APPLICATION OF SMARTPHONE DAMAGE PREDICTION USING THE NAIVE BAYES METHOD AND LAPLACE SMOOTHING
This study aims to build and implement prediction system of smartphone damage on the android platform. This application was built using android studio 2.0 and SQLite database. The recommendation system is a software that aims to assist users by providing recommendations to users when users are faced with large amounts of information. Recommendations are expected to help users in the decision-making process, such as what items to buy, what laptops will be used, or what songs will be heard, and more. This system serves to provide prediction of damage to the smartphone built from the calculation of user input parameters in the form of questions about the symptoms experienced by users on their smartphone, then will generate predictions about the possibility of damage experienced by using methods naïve bayes and laplace smoothing, this method is used in determining an event using previously collected data. The results of this study indicate that the accuracy is not satisfactory with an accuracy rate of 20%.