The increasing amount of internet usage encourages organizations, companies, and other institutions to engage with the public through various online media. Website is an example of online information channel for those institutions, enabling the visitors to search detailed information. Extracting pattern of website visitors' behavior is important to find out the trend on information searching and page accessing. Thus, the website can be improved to have better accessibility and user performance. However, the extracting pattern in an educational website is not often conducted while an educational website is considered as useful. This study was conducted using pattern mining, one of the applications of web usage mining, to find out patterns and trend of visitors' behavior in information searching through educational institution website. In this study, visitors' web log data of the website in February, March, and April was processed using the FP-Growth algorithm of association rules and compared as those three months have the highest number of visitors' activities in accessing website information in a year. The results show that there are seven similar patterns among the three months. However, there are some distinctive patterns found which describe the visitors' behavior each month which may occur due to the selection process agenda. By knowing these patterns, an educational institution may improve the interface and the quality of the website by creating link recommendation for each tab views which has the higher correlation to make the visitors access the information easier.