Journal of Artificial Intelligence and Engineering Applications (JAIEA)
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.
Articles
128 Documents
<![CDATA[Cluster Analysis Based on McKinsey 7s Framework in Improving University Services ]]>
<![CDATA[Deny Jollyta]]>;
<![CDATA[Dwi Oktarina]]>;
<![CDATA[Gusrianty]]>;
<![CDATA[Renita Astri]]>;
<![CDATA[Lina Arliana Nur Kadim]]>;
<![CDATA[Ni Gusti Ayu Dasriani]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.53842/jaiea.v1i1.45
<![CDATA[The epidemic of Covid-19 has impacted all aspects of human life, including education. Academic and administrative services for academic community are suffering, as a result of the fact that not all universities are able to provide online services to help break the chain of Covid-19 distribution. This is due to a lack of human competencies to use technology and a lack of information technology resources, necessitating the development of new strategies by universities to address these flaws. The goal of this study is to develop a university service strategy based on McKinsey 7s cluster results on the part that is having issues based on questionnaire data. The questionnaire is organized on seven McKinsey elements. The Manhattan distance calculation and the K-Medoids algorithm results demonstrated that the structure, system, skill and staff are all part of elements that clustered in k=2 and has to be addressed in aiding services during the Covid-19 pandemic. The McKinsey 7s showed that universities service enhancements may be achieved by combining clustering techniques and McKinsey framework.]]>
<![CDATA[Classification Analysis of Student Ability in Learning Using Clustering Method at SMA Tunas Pelita ]]>
<![CDATA[Nurhayati]]>;
<![CDATA[Juliana Naftali Sitompul]]>;
<![CDATA[Tri Kartika Sari]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.53842/jaiea.v1i1.46
<![CDATA[This study aims to classify the assessment of the learning process at SMA Tunas Pelita Binjai T.A. 2018/2019 based on the average grade X, additional subjects applied technology, and student absenteeism classified using Matlab.The data is processed based on learning grouping as much as 2 clusters with different centroids, namely for cluster 1 the average value of even and odd semesters for class X (85.0), additional subjects of applied technology (86.3) and student attendance (2.4) and cluster 2 the average grades of odd-even semesters for class X (68.2), additional subjects of applied technology (70.3) and student attendance (2.4). In the final result, it can be seen that the grouping of learning at SMA Tunas Pelita Binjai with 100 data can be divided into 2 groups, namely group 1 with 62 data with an average value of odd and even semesters and high additional applied technology and student absenteeism. low grades are classified as students with good grades and group 2 as many as 38 data with an average value of odd, even semesters and low values of applied technology and high student absenteeism belonging to students who have poor grades.]]>
<![CDATA[Implementation of K-Means Clustering on High School Students Management ]]>
<![CDATA[Anggriani Dwi Kartina]]>;
<![CDATA[M. Safii]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.53842/jaiea.v1i1.47
<![CDATA[The quality of national education and teaching needs to be monitored continuously in every stage and step of educational activities. The monitoring is intended as an effort to control the quality of education and furthermore as a guarantee of the quality of education. Therefore, a method is needed to facilitate the grouping of high school student data. With the k-means clustering approach, the division of student groups can be done based on the national final exam scores. In this study, students were clustered using the K-Means algorithm. By using K-Means, it aims to facilitate the grouping of the highest and lowest Pemtangssiantar High School students. The result is a picture that shows the grouping of students based on national final exam scores.]]>
<![CDATA[Application of the C5.0 Algorithm to Determine the Level of Public Satisfaction with the E-KTP Recording Service at the Bandar Sub-District Office ]]>
<![CDATA[Dini Fadila Hardani]]>;
<![CDATA[Poningsih]]>;
<![CDATA[Yuegilion Pranayama Purba]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.53842/jaiea.v1i1.49
<![CDATA[Community satisfaction at the Bandar Sub-district Office is one of the most important things in assessing the level of e-KTP recording services provided by the agency to the community. The purpose of this study was to determine the quality of the e-KTP recording service at the Bandar Sub-district Office in terms of the Service Procedure, Time, Behavior and Facilities aspects of the Bandar sub-district community. At the Bandar Camat Office these four aspects have not been measured with certainty, so the agency finds it difficult to determine which aspects must be improved. The method used in this study is the C5.0 Algorithm, where the data source used is a questionnaire/questionnaire technique given to the people of Bandar sub-district. The research test process uses Rapid Miner software to create a decision tree. The results of the study obtained 12 rules for classifying the level of community satisfaction with e-KTP recording services. The C5.0 algorithm can be used in cases of community satisfaction with an accuracy rate of 100%. From these results, it is expected to improve the quality of service for the e-KTP recording of the Bandar Sub-District Office to be even better.]]>
<![CDATA[K-Medoids Algorithm Analysis in Grouping Students' Level of Understanding of Subjects ]]>
<![CDATA[Ehrlich F.T Butarbutar]]>;
<![CDATA[M. Safii]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.53842/jaiea.v1i1.50
<![CDATA[Analysis of the teaching and learning process needs to be done as feedback on the understanding of the material for students. One of the obstacles faced by schools is that there is no method of how this feedback can be done so that student achievement is uneven. Student achievement in subjects can be seen from the results of the scores on the report cards obtained by students after taking the final semester exam. Due to the uneven achievement of students, it is necessary to make a method so that feedback analysis can be carried out on the level of student understanding of the subject. Is data mining with clustering techniques using the K-Medoids algorithm. With this algorithm, students' understanding of subjects with high potential can be grouped with high brightness average results]]>
<![CDATA[Application of Nave Bayes Algorithm for Security Performance Evaluation at PT. Sei Mangke Nusantara 3 ]]>
<![CDATA[Fifin Handayani]]>;
<![CDATA[Rahmat W. Sembiring]]>;
