The Forecasting Application for Further Study Selection Based on Personal Preference
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Abstract
The development objectives of the forecasting application for further study selection based on personal preferences are to study the algorithm model for the effective prediction of further study and to develop a forecasting application for further study options based on personal interests. The operation process is divided into 6 steps: 1) Studying the relevant information 2) Developing the data warehouse 3) Testing with the decision tree algorithm, including J48, LMT and HoeffdingTree 4) Testing the accuracy of the model using Cross-validation test method with dividing the data into 5 parts, and 10 parts 5) Forecasting application development and 6) Evaluation of application satisfaction. The forecast was based on quantitative statistics of 892 students in Ubon Ratchathani Rajabhat University. The results of the algorithm tests indicate that J48 had the highest accuracy equal to 93.1%. After that, the application was developed, then the quality assessment by 5 experts was done. The overall evaluation was 4.16. The results of a satisfaction assessment with 30 students showed that the satisfaction of correctness and accuracy in data processing was 4.60 on average. The application is useful for further study selection based on personal preferences with an average of 4.57 and the forecasting results from this application are applicable with an average of 4.53.
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Articles published in Journal of Industrial Technology Ubon Ratchathani Rajabhat University both hard copy and electronically are belonged to the Journal.
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