The objectives of this research are to propose a Bayesian model for spatial time series analysis to apply the proposed model to forecast a monthly rubber yield in Southern provinces of Thailand and to compare the performance of the proposed model with the classical Holt-Winters Additive Exponential smoothing. The proposed model is a linear mixed model (LMM) with spatial effects which follow a conditional autoregressive model (CAR). Dummy variables are used for seasonal effects. A Bayesian method is used for parameter estimation. The estimated monthly yields are used for the monthly rubber yield forecasting. The dependent variables are the rubber yield in each month of each province. The data are secondary data at a provincial level. The factors considered are spatial effects heterogeneity effects and seasonal effects. The results show that the factors influencing on the amount of rubber yields are spatial heterogeneity and seasonal effects. The proposed model is proper and forecast accurately. Using the mean absolute error (MAE) the proposed model has a better performance compared to the classical Holt-Winters Additive Exponential smoothing in both model fitting and model validating. The proposed model should be the first consideration for spatial time series forecasting.

The purposes of the research were to create and find efficiency validation of computer assisted instruction focused on the Basic Plumbing for the standard 90/90 and analyze the students’ Learning achievement after using computer assisted instruction. The samples were the subjects used in this research were the students 20 person the first – year students Diploma of Metal Technology in the Faculty of Engineering at Rajamangala University of Technology Phra Nakhon The researcher experimented by using pretest and then using the computer assisted instruction focus on the Basic Plumbing next the students did the posttest. After that the researcher calculated to find the computer assisted instruction efficiency and analyzed the students’ learning achievement after studying. The result revealed that the computer assisted instruction efficiency was efficient for standard 90/90. And after studying by using computer assisted instruction the students’ learning achievement increased significantly at 0.05.