A Study on the Digital Wallet Usage among Citizens of Kochi using FP-Growth Algorithm
Aparna H1, Karthika S2, Rajalakshmi V R3
1Aparna H, Department of Computer Science and IT, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham, Kochi, India.
2Karthika S, Department of Computer Science and IT, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham, Kochi, India.
3Rajalakshmi V R, Department of Computer Science and IT, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham, Kochi, India.
Manuscript received on 23 March 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 March 2019 | PP: 1315-1322 | Volume-7 Issue-6, March 2019 | Retrieval Number: F2915037619/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Digital transaction has gained popularity among the Indian citizens after the demonetization of 2016. People have started to prefer cashless payment methods for their financial transactions and digital wallets has emerged as one of the significant tools. A digital wallet is a smart phone application provided by a service provider which enables the user to keep money and to make electronic transactions. They are an alternative version of the traditional leather wallets. The money can be loaded to the wallet from bank account by using any electronic payment methods such as internet banking, mobile banking, debit cards etc. as well as it can be transferred to other accounts as well. There are many types of transactions for which digital wallets are used such as paying utility bills, mobile recharge, fund transfer, donations, etc. This paper focuses on mining association rules on the types of transaction for which people use digital wallet the most using FP-growth algorithm. The algorithm is best suited for mining out interesting patterns from large datasets. A survey is conducted among the citizens of Kochi whose results is used as dataset for the algorithm. RapidMiner Studio is used for analyzing the data. Through our research we found that citizens of Kochi use their app the most for mobile recharging, train/bus/cab/airline booking and movie ticket booking. We have also found out the results based on gender. This data can be used by both private and public sector companies in building an efficient app having a wider public approval and thus promoting cashless transactions in our country
Keywords: Association rules, Data mining, Digital Wallet, FPGrowth algorithm
Scope of the Article: Data Mining