<![CDATA[Saifullah]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.53842/jaiea.v1i1.51
<![CDATA[Security serves as a security guard in an agency. In carrying out his duties a security must have a balance and functions in achieving the needs of an agency itself. In the world of work at an agency, especially security, which plays a role in maintaining the security of the agency. In the current era of security, there are those who are not responsible for their duties, so that an agency does not feel comfortable with the security. The purpose of this study to evaluate the performance of security at PT. Sei Mangke Nusantara Tiga and to create a safe and orderly atmosphere. In this study, the researchers used a Data Mining technique using the Naïve Bayes algorithm. Sources of research data obtained from the provision of questionnaires or questionnaires to danton PT. Sei Mangke Nusantara Tiga. The variables of the research used are discipline, attendance, honesty, communication skills and responsibility. In this study, the alternative used as a sample is security at PT. Sei Mangke Nusantara Tiga. The number of data tested is 5 security with two classes. From the results of the calculation of the Naïve Bayes Algorithm, it is obtained that there are 3 classes of good security and 2 security classes that are not good. The results of this study found that the level of accuracy of 100.00%.]]>
<![CDATA[Implementation Data Mining of Employement Contract Exten-sion at Indosat Using Naïve Bayes ]]>
<![CDATA[Andini Fadila Sari]]>;
<![CDATA[M. Safii]]>;
<![CDATA[Dedi Suhendro]]>;
<![CDATA[Irfan Sudahri Damanik]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.53842/jaiea.v1i1.52
<![CDATA[Contract employees are company resources in carrying out oprasional activities for a certain time based on an agreement or contract. Every company that uses a work contrak system every year, there must be employees who are extended and not renewed. Employees will get additional contracts if they have good performance. In this case to determine whether an employee is extended or not extended his work contract, there is difficulty in determining it and requires a long time and process. Therefore, this research was conducted to help guarantee the extension of the employee’s work contract by classifier it into the labes “Eligble” and “Not Feasible” which has 4 variables for the process of employees who will be extended or not. The four variables are age, years of service, aspects of delay, achievement. In this study, the alternatives used as samples were employees at PT. Indosat Ooredoo. The number of data tested is 5 employees with two classes. From the results of the calculation of the Naïve Bayes Algorithm, it is obtained classification with 3 employees eligible class and 2 employees not eligible class. The results of this study found that the level of accuracy of 100.00%.]]>
<![CDATA[Grouping of Toddlers with Malnutrition Based on Provinces in Indonesia Using K-Medoids Algorithm ]]>
<![CDATA[Sri Anita Siallagan]]>;
<![CDATA[M. Safii]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.53842/jaiea.v1i1.53
<![CDATA[Malnutrition is a poor health condition in infants and toddlers caused by a lack of nutritional intake. Babies and toddlers who suffer from malnutrition will experience conditions of slowness in development, slowness in thinking, underweight and so on. Malnutrition can be prevented by complete immunization from birth, providing good nutrition for their development, and so on. The purpose of this study was to determine the results of the grouping of provinces with the highest malnutrition sufferers using the K-Medoids method which is part of Data Mining. The K-Medoids method is a clustering method that can break the dataset into several groups. In this study, the data used were sourced from the Central Statistics Agency in 2016 – 2018. The results of this clustering will later show the province which is the toddler with the highest malnutrition. This research is expected to provide information for the government regarding the grouping of children under five with malnutrition in Indonesia.]]>
<![CDATA[Application of the C4.5 Algorithm in Teaching Teachers' Skills on Learning Effectiveness ]]>
<![CDATA[Feby Widya Sari]]>;
<![CDATA[M. Safii]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.53842/jaiea.v1i1.54
<![CDATA[Teachers as educators and education personnel have a very important role in improving the quality of education in schools. In an effective teaching and learning process, teacher skills in teaching are very important. This study aims to classify the skills of teachers in SMA Yayasan Pendidikan Keluarga using the Decision Tree method with the application of the C4.5 Algorithm in order to improve the teaching system in an effort to increase students' understanding of the learning process. In determining the teaching skills of teachers, classification is carried out into the labels "Relevant" and "Not Relevant" which has 5 variables, namely Age, Length of Work, Number of Teaching Hours, Students, and Learning Media. Sources of data used in this study obtained by conducting observations and interviews.]]>
<![CDATA[Family Economic Correlation To Students Learning Achievment Using Apriori Method ]]>
<![CDATA[Nurhayati]]>;
<![CDATA[Juliana Naftali Sitompul]]>;
<![CDATA[Tri Kartika Sari]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.53842/jaiea.v1i1.55
<![CDATA[The education system in Indonesia as mandated in the GBHN aims to educate the nation while at the same time responding to new challenges to create a decent and prosperous life. Understanding, apprecation, and experience of cultural and religious values in the right and true form will be increasingly needed. The economic status of the family is one of the factors that is sufficient to support the level of continuing education, especially for teenagers who are still student in school. Apriori method is used to obtain association rules that describe the relationship between item in the transactional database. There are two databases used, each of which has a different number of transactions. This study aims to aplly the apriori algorithm, as an analytical technique. The data taken as a case example is familiy economic data. This association search uses WEKA which will later find the rules and MySQL as the placeholder for the Database. From the results of the analysis using apriori, the highest confidence value was obtained at 0.9 with support 0.1 resulting in a students rule whose economics supported the learning achievement was very supportive, and the lowest confidence value of 0.2 with support 0.1 resulted in a students rule who had sufficient economics, so their learning achievement was also quite increased..]]>
