Penerapan Algoritma SVM untuk Deteksi Review Buatan Bot pada Ulasan Aplikasi Facebook di Google Play Store - Shams Afzal Karim, MIkhail; Akhsanul Hakim, Albi; Maulidatul Khairah, Ama; Puspita Sari, Anggraini (Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research, 2024)
App reviews on Google Play Store serve as a crucial source of information for users to select applications that align with their needs. However, there is a growing concern regarding the misuse of app reviews through the creation of fake reviews by bots. These fake reviews can mislead users and negatively impact the reputation of app developers. This research aims to detect bot-generated reviews in Facebook app reviews on Google Play Store using the Support Vector Machine (SVM) algorithm. SVM is a classification algorithm that has proven effective in various classification tasks, including fraud detection. The research utilizes a dataset that has been categorized as genuine or bot-generated texts. The results demonstrate that the SVM algorithm successfully detects bot reviews with a high F1-score of 0.8981, exhibiting no signs of overfitting. This is further supported by the consistent F1-score values across training and testing data. Implementing the SVM algorithm can contribute to enhancing the quality of app reviews and protecting users from misleading information. This research shows that the SVM algorithm can be an effective tool for detecting bot-generated reviews on Facebook application reviews on the Google Play Store.