RESEARCH ON FACTORS AFFECTING TOURIST INVOLVEMENT IN COFFEE TOURISM AFTER COVID-19 PANDEMIC IN THAILAND

In this paper, we analyze the factors affecting tourist involvement in coffee tourism after covid-19 pandemic in Thailand. The coffee tourism data is collected. Using Stop word removal, stemming, dimensionality reduction, Min-max normalization the data can be preprocessed. Feature can be extracted by using Linear Discriminant Analysis (LDA). Bat Algorithm is used for feature selection. Stochastic Neuro Fuzzy Decision Tree (SNF-DT) is used for Data analysis. Figure 2 indicates an overall methodology used. A. Dataset This study comprised 6,485,791 Thai and international visitors who visited Chiang Rai, Chiang Mai, Mae Hong Son, and Lampang provinces were included in this research. This study includes tourists from Thailand and abroad who visited coffee tourism destinations and participated in coffee-related tourism activities such as a tour of the cultivation and production area or a coffee tasting. The sample was selected using grab sampling. Based on ninety five percent confidences, the sample size was determined to be 10,000 participants with a margin of error of 0.05. The final result was 398, however it was rounded up to 400 to make data gathering. The proportion of people that responded is also shown for each province. Table 1 show that Sample Group in Each Province.