จากตารางที่ 4.15 ผลการวิเคราะห์ความ

From table 4.15 ANOVA results showed linear relationships correspond to the Attitude of the Perceived usefulness, Perceived ease of use, Perceived rist statistical significant level of .01, there is at least one free variable (of the Perceived usefulness, Perceived ease of use, Perceived rist) that is associated with a significant Attitude and can create an equation to predict. therefore, calculate the correlation coefficient value multiples. The value of the weight is in the standard score prediction and raw score, as well as create a regression equation, the multiples table 4.16 and 4.17 table.Table 4.16 the value of the correlation coefficient between the Perceived usefulness, Perceived multiples ease of use, Perceived rist with Attitude. From the table, it appears that the prediction of 4.16 at selected best Perceived ease of use comes first, is there a relationship with an equal Attitude and positive relationships are 0.779 significant statistical prediction of Perceived level of .01 when adding a usefulness, it was found that the relationship between the Perceived ease of use, Perceived usefulness to an equal Attitude and relationship 0.802 has a positive relationship with a significant level of .01, but statistical prediction of Perceived added value relationship found no rist increase shows that Perceived rist added to very little effect, therefore, Perceived ease of use that and Perceived usefulne.Ss is a prediction that can be used to predict and calculate weight and Attitude so the importance of forecasting and prediction equation generated the Attitude shows the table 4.17.

Table 4.15 Analysis of variance showed Attitude correlated linearly with the Perceived usefulness, Perceived ease of use, Perceived rist significant statistical level. 01 shows that independent variables least one body (of. Perceived usefulness, Perceived ease of use, Perceived rist) that correlated significantly with Attitude. And to create a predictive equation. The multiple correlation coefficient calculation. Weight important predictors of standard scores and raw scores. Including creating multiple regression equation shown in Table 4.16 and Table 4.17 Table 4.16 coefficient of multiple correlation between the Perceived usefulness, Perceived ease of use, Perceived rist with Attitude Table 4.16 shows that predicting the best is. selected before the Perceived ease of use is associated with Attitude equals 0.779 and a positive correlation with statistical significance level. 01 when adding predictors Perceived usefulness find that the relationship between Perceived ease of use, Perceived usefulness with. Attitude equals 0.802 correlated increase. And have a positive relationship with a significant statistical level. 01 But when the predictors Perceived rist found that the relationship did not add that Perceived rist added to little effect therefore concluded that Perceived ease of. Perceived usefulness and use as predictors used to forecast Attitude and thus calculates the weight of importance of the forecast. Attitude and created regression equation shown in Table 4.17.