Comparison of Artificial Intelligence Approach Models Based on Artificial Neural Networks and Classical Models in Predicting E-wallet Interest
Perbandingan Model Pendekatan Artificial Intelligence berbasis Jaringan Saraf Tiruan dan Model Klasik dalam Prediksi Minat E-wallet
DOI:
https://doi.org/10.21070/ups.7674Keywords:
Artificial Neural Network, Multiple Linear Regression, Security, Privacy, E-TrustAbstract
Rapid technological advances have brought about changes in all aspects, especially the payment sector. Electronic wallets or e-wallets are currently trending in society because of their curiosity and convenience. However, the implementation of e-wallets cannot be separated from several factors that influence consumer interest in using them. Some of the main factors that influence consumer decisions in using e-wallets include security, privacy and e-trust factors. This study aims to analyze the effect of security, privacy and e-trust on the interest in using e-wallets in Indonesia by comparing two methods, namely Artificial Neural Networks and Multiple Linear Regression using two software, namely SPSS and MATLAB. Comparative analysis was carried out to identify the method that has the best level of accuracy. The population used in this study was calculated using the Lemeshow formula, which produced 165 responses. The results of the study showed that the Artificial Neural Network method provided much better analysis results than Multiple Linear Regression with the results of the values obtained in each variable approaching the expected target numbers, while multiple linear regression provided less than optimal results, especially in the security and privacy variables.
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