scholarly journals PENDETEKSIAN KECURANGAN LAPORAN KEUANGAN DENGAN BENISH M-SCORE PADA PERUSAHAAN YANG TERDAFTAR DI BURSA EFEK INDONESIA

Solusi ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Amerti Irvin Widowati ◽  
Linda Ayu Oktoriza

<p>Beneish M-Score adalah suatu teknik analisis laporan keuangan dapat dit-erapkan untuk mendeteksi kecurangan laporan keuangan berupa manipulasi laba earning overstatement. Pernyataan ini telah dijawab oleh Messod D. Beneish, seorang profesor di Indiana University yang melakukan penelitian atas perbedaan kuantitaif antara perusahaan yang teridentifikasi telah melakukan manipulasi laba dan perusahaan yang teridentifikasi tidak melakukan manipulasi laba.</p><p>Objek penelitian ini adalah perusahaan sektor Penghasil bahan baku dan manufaktur yang terdaftar di BEI tahun 2019. Terdapat 178 perusahaan yang menjadi sampel pada penelitian ini. Teknik penentuan sampel menggunakan non probability-purposive judgement sampling. Metode pengumpulan data menggunakan metode dokumentasi. Metode analisis data dengan deskriptif kuantitatif menggunakan rasio yang dikemukakan oleh Messod D.Beneish. Terdapat 5 variabel pengukuran yaitu Days’ Sales In Receivables Index (DSRI), Gross Margin Index (GMI), Asset Quality Index (AQI), Sales Growth Index (SGI), dan Total Accrual To Total Assets Index (TATA).</p><p>Hasil dari penelitian ini adalah: 1) terdapat 2 perusahaan yang tergoLong manipulator yang ditunjukkan dengan masuk kategori manipulator pada 3 kategori dari 5 kategori yang diukur; 2)sedangkan lainnya termasuk dalam kategori Non manipulator dan Grey company.</p><p align="left"> </p><p align="left"> </p><p align="left">Kata kunci: Beneish M-Score, Laporan keuangan</p>

2020 ◽  
Vol 7 (1) ◽  
pp. 7
Author(s):  
Fitri Aulia Rachmi ◽  
Djoko Supatmoko ◽  
Bunga Maharani

Penelitian ini bertujuan menguji dan menganalisis penggunaan model Beneish M-Score untuk mendeteksi financial statement fraud. Data yang digunakan adalah data sekunder berupa laporan keuangan perusahaan pertambangan terbuka di Indonesia. Metode penelitian yang digunakan adalah metode kuantitatif dengan analisis diskriminan. Metode analisis diskriminan digunakan untuk menganalisa hubungan antara model Beneish M-Score dengan financial statement fraud dengan cara melihat faktor atau variabel mana yang secara nyata dapat mempengaruhi variabel dependen. Pengaplikasian analisis diskriminan dilakukan untuk menguji variabel independen manakah yang secara akurat dapat membedakan sampel laporan keuangan yang diduga telah dimanipulasi dan laporan keuangan yang diduga tidak dimanipulasi. Hasil penelitian menunjukkan bahwa variabel yang mampu membedakan sampel laporan keuangan yang diduga telah dimanipulasi dan diduga tidak dimanipulasi adalah variabel Days Sales Receivable Index (DSRI), Gross Margin Index (GMI), Sales Growth Index (SGI), dan Total Accrual to Total Asset (TATA) sementara variabel Asset Quality Index (AQI), Depreciation Index (DEPI), Sales and General Administration Expenses Index (SGAI), Leverage Index (LVGI) terbukti tidak mampu membedakan laporan keuangan yang diduga telah dimanipulasi dan diduga tidak dimanipulasi.


2020 ◽  
Vol 7 (02) ◽  
pp. 235-246
Author(s):  
Nurina Prawinin Tyas ◽  
Nurmala Ahmar ◽  
M. Ardiansyah Syam

ABSTRACT        This study aims to test and prove the empirical evidence of the Financial Distress Prediction Model of Family Companies in Indonesia with the Beneish Ratio Index. The sample used in this study is a group of family companies in Indonesia which are listed on the Indonesia Stock Exchange with an observation period of 31 December 2014 to 2018. The research method used is a quantitative method with a survey approach for secondary data. The Days Sales in Receivable Index (DSRI), Sales Growth Index (SGI), Sales General and Administrative Index (SGAI), and Leverage Index (LVGI) variables do not differ in the treatment of the Beneish Model components based on the Financial Distress status of the Family Group Company. Variable Gross Margin Index (GMI), Asset Quality Index (AQI), Depreciation Index (DEPI), and Total Accruals to Total Assets Index (TATA) differ in the treatment of the Beneish Model component based on the Financial Distress status of the Family Company Group. This research contributes to the parties concerned with the prediction of financial distress, such as auditors and the government in assessing the potential for financial distress in the company. ABSTRAK         Studi ini bertujuan untuk menguji dan membuktikan bukti empiris Model Prediksi Financial Distress Grup Perusahaan Keluarga Di Indonesia Dengan Beneish Ratio Index. Sampel yang digunakan dalam penelitian ini adalah Grup perusahaan keluarga di Indonesia yang terdaftar di Bursa Efek Indonesia dengan periode pengamatan 31 Desember 2014 hingga 2018. Metode penelitian yang digunakan adalah metode kuantitatif dengan pendekatan survey untuk data sekunder. Variabel Days Sales in Receivable Index (DSRI), Sales Growth Index (SGI), Sales General and Administrative Index (SGAI), dan Leverage Index (LVGI) tidak ada perbedaan perlakuan komponen Beneish Model berdasarkan status Financial Distress pada Grup Perusahaan Keluarga. Variabel Gross Margin Index (GMI), Asset Quality Index (AQI), Depreciation Index (DEPI), dan Total Accruals to Total Assets Index (TATA) ada perbedaan perlakuan komponen Beneish Model berdasarkan status financial distress pada Grup Perusahaan Keluarga. Riset ini memberikan panduan kepada pihak-pihak yang berkepentingan terhadap memprediksi financial distress yang akan terjadi dalam perusahaan ataupun industri, pihak yang berkepentingan seperti Auditor dan Pemerintahan. JEL Classification : G32, M41


2021 ◽  
Author(s):  
Firdaus Adi Sentari ◽  
◽  
Fitriana Fitriana ◽  
Didin Saepudin ◽  
◽  
...  

