PENERAPAN METODE REGRESI LOGISTIK BINER DENGAN MENGGUNAKAN PHYTON UNTUK MENGANALISA PENGGUNA MEDIA SOSIAL TERHADAP PROBABILITAS PEMBUKAAN REKENING PADA BANK X

Abstract

In the rapidly developing digital era, financial institutions, such as Bank X, can utilize social media to understand consumer behavior and expand their customer base. This research uses a binary logistic regression method with social media user data to analyze the relationship between online activity and the decision to open an account at the bank X. The aim of this research is to assess the influence of user activity on social media platforms (Instagram, TikTok, Facebook, Twitter and YouTube) on the decision to open an account at the Bank X as well as analyze and identify key variables that influence the decision to open an account, based on media activity data. social. Results show that Instagram has a significant influence, with the combination of social media platforms increasing the probability of opening an account. TikTok and Facebook also have a positive impact, while Twitter and YouTube have a lower impact. Recommended marketing strategy to focus more on Instagram, with an emphasis on a combination of other social media platforms. From the results of the scenario interpretation, Instagram has a significant positive influence on the decision to open an account, with the highest probability among other individual platforms. TikTok, Facebook, and Twitter also have a positive impact, although their probabilities tend to be similar. Meanwhile, YouTube's influence on the decision to open an account seems to be lower than other social media platforms.