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Resty Wulanningrum
University of Nusantara PGRI Kediri

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Learning Vector Quantization Image for Identification Adenium Resty Wulanningrum; Bagus Fadzerie Robby
Indonesian Journal of Electrical Engineering and Computer Science Vol 4, No 2: November 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v4.i2.pp383-389

Abstract

Information and technology are two things that can not be separated and it has become a necessity for human life. Technology development at this time was not only used for intelligence purposes only, but has penetrated the world of holtikurtura. Adenium is one of the plants are much favored by ornamental plants lovers. Many of cultivation adenium who crosses that appear new varieties that have the color and shape are similar to each other. From this case, then made an application that can identify the type of adenium based on the image of that flower. Learning Vector quantization is one of the algorithm  that used for clustering. Based on test scenarios were performed, image identification applications Adenium petals produce an accuracy of 86.66% with a number of training dataset of 135 images and datasets with a test as many as 45 images max epoch 10 and learning rate between 0.01 to 0.05.
Prediction Of College Student Achievement Based on Educational Background Using Decision Tree Methods Ratih Kumalasari Niswatin; Resty Wulanningrum
Indonesian Journal of Electrical Engineering and Computer Science Vol 4, No 2: November 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v4.i2.pp429-438

Abstract

College student as a product can be used as a reference to show the success of education. This research will build a system prediction of college student achievement based on educational background using decision tree method.The research will be conducted on students of Informatics Engineering Department, Faculty of Engineering, University of Nusantara PGRI Kediri. The objective of this system is to help the new admissions process in the selection of students is based on the predicted results of student achievement and help the department to classify new students based on educational background. The method used to predict student achievement is the algorithm C4.5 decision tree method using several criteria based on the educational background of students before, they arethe uan mathematical value, the uan Indonesianvalue, theuan English value, the majors in the school, and the average report cards in the school of origin. This system will be made based on the web to be more effective, fast and easy to use. This system will produce predictions of student achievement information on Informatics Engineering
Co-Authors Bagus Fadzerie Robby Ratih Kumalasari Niswatin