-based knowledge into a dynamic and interconnected system for addressing these agricultural challenges. The study delineates constructing a comprehensive knowledge graph, commencing with data extraction with SPARQL queries, and progressing to ontology design, object property and datatype property specification, and instance generation. The resultant knowledge graph not only serves as an organized archive for pest and disease information but also gives a systematic framework for the integration, analysis, and decision-making of data in agriculture. This knowledge graph adds to the broader junction of data science and agriculture by improving the diagnosis, prevention, and control of rice diseases.

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