Claim Missing Document
Check
Articles

Found 6 Documents
Search
Journal : Journal of Artificial Intelligence and Engineering Applications (JAIEA)

Implementation of K-Means Clustering on High School Students Management Kartina, Anggriani Dwi; Safii, M.
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (644.606 KB) | DOI: 10.59934/jaiea.v1i1.47

Abstract

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.
K-Medoids Algorithm Analysis in Grouping Students' Level of Understanding of Subjects Butarbutar, Ehrlich F.T; Safii, M.
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (718.315 KB) | DOI: 10.59934/jaiea.v1i1.50

Abstract

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
Implementation Data Mining of Employement Contract Exten-sion at Indosat Using Naïve Bayes Sari, Andini Fadila; Safii, M.; Suhendro, Dedi; Damanik, Irfan Sudahri
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (992.868 KB) | DOI: 10.59934/jaiea.v1i1.52

Abstract

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%.
Grouping of Toddlers with Malnutrition Based on Provinces in Indonesia Using K-Medoids Algorithm Siallagan, Sri Anita; Safii, M.
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (785.331 KB) | DOI: 10.59934/jaiea.v1i1.53

Abstract

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.
Application of the C4.5 Algorithm in Teaching Teachers' Skills on Learning Effectiveness Sari, Feby Widya; Safii, M.
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1211.737 KB) | DOI: 10.59934/jaiea.v1i1.54

Abstract

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.
Analysis of Decreased Public Awareness in the Application of Health Protocols with the C4.5 . Algorithm Arfika, Retno; Safii, M.
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (427.989 KB) | DOI: 10.59934/jaiea.v1i1.56

Abstract

The purpose of this study is to determine the dominant factors that affect the decline in public awarenesson the application of health protocols using the C4.5 Algorithm. Sources of data used in this study obtained by conducting observations and interviews. The variables used include (1) Employment, (2) Environment, (3) Sanctions and (4) Concern. The research test process uses RapidMiner software to create a decision tree. The results obtained 6 rules with 4 rules decreasing status and 2 rules increasing status. The level of accuracy obtained is 100%. The results of this study are expected to be input for the surrounding community to better understand the importance of implementing health protocols at this time, so that they can help the Government to succeed in the health protocol awareness program in inhibiting the spread of Covid-19 in Indonesia.