Intelligent Information System for Management of Annual Budget Plan of Sirindhorn College of Public Health Khon kaen

Abstract

The purposes of the research were to compare efficiency in forecasting budget in annual performance plan among Neural Networks (Single Layer), Neural Networks (Multi-Layer), Linear Regression and to Predict data budget in annual performance plan and to Study the satisfaction system for administration and management in annual performance plan from 46 people were

classified into 3 groups by purposive sampling. Group 1 is 3 computer experts. Group 2 is users are involved in the preparation of plans Budget allocation Spend budget Of Sirindhorn Public Health College 25 people in Khon Kaen Province. Group 3 is the administrators of Sirindhorn Public Health College. Khon Kaen Province, 18 people and tool was satisfaction questionnaire. The statistics used were mean and standard deviation.

            The research findings showed that the Linear Regression gave efficiency in highest data classification or with the highest predictive accuracy if 78.37 percent. The Absolute value of error average at 0.16, Followed by Neural Networks (Multi-Layer) gave efficiency in the data classification with 74.15 percent. The Absolute value of error average at 0.22, Followed by Neural Networks (Single Layer) gave efficiency in the data classification with 73.23 percent. The Absolute value of error average at 0.20 respectively. 2) Predict data budget in annual performance plan results of user about exactly of predict data budget at a high level. 3) Overall satisfaction assessment results of user at a high level. It’s showed that the efficiency system responds the needs of users and able to apply to the organization.