Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal International Journal of Engineering and Emerging Technology
Antonius Ibi Weking
Department of Electrical and Computer Engineering, Udayana University
Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Mechanical Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Determination of the Senior High School Department Using the Expectation Maximization Algorithm I Made Gede Yudiyana; Andrew Sumichan; Muhammad Ridwan Satri0; Antonius Ibi Weking
International Journal of Engineering and Emerging Technology Vol 4 No 1 (2019): January - June
Publisher : Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

High school is an educational institution that has directed students to concentrate or learn more in the field of science in accordance with the academic abilities of the students concerned. Generally the top high school has 3 department intended for students when climbing levels from grade 1 to grade 2, namely majors in Science, Social Sciences and Language. Nowadays with a growing human population, the number of students enrolled in a school is quite large, with the number generally in public schools 30 to 40 students per class. With the large number of students this will provide difficulties to determine the direction of each student if done manually. With this problem the researcher implements an EM (Expectation Maximization) method, this method is chosen because of its ability to get the highest probability value and can find the optimal parameters even though the available available map is incomplete or lacking. Using this method will make it easier for a school institution to determine the right direction for students
Application of Data Mining with Support Vector Machine (SVM) in Selling Prediction Trend of Spiritual Goods (Case Study: PT. X Bali) Philipus Novenando Mamang Weking; I Gusti Ngurah Wira Partha; Antonius Ibi Weking
International Journal of Engineering and Emerging Technology Vol 4 No 1 (2019): January - June
Publisher : Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Spiritual activities become an inseparable part of human life. To support these spiritual activities, the need for spiritual equipment that supports the process of running a spiritual activity. PT. X Bali is a company that runs the business of selling spiritual goods. The tight competition and economic factors faced make PT. X Bali wants to predict the sale of goods so that they can see whether the sale of spiritual goods is up or down in order to increase the efficiency. The prediction process can be done with data mining technique using the Support Vector Machine (SVM) method. Data that used for prediction is based on stock data and data on goods sold from the total sales results of the last two years. Based on the results of SVM calculations, the level of prediction accuracy results reached 62.5% and the need for spiritual goods in the following year will be predicted to decline
Co-Authors Andrew Sumichan I Gusti Ngurah Wira Partha I Made Gede Yudiyana Muhammad Ridwan Satri0 Philipus Novenando Mamang Weking