A Synthesis forms the CAI network Students classified by aptitude theoretical 4 MAT By Decision Tree Methodology

Abstract

This research aims 1) Synthetic forms of computer on the network is classified as learning aptitude by 4 MAT theory by decision tree methodology and 2) Assessing the patterns CAI network classified as learning aptitude by 4 MAT theory by decision tree methodology. The sample is 5 experts with expertise in computer studies. Academic and research the lecturer of computer and Information Innovation in educational. The tools used in this research were formed CAI network and assess the suitability of the model. Data were collected through questionnaires to assess the scale five-star reviews. The results showed that The comments on the concept of a synthetic form of the CAI network classified as learning aptitude by 4 MAT theory by decision tree methodology. Module 1: Data Learning For 4 MAT Rule Module is composed of three parts. Part 1 Collection Data was high. ( = 4.40) Part 2 Tree Decision Classification Module is at the highest level. ( = 5.00) And Part 3 Develop Base Module at a high level. ( = 4.80) Module 2: 4 MAT Learning Style Module consists of three parts. Part 1 Student Module at a high level. ( = 4.20) Part 2 4 MAT Rule Base at a high level. ( = 4.20) and Part 3 Allocation 4 MAT Learning Style Module at a high level. (= 4.60) Module 3: Learning Management Module is composed of three parts. Part 1 Subject Learning Module at a high level. ( = 4.00) Part 2 Student Management Module at a high level. ( = 4.20) and Part 3 Teacher Module at a high level. ( = 4.60) Module 4: Evaluation Add Assessment Module at a high level. ( = 4.40) Results of the evaluation of components and frameworks. Is appropriate at a high level. ( = 4.44) And can be useful to the process of developing CAI distribution network based learning aptitude by 4 MAT theory by decision tree methodology.