PENGARUH RANDOM UNDER-SAMPLING TERHADAP KLASIFIKASI KECURANGAN TRANSAKSI MOBILE MENGGUNAKAN GRADIENT BOOST TREE

ABINUUGROHO, DARMAWAN and Abdiansah, Abdiansah and Miraswan, Kanda Januar (2022) PENGARUH RANDOM UNDER-SAMPLING TERHADAP KLASIFIKASI KECURANGAN TRANSAKSI MOBILE MENGGUNAKAN GRADIENT BOOST TREE. Undergraduate thesis, Sriwijaya University.

	Text RAMA_55201_09021181722010.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (2MB) | Request a copy
	Text RAMA_55201_09021181722010_TURNITIN.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (8MB) | Request a copy
Preview	Text RAMA_55201_09021181722010_0001108401_0009019002_01_front_ref.pdf - Accepted Version Available under License Creative Commons Public Domain Dedication. Download (793kB) | Preview
	Text RAMA_55201_09021181722010_0001108401_0009019002_02.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (376kB) | Request a copy
	Text RAMA_55201_09021181722010_0001108401_0009019002_03.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (174kB) | Request a copy
	Text RAMA_55201_09021181722010_0001108401_0009019002_04.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (951kB) | Request a copy
	Text RAMA_55201_09021181722010_0001108401_0009019002_05.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (427kB) | Request a copy
	Text RAMA_55201_09021181722010_0001108401_0009019002_06.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (96kB) | Request a copy
	Text RAMA_55201_09021181722010_0001108401_0009019002_07_ref.pdf - Bibliography Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (163kB) | Request a copy
	Text RAMA_55201_09021181722010_0001108401_0009019002_08_lamp.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (139kB) | Request a copy

Abstract

Mobile Money Transfer can be defined as a payment transaction process in the form of digital money. This process can make payments, money transfers, and transactions via mobile devices. In the traditional economy toward a digital economy, violations often occur. Control of fraud in the financial sector is not enough to commit fraud crimes. This study builds a mobile transaction classification system that uses the Gradient Boost Tree algorithm. There are problems with the data used, the data is unbalanced. Random undersampling was chosen to solve the data problem. In the application of this algorithm, 10 tests were carried out with the evaluation of k-fold cross-validation on the dataset. From and testing the data, it was found that the average training accuracy is 99.84% and the computation time is 1433.6 seconds for the Gradient Boost Tree algorithm with a parameter value of 100 while the 1000 parameter gets an accuracy of 99.89% with a time of 14044 seconds. In the next scenario, the average accuracy is 97.64% and the computation time is 2.98 seconds for Random Under-sampling and Gradient Boost Trees with a parameter value of 100. The last scenario obtained an average accuracy of 98.57% and computation time of 30.64 seconds for Random Undersampling and Gradient Boost Tree with a parameter value of 1000. There is a decrease inaccuracy due to the Random Under-sampling method that removes data randomly to make the data balanced. Random data deletion causes some important data to be deleted and results in the classification results.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Gradient Boost Tree, Random Under-sampling
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General) > T14 Philosophy. Theory. Classification. Methodology Cf. CB478 Technology and civilization
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Mr Darmawan Abinugroho
Date Deposited:	20 Apr 2022 06:37
Last Modified:	20 Apr 2022 06:39
URI:	http://repository.unsri.ac.id/id/eprint/69242

Actions (login required)

View Item