Evaluasi Kinerja Model Klasifikasi Machine Learning untuk Deteksi Fraud pada Data Transaksi Tidak Seimbang

Kaslin Yulianty ; Abidin ; Dodo Zaenal ; Devitra ; Joni
Prosiding Seminar Nasional Ilmu Teknik 📅 2025 Vol 2, No 2 🔗 DOI: 10.61132/prosemnasproit.v2i2.152
Abstract
Private vehicles are a frequently used mode of transportation because they are considered more practical. However, using private vehicles carries several risks, such as traffic accidents due to drivers losing focus on the road due to other activities, such as making calls on smartphones, drinking, or operating the radio. Approximately 90% of accidents are caused by human error. Convolutional Neural Network (CNN) is a type of neural network commonly used on image data. CNN is often used for image classification due to its high performance and accuracy. Therefore, this study aims to analyze the performance of CNN for the classification of distracted driving activities. The results show that the CNN model is able to effectively classify images of distracted driving activities, with an accuracy of approximately 99% across all datasets and across all input image size variations. Furthermore, the results of this study also show that differences in right-hand and left-hand drive datasets do not significantly affect model accuracy. Variations in input image size also do not significantly affect model accuracy, but do affect the training duration.
Keywords
Balanced Accuracy; Credit Card Transactions; Fraud Detection; ROC-AUC; SMOTE
How to Cite

Kaslin Yulianty, et al. (2025). Evaluasi Kinerja Model Klasifikasi Machine Learning untuk Deteksi Fraud pada Data Transaksi Tidak Seimbang. Prosiding Seminar Nasional Ilmu Teknik, 2(2). https://doi.org/10.61132/prosemnasproit.v2i2.152

Kaslin Yulianty; Abidin, Dodo Zaenal; Devitra, Joni, "Evaluasi Kinerja Model Klasifikasi Machine Learning untuk Deteksi Fraud pada Data Transaksi Tidak Seimbang," Prosiding Seminar Nasional Ilmu Teknik, vol. 2, no. 2, 2025.

Kaslin Yulianty; Abidin, Dodo Zaenal; Devitra, Joni. "Evaluasi Kinerja Model Klasifikasi Machine Learning untuk Deteksi Fraud pada Data Transaksi Tidak Seimbang." Prosiding Seminar Nasional Ilmu Teknik, vol. 2, no. 2, 2025.

Kaslin Yulianty; Abidin, Dodo Zaenal; Devitra, Joni. "Evaluasi Kinerja Model Klasifikasi Machine Learning untuk Deteksi Fraud pada Data Transaksi Tidak Seimbang." Prosiding Seminar Nasional Ilmu Teknik 2, no. 2 (2025).

Kaslin Yulianty, et al. (2025) 'Evaluasi Kinerja Model Klasifikasi Machine Learning untuk Deteksi Fraud pada Data Transaksi Tidak Seimbang', Prosiding Seminar Nasional Ilmu Teknik, 2(2). doi: 10.61132/prosemnasproit.v2i2.152.

Kaslin Yulianty; Abidin, Dodo Zaenal; Devitra, Joni. Evaluasi Kinerja Model Klasifikasi Machine Learning untuk Deteksi Fraud pada Data Transaksi Tidak Seimbang. Prosiding Seminar Nasional Ilmu Teknik. 2025;2(2).

Artikel Terkait

Pengolahan Citra Digital Kamera Multispektral Berbasis Drone dengan Artificial Neural Network (ANN) untuk Identifikasi Cekaman Air pada Tanaman Padi

Shahiban Muzaki

Analisis Tingkat Kepuasan Pengguna Pada Website Smp Negeri 5 Kota Jambi Menggunakan Model Webqual 4.0 Dan Importance Performance Analisis (Ipa)

Usi Nofriana; Nurhadi Nurhadi; Joni Devitra

Implementasi Simple Additive Weighting Untuk Rekomendasi Karir Mahasiswa Berdasarkan Hasil Tes Psikologi

Moh Nur Iman Siyus Setyowati; Dihin Muriyatmoko; Eko Prasetio Widhi

Analisis Performa Convolutional Neural Network untuk Klasifikasi Aktivitas Pengemudi Terganggu

Zufar Abdullah Rabbani; Wahyu Syaifullah J S; Alfan Rizaldy Pratama

Analisis Korelasi Faktor Gaya Hidup Terhadap Indikator Kesehatan Menggunakan Metode Shapiro-Wilk dan Spearman

Mohd Fadli Ariansyah; Eka Pandu Cynthia

Pengukuran Tingkat Kesiapan Pasien RSUD Abdul Manap Terhadap Mobile JKN Menggunakan Metode HOT-Fit

Titania Arida Nandini; Setiawan Assegaff; Nurhadi Nurhadi
Tren Sitasi Jurnal