Credit Card Fraud Detection Using AES Technic

Sudha, C.; Akila, D.

doi:10.1007/978-981-15-3284-9_10

Cited by 3 publications

(1 citation statement)

References 30 publications

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“…Beberapa penelitian tentang penggunaan algoritma kNN ini telah dilakukan untuk beberapa bidang seperti kesehatan yang digunakan untuk memprediksi penyakit [5,6,7]. Dalam bidang keuangan diterapkan untuk memprediksi kelancaran pembayaran kredit [8,9] maupun mendeteksi kecurangan [10,11]. Selain untuk bidang-bidang tersebut, penggunaan algoritma ini juga telah diterapkan untuk mengklasifikasikan dokumen atau teks yang lebih dikenal dengan text mining [12,13].…”

Section: Pendahuluanunclassified

Penerapan Data Mining untuk Memprediksi Siswa Berprestasi dengan Menggunakan Algoritma K Nearest Neighbor

Widaningsih¹

2022

JATISI

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Proses penentuan siswa berprestasi di SMK Tunas Sinar Mandiri Cianjur tidak hanya ditentukan dari nilai akademik saja, tetapi dipertimbangkan beberapa aspek non akademik seperti jenis kelamin, keaktifan ekstrakulikuler, presensi, dan kepribadian. Untuk nilai akademik, diambil dari nilai mata pelajaran produktif kelas X dan XI. Untuk memprediksi siswa mana yang berprestasi di kelas XII dapat diterapkan teknik data mining dengan menggunakan algoritma k nearest neighbor (kNN) dengan k = 1. Tahapan proses data mining mengikuti tahapan dalam Knowledge Discovery di Databases (KDD). Tahapan ini dimulai dari selection, preprocessing, transformation, data mining, dan evaluation/interpretation. Proses transformasi data menggunakan metoda min- max dan rumus jarak yang digunakan yaitu jarak euclidian. Pembuatan aplikasi data mining ini mengikuti paradigma waterfall. Dari hasil analisis dan desain dengan menggunakan unified modeling langunge (UML) dihasilkan beberapa halaman utama yaitu kelola data siswa, penentuan variabel dan bobot variabel, Dengan penerapan teknik data mining ini dapat mempermudah pihak sekolah mempersiapkan siswa yang akan mendapatkan beasiswa.

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Section: Pendahuluanunclassified

Penerapan Data Mining untuk Memprediksi Siswa Berprestasi dengan Menggunakan Algoritma K Nearest Neighbor

Widaningsih¹

2022

JATISI

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An Empirical Analysis of Machine Learning Techniques in Phishing E-mail detection

Livara

Hernandez

2022

2022 International Conference for Advancement in Technology (ICONAT)

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Analysis of Credit Card Fraud Detection Using Machine Learning Algorithms

Kumar

Arumugam

2022

IJARSCT

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For the past decade of year’s credit card holders are facing a problem that the card had been swiped and cash has been withdrawn in an ATM (Automatic Teller Machine) or it has been swiped in a shopping mall by purchasing a product as creating a fake credit card. These transactions are considered as illegal activity, it is also one of the cybercrime theft activities. Credit card fraud detection has been increasing highly in the world. Fake credit cards can be tackled by applying data science along various machine learning algorithms. This research work focus on analysis of various credit card fraud transaction using machine learning algorithms. Also, this research focuses on detecting the fake credit cards by approaching Artificial Intelligence (AI), Data mining and Big data analytics etc. by using machine learning algorithms. Machine learning algorithms are applied by training the dataset which are collected from the fake credit dataset and original credit card dataset. Computer operations are handled by the data as data’s are ruling the world. Predicted card details are stored on the server of the banker. From the server information has been passed to the cybercrime in order to catch the culprit. Different kinds of machine learning algorithms that has been used for credit card fraud detection has been studied on which it gives the more precision.

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Credit Card Fraud Detection Using AES Technic

Cited by 3 publications

References 30 publications

Penerapan Data Mining untuk Memprediksi Siswa Berprestasi dengan Menggunakan Algoritma K Nearest Neighbor

Penerapan Data Mining untuk Memprediksi Siswa Berprestasi dengan Menggunakan Algoritma K Nearest Neighbor

An Empirical Analysis of Machine Learning Techniques in Phishing E-mail detection

Analysis of Credit Card Fraud Detection Using Machine Learning Algorithms

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