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Journal : JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING

Data Clustering Recommendations For Selection Student Majors To Higher Edication Using The K-Means Method (Case Study of SMAN 2 Palembang) Jemakmun makmun Jemakmun; R. Ahmad Dicky Syarief Purboyo
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 6 No. 2 (2023): Issues January 2023
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v6i2.7911

Abstract

SMA Negeri 2 Palembang has two majors, science and social studies. As a result of choosing the wrong major after entering college, students sometimes experience difficulties and feel the wrong major, in connection with this problem the author tries to provide a solution for determining majors for college using the k-means clustering method. In this study, the students were grouped using the data mining method. The group is based on the attributes of majors, interests, traits, hobbies, talents, and the average value of science and social science subjects. Clustering data using the K-Means method and measuring the Euclidean distance, analyzed using Microsoft excel manual calculations and RapidMiner tools. The results of the study indicate that Cluster 1 is a cluster that is recommended to take the Language major. Cluster 2 is a cluster that is recommended for a major in Engineering. Cluster 3 is a cluster that is recommended to major in Health/Medicine. Cluster 4 is a cluster that is recommended for majoring in Economics. Cluster 5 is the recommended cluster for majoring in Language. While the results of the calculation research using RapidMiner, Cluster_0 is recommended to major in Engineering, Cluster_1 is recommended to major in Economics, Cluster_2 is recommended to major in Language, Cluster_3 is recommended to major in Education, Cluster_4 is recommended to major in Medicine/Health.
Haar Cascade Algorithm On Mask Detection System Based On Distance In Facing The Normal Era Jemakmun makmun Jemakmun; Rudy Suhirja
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 7 No. 1 (2023): Issues July 2023
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v7i1.9346

Abstract

The COVID-19 outbreak has hit almost the whole world, including Indonesia which has become a disease outbreak in early 2020. Therefore, currently, various places have enforced regulations to comply with health protocols by using masks. So all South Sumatra must follow health protocols by wearing masks and maintaining distance. So the program for making this Mask Detection System is one way to overcome public awareness, especially among Bina Darma University students about the importance of using masks today. In the case of making this mask detection system program, the researchers used Python and the Haar Cascade Algorithm. From experiments using the Haar Cascade method, this system can detect people who use masks and do not use masks. This test is also done by inputting images or videos. The results of the study that, based on distance and angle, the estimated minimum distance for this mask detection application is 25 cm and the maximum is 150 cm will produce maximum mask detection results and based on distance, the estimated distance is 50 cm to 300 cm, the design of the detection system can recognize the maximum face
EVALUATION OF STUDENTS' E-LEARNING LEARNING OUTCOMES USING THE COURSE COMPLETION METHOD Jemakmun, Jemakmun makmun; Rahmatullah, M.Taufik; Roni, Mukran
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 8 No. 1 (2024): Issues July 2024
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v8i1.11639

Abstract

The current development of internet technology has changed the direction of the learning system at both elementary and tertiary levels by means of online, blended learning, and e-learning. This research aims to determine and analyze the learning outcomes of students using course completion during lectures using the eLearning method. The research subjects are Bina Darma University students. Data collection was carried out in this research through observation and taking primary data from the e-learning system. The instruments in this research include the independent variable (X), which is report completion, and the dependent variable (Y), which is elearning learning outcomes. The resulting research results are: 1. There is a positive influence from the activity task variable on the student learning outcome variable, which is known to be active in carrying out the tasks in e-learning. 2. There is a positive influence from the material variable on the student learning outcome variable, which is known to be active in opening the material. provided in e-learning. Multiple linear regression tests result from the course completion variable on student learning outcomes. It can be concluded that there is a positive influence on the learning outcomes of variable Y from variable X. Students can also share information or opinions on various matters relating to the subject matter or assignments given by the lecturer. Apart from that, lecturers can place learning materials and assignments that students must complete in certain places in e-learning for students to access.