Analysis System of Fraudulent Financial Statement Through Ratio Analysis Using Support Vector Machine
MUHAMMAD NOVARIO EKAPUTRA
Informasi Umum
Kode
19.04.5092
Klasifikasi
006.31 - Machine Learning
Jenis
Karya Ilmiah - Skripsi (S1) - Reference
Subjek
Machine Learning
Dilihat
59 kali
Informasi Lainnya
Abstraksi
In this digital era, fraud has been rampant in various sectors. Fraud is not difficult to do with a variety of specific purposes, including fraudulent financial statements of banking companies or not. With the proliferation of fraudulent financial statements, many parties, especially companies that experience serious losses. Not much research has been done to detect forgery of financial statements by analyzing using a classification model, especially in the banking world. In this study the authors conducted a financial ratio analysis which is still part of a financial statement to be a feature. The author finds that anomalies in a financial ratio can predict the potential for falsification of financial statements. The five features that were most influential were found to detect the potential for counterfeiting.
Koleksi & Sirkulasi
Seluruh 1 koleksi sedang dipinjam
Anda harus log in untuk mengakses flippingbook
Pengarang
| Nama | MUHAMMAD NOVARIO EKAPUTRA |
| Jenis | Perorangan |
| Penyunting | YULIANT SIBARONI, NIKEN DWI WAHYU CAHYANI |
| Penerjemah |
Penerbit
| Nama | Universitas Telkom, S1 Informatika |
| Kota | Bandung |
| Tahun | 2019 |
Sirkulasi
| Harga sewa | IDR 0,00 |
| Denda harian | IDR 0,00 |
| Jenis | Non-Sirkulasi |
