Research Article
Deep Learning-Based Complaint Classification for Indonesia Telecommunication Company's Call Center
@INPROCEEDINGS{10.4108/eai.12-10-2019.2296518, author={Shinta Devi Lukitasari and Fadhil Hidayat}, title={Deep Learning-Based Complaint Classification for Indonesia Telecommunication Company's Call Center}, proceedings={Proceedings of the 7th Mathematics, Science, and Computer Science Education International Seminar, MSCEIS 2019, 12 October 2019, Bandung, West Java, Indonesia}, publisher={EAI}, proceedings_a={MSCEIS}, year={2020}, month={7}, keywords={call center deep learning intent complaint classification rnn}, doi={10.4108/eai.12-10-2019.2296518} }- Shinta Devi Lukitasari
Fadhil Hidayat
Year: 2020
Deep Learning-Based Complaint Classification for Indonesia Telecommunication Company's Call Center
MSCEIS
EAI
DOI: 10.4108/eai.12-10-2019.2296518
Abstract
The preliminary research was held to utilize the call center conversations records from a broadband telecommunications company in Indonesia. There is a need from the company to classify customer's complaints automatically by a system to minimize human errors and at once streamline the business processes and resources. Natural Language Processing (NLP), as an integral part of artificial intelligence (AI), empower machines to understand human languages for performing beneficial tasks. The growth of deep learning is the main driver behind NLP for performing various practical applications and business, therefore deep learning is expected to overcome the problems encountered. This paper explains the methods used in designing the classification systems based on deep learning. A literature review is conducted to find the proper algorithm used in classifying problems. Furthermore, it also explains the stages performed in preparing the data and building the system model. From experiments conducted, it can be stated that the RNN algorithm can be used in the classification of customer complaints with the results shown by the accuracy value of the model.
