Logo

Classification algorithm for customer complaint using fuzzy approach

Razali, R. and Jaafar, J. (2016) Classification algorithm for customer complaint using fuzzy approach. Jurnal Teknologi, 78 (12-2). pp. 65-76.

Full text not available from this repository.

Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

Customer complaint contains valuable information to realize the opportunity to enhance service for customer satisfaction. The main challenge to extract the valuable information is a proper approach managing the complaint data, classification process and high level of uncertainties on the complaint and involvement of experts� opinion. Besides, most of the existing complaint system still running the complaint handling process manually. The impact is on time processing issue. Another problem, current complaint system focused on the English keyword, while in Malaysia, the complaint system is using Malay wording and keyword. Hence, an effective approach is needed to tackle these issues properly. This paper presents Fuzzy Logic Complaint Handling Algorithm (FLCHA) to handle the complaint handling process. The FLCHA used fuzzy logic approach to classifying real complaint, and non-real complaint, improve time processing and automate the complaint handling process. Customer complaints data from local government in Kuala Lumpur is used for this study to prove the efficiency of the proposed approach. Seven experts from the local government are working together in this study. The domain of the complaint data focused on landscaping and 406 data provided for the testing. Results show that the proposed approach is highly consistent with the human benchmark, efficient and good processing time. Overall GGTrap (fuzzy type-1) membership function using fuzzy number is the best membership function for customer handling process with accuracy 93.35 and processing time 0.441 seconds. © 2016 Penerbit UTM Press. All rights reserved.

Item Type:Article
Impact Factor:cited By 2
ID Code:25798
Deposited By: Ms Sharifah Fahimah Saiyed Yeop
Deposited On:27 Aug 2021 13:06
Last Modified:27 Aug 2021 13:06

Repository Staff Only: item control page