Open AccessOptimization Of The Decision Tree Algorithm Used Particle Swarm Optimization In The Selection Of Digital Payments
Author(s) -
Indah Ariyati,
Susy Rosyida,
Kresna Ramanda,
Verry Riyanto,
Siti Faizah,
Ridwansyah
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1641/1/012090
Subject(s) - particle swarm optimization , payment , computer science , selection (genetic algorithm) , decision tree , quality (philosophy) , data mining , algorithm , machine learning , world wide web , philosophy , epistemology
One of the developments of information technology in Indonesia was the developments in Fintech (financial technology) that made it easy for people to access financial products, facilitated online transactions and also increased financial literacy. The development of fintech occurs when the use of cash was reduced to cashless when making payment transactions so that transactions would be more practical, easy, safe and comfortable. The purpose of this study to improve the quality of decision tree modeling and accuracy in the selection of digital payments. This research was focused on determining the fintech applications that were widely used by the people of Indonesia, namely Gopay or Ovo by comparing the advantages of applications and features of each fintech application. Optimization method of Decision Tree Algorithm (C4.5) and Particle Swarm Optimization by selecting several attributes including the level of ease of use, data security, application trust and convenience, maximum balance increase, discounts, cashback, ease of top-ups, range of existing merchants, return the money and customer complaint services. The results of the development of a decision tree algorithm based on particle swarm optimization provide a good classification and increase the validation value in the selection of digital payments.