Selected Papers from the 1st International Conference on Islam, Science and Technology, ICONISTECH-1 2019, 11-12 July 2019, Bandung, Indonesia

Research Article

Analysis on User Activity in E-Commerce Website for Performance Evaluation and Decision Making Using Big Data Analytics

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  • @INPROCEEDINGS{10.4108/eai.11-7-2019.2298019,
        author={Radityo  Pradana and Rizky  Luxianto},
        title={Analysis on User Activity in E-Commerce Website for Performance Evaluation and Decision Making Using Big Data Analytics},
        proceedings={Selected Papers from the 1st International Conference on Islam, Science and Technology, ICONISTECH-1 2019, 11-12 July 2019, Bandung, Indonesia},
        publisher={EAI},
        proceedings_a={ICONISTECH-1},
        year={2020},
        month={11},
        keywords={big data; e-commerce; website; web-based business; decision making},
        doi={10.4108/eai.11-7-2019.2298019}
    }
    
  • Radityo Pradana
    Rizky Luxianto
    Year: 2020
    Analysis on User Activity in E-Commerce Website for Performance Evaluation and Decision Making Using Big Data Analytics
    ICONISTECH-1
    EAI
    DOI: 10.4108/eai.11-7-2019.2298019
Radityo Pradana1,*, Rizky Luxianto1
  • 1: Universitas Indonesia
*Contact email: radityo_pradana@yahoo.com

Abstract

The purpose of this study is to analyze how Big Data Analytics can help managers in their decision making process, specifically in e-commerce / web-based business. This study took the dataset from one website that implements e-commerce functions in its website. The data taken would be the data of user activities in the website such as page visit, add product to cart, and buy online. To analyze the dataset, several algorithm will be used, such as Association Rule Mining Algorithm (APRIORI), K-Means Clustering, and Pearson's Correlation Coefficient. The data will be processed and will be used to show details in users behavior in the website to see the specific pattern that can be useful for decision making. For example, which product is visited and bought the most, how many pages are visited before buying the product, how many users repurchase the product, and which retailer is mostly used by users. This paper would also identify whether the current Big Data implementation on the company can be improved, and identify if it is a good investment for the company to improve the Big Data implementation system.