Rough Set Method for Determining Knowledge Attribute on Customer Satisfaction

Abstract

Purpose: The research aims to determine how the level of customer satisfaction in a small business is a field of flower arrangement services as well as information that can dug from a collection of customer data. Approach/Methodology/Design: The samples used were ten customers who considered loyal. The method used is a Rough set with a satisfaction attribute consisting of confidence, integrity, pride, and desire. Findings: Based on this decision rule, confidence becomes the most dominant attribute. The results showed that the four dimensions of the emotional bond used as an attribute in the Rough Set process to analyze the level of customer satisfaction that strongly affects is the dimension of Confidence, this is evident from the resulting General Rule. Every decision produced always uses the confidence dimension in the comparison input, meaning the level of customer confidence in the company should be a special concern. In the dimensions of the emotional bonds the first dimensions are constructed and fundamental is the confidence dimension, this dimension indicates the level of customer confidence in the company. Confidence dimensions cannot stand it self yet to build long-term relationships with customers without by other dimensions. Practical Implications: The study will contribute positively to give some information of knowledge that contained on customer satisfaction. It shown the alternative for measuring for satisfaction that can be used for a small business and academic. Originality/Value The results generated in this study opened new avenues for customer satisfaction analysis. We must not limit the analysis of customer satisfaction survey data using conventional statistical methods. The Rough theory Set is an innovative tool for finding Knowledge of customer behaviour patterns.

Rough Set Method for Determining Customer Satisfaction at Pdam Tirtanadi Medan City

“…Drinking Water Companies (PAM) located in regional government areas are called Regional Drinking Water Companies (PDAM), one of which is PDAM Tirtanadi located in Medan City, North Sumatra Province.In order to increase customer satisfaction, PDAM Tirtanadi often experiences difficulties in maintaining the production of clean water installations because the quantity of clean water to consumers is disrupted. The instability of raw water supply to production installations is caused by the amount of water discharge experiencing uncertainty in the time process from one dry season to another,To find out the level of consumer satisfaction, data mining is one solution to solve this problem (Istianingsih & Defit, 2021) (Oyedele et al, 2020). Data Mining is a process that uses statistical techniques, mathematics, artificial intelligence, machine learning to extract and identify useful information and related knowledge from various large databases (Saura, 2021)(Rao Vajjhala & Ramollari, 2016).…”