Analysis of E-Commerce Process in the Downstream Section of Supply Chain Management Based on Process and Data Mining

Abstract

Most businesses today use ecommerce stores and/or ecommerce platforms to carry out online marketing and sales activities. The rapid increase in the volume of E-commerce sales transactions normatively causes various problems that occur, especially in this case the buyer or consumer. Consumers expressed dissatisfaction in their e-commerce delivery experience. Customers often complain to sellers in the marketplace about the delay in sending the ordered package. This paper proposes a research model that is proposed in analyzing the datasets generated from the Downstream Supply Chain Management process, especially the process of selling and shipping E-Commerce goods to end customers. The mechanism used is collaborating process mining and data mining so that the resulting analysis becomes more powerful and better information is obtained compared to only analyzing separately. The results of the analysis in the case study of the E-commerce Costumer to Customer (C2C) marketplace show that process mining related to shipping goods can be explained by adding the results of data mining analysis from the datasets obtained, especially the processes in the Downstream Supply Chain Management Section.