Penerapan Teknik Super Learner dalam Pemodelan Faktor yang Memengaruhi Rekomendasi Operator Seluler

Abstract

Telecommunication refers to the exchange of information over long distances. Indonesia is one of the countries with the highest number of mobile network operators worldwide. This situation motivated Mobile Operator A to conduct a survey investigating store attendants’ recommendations to customers regarding the use of Operator A’s services. Classification methods can be applied to identify which operator a store attendant is likely to recommend based on several influencing factors. In this study, the super learner method is employed to integrate multiple base learners into a single optimized predictive model. The base learners used include random forest, bagging, and logistic regression. The resulting super learner model achieves an accuracy of 88.11% and an AUC of 0.9083. The most influential factor driving store attendants’ recommendations is whether Operator A is the best-selling internet provider in the respective store. Beyond individual effects, several interactions between pairs of explanatory variables are also found to play a significant role.