Analysis of Indonesian Public Satisfaction Towards Goods Delivery Services using the CNN-LSTM Model - Sadhaka, Anak Agung Istri Prabhaisvari; Agus Dwi Suarjaya, I Made; Buana, Putu Wira (Journal of Information Technology and Computer Science, 2025)
The fast-paced development of e-commerce in Indonesia has driven the expansion and rising demand for goods delivery services. Every goods delivery service offers consultations or Q&A sessions about their services through Twitter. The number of tweets from users of goods delivery services can be used to determine the level of public satisfaction with these delivery services. The sentiment analysis process is conducted using a CNN-LSTM deep learning model. Evaluation of the CNN-LSTM model resulted in an accuracy of 0.838, an F1-score of 0.838 for the macro average and micro average, a precision of 0.840 for the macro average and 0.838 for the micro average, and a recall of 0.840 for the macro average and 0.838 for the micro average. Based on the results of analysis, it was found that Indonesian people tend to be dissatisfied with existing delivery services.