Abstract— As consumer transaction preferences shifted from
analog to digital, banks were compelled to develop digital
transactions in the form of mobile banking. Users of mobile
banking provide feedback regarding the application's usability.
The opinions of users can be emotive. Emotions influence what a
person emits or applies. Emotions are the behavioral response of a
person when he is happy or unhappy. Thus, the manifestation of a
person's emotions, whether in the form of facial expressions,
verbal communication, written text, or judgment, can be used as a
source of information to aid in decision making. The objective of
this study is to apply emotion mining to the analysis of user
evaluations of the BRImo application, one of the three most
popular platforms in Indonesia as of August 2022, with a total of
800,000 reviews on the Play Store. Emotion Mining can be used to
analyze the four categories of emotions expressed by users in the
comments section: happy, angry, sad, and afraid. According to
BRImo user evaluations, the decision tree algorithm is used to
categorize happy, sad, afraid, and angry feelings. Using a decision
tree to manage large data category sets is effective. The obtained
dataset included 2959 happy classes, 2196 sad classes, 387 angry
classes, and 81 scared classes. According to the findings of the
analysis, a significant number of users of the BRImo application
express positive sentiments in their evaluations, which are
indicative of happy emotions. The Decision Tree algorithm yields
results with a performance specification of 84.5%, sensitivity of
85.5%, and precision of 84.4%.