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All Journal OIKOS: Jurnal Kajian Pendidikan Ekonomi dan Ilmu Ekonomi ULIL ALBAB
Resky Awalia
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Studi Literatur: Apakah Earnings Management Termasuk Tindakan Kecurangan? Resky Awalia; Rafqah Annisa Kusumaningrum; Natasya Salsabila Nafis
ULIL ALBAB : Jurnal Ilmiah Multidisiplin Vol. 2 No. 2: Januari 2023
Publisher : CV. Ulil Albab Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/jim.v2i2.1325

Abstract

Banyak yang berpendapat bahwa manajemen laba merupakan tindakan kecurangan. Studi literatur ini menjelaskan dan menggambarkan masalah dari perspektif luar manajemen laba. Metode penelitian ini menggunakan kualitatif dengan studi literatur. Hasil penelitian ini menunjukkan manajemen laba bukanlah kecurangan. Kecurangan merupakan “tindakan penipuan kriminal” atau “perbuatan kecurangan yang dapat di hukum”. Manajemen laba merupakan batasan yang sah, menyiratkan bahwa penyimpangan pendapatan yang dilaporkan dari mandasari atau pendapatan ekonomi karena manajemen laba adalah sah atau disahkan oleh standar akuntansi dan hukum perusahaan.
PREDIKSI FINANCIAL DISTRESS MENGGUNAKAN ARTIFICIAL NEURAL NETWORK (ANN) PADA PERUSAHAAN PERBANKAN YANG TERDAFTAR DI BURSA EFEK INDONESIA (BEI) PERIODE 2017-2021 Resky Awalia; Farida Titik Kristanti
OIKOS: Jurnal Kajian Pendidikan Ekonomi dan Ilmu Ekonomi Vol 7 No 2 (2023): OIKOS: Jurnal Kajian Pendidikan Ekonomi dan Ilmu Ekonomi
Publisher : Fakultas Keguruan Dan Ilmu Pendidikan Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/oikos.v7i2.7924

Abstract

The Earnings Per Share (EPS) value from 2017 to 2021 shows how banking companies listed on the Indonesia Stock Exchange (IDX) did. Several banking companies experienced a decrease in EPS values from 2017 to 2021 and even obtained a negative EPS value which could indicate that the company identified as having a poor profit growth value and even triggering financial distress. This study plans to foresee the event of monetary trouble in financial organizations recorded on the Indonesia Stock Trade for the 2017-2021 period by utilizing a Fake Brain Organization. The info boundaries utilized are monetary proportions, specifically the ongoing proportion, return on resources, obligation to-resource proportion, and complete resource turnover. The results of the study show that the four ratios are suitable for use as input parameters because they provide significant differences between companies that declared distress and non-distress. This study's prediction process utilized an ANN architecture consisting of 20 neurons as the input layer, 5 neurons as the hidden layer, and 1 neuron as the output layer, achieving the highest accuracy of 87 percent. Keywords: Artificial Neural Network, Financial Distress, Financial Ratios.
Co-Authors Farida Titik Kristanti Natasya Salsabila Nafis Rafqah Annisa Kusumaningrum