Kasus kecurangan laporan keuangan (fraud) yang terjadi di dunia terus mengalami peningkatan, begitu juga di Indonesia. Kecurangan yang terjadi memberikan dampak yang besar bagi perusahaan maupun bagi pengguna laporan keuangan lainnya. Maka dari itu diperlukan suatu alat deteksi yang bisa digunakan untuk mengetahui kemungkinan dilakukannya tindakan fraud sebagai upaya mengurangi kerugian yang timbul akibat kecurangan tersebut, salahsatunya metode Beneish Ratio Index. Penelitian ini dilakukan untuk mendeskripsikan dan menguji pengaruh Days Sales Receivable Index (DSRI), Gross Margin Index (GMI), Asset Quality Index (AQI), Sales Growth Index (SGI) dan Depreciation Index (DEPI) yang menjadi variabel Beneish Ratio Index terhadap pendeteksian kecurangan laporan keuangan (fraud) pada perusahaan manufaktur sub sektor kimia dan farmasi yang terdaftar di BEI tahun 2016-2019. Metode penelitian yang digunakan adalah metode deskriptif dan verifikatif. Teknik analis data menggunakan analisis regresi logistik dengan menggunakan software SPSS 21. Hasil penelitian membuktikan bahwa: (1) Rata-rata perusahaan yang menjadi sampel penelitian memiliki kondisi DSRI, GMI, AQI, SGI dan DEPI yang kurang baik; (2) Semakin tinggi DSRI, GMI, AQI, SGI dan DEPI maka semakin tinggi terdeteksinya kecurangan laporan keuangan; (3) Tinggi rendahnya DSRI tidak ada pengaruhnya terhadap terdeteksinya kecurangan laporan keuangan; (4) Semakin tinggi GMI maka semakin tinggi terdeteksinya kecurangan laporan keuangan; (5) Tinggi rendahnya AQI tidak ada pengaruhnya terhadap terdeteksinya kecurangan laporan keuangan; (6) Semakin tinggi SGI maka semakin tinggi terdeteksinya kecurangan laporan keuangan; (7) Tinggi rendahnya DEPI tidak ada pengaruhnya terhadap terdeteksinya kecurangan laporan keuangan.


2020 ◽  
Vol 7 (02) ◽  
pp. 235-246
Author(s):  
Nurina Prawinin Tyas ◽  
Nurmala Ahmar ◽  
M. Ardiansyah Syam

ABSTRACT        This study aims to test and prove the empirical evidence of the Financial Distress Prediction Model of Family Companies in Indonesia with the Beneish Ratio Index. The sample used in this study is a group of family companies in Indonesia which are listed on the Indonesia Stock Exchange with an observation period of 31 December 2014 to 2018. The research method used is a quantitative method with a survey approach for secondary data. The Days Sales in Receivable Index (DSRI), Sales Growth Index (SGI), Sales General and Administrative Index (SGAI), and Leverage Index (LVGI) variables do not differ in the treatment of the Beneish Model components based on the Financial Distress status of the Family Group Company. Variable Gross Margin Index (GMI), Asset Quality Index (AQI), Depreciation Index (DEPI), and Total Accruals to Total Assets Index (TATA) differ in the treatment of the Beneish Model component based on the Financial Distress status of the Family Company Group. This research contributes to the parties concerned with the prediction of financial distress, such as auditors and the government in assessing the potential for financial distress in the company. ABSTRAK         Studi ini bertujuan untuk menguji dan membuktikan bukti empiris Model Prediksi Financial Distress Grup Perusahaan Keluarga Di Indonesia Dengan Beneish Ratio Index. Sampel yang digunakan dalam penelitian ini adalah Grup perusahaan keluarga di Indonesia yang terdaftar di Bursa Efek Indonesia dengan periode pengamatan 31 Desember 2014 hingga 2018. Metode penelitian yang digunakan adalah metode kuantitatif dengan pendekatan survey untuk data sekunder. Variabel Days Sales in Receivable Index (DSRI), Sales Growth Index (SGI), Sales General and Administrative Index (SGAI), dan Leverage Index (LVGI) tidak ada perbedaan perlakuan komponen Beneish Model berdasarkan status Financial Distress pada Grup Perusahaan Keluarga. Variabel Gross Margin Index (GMI), Asset Quality Index (AQI), Depreciation Index (DEPI), dan Total Accruals to Total Assets Index (TATA) ada perbedaan perlakuan komponen Beneish Model berdasarkan status financial distress pada Grup Perusahaan Keluarga. Riset ini memberikan panduan kepada pihak-pihak yang berkepentingan terhadap memprediksi financial distress yang akan terjadi dalam perusahaan ataupun industri, pihak yang berkepentingan seperti Auditor dan Pemerintahan. JEL Classification : G32, M41


2018 ◽  
Vol 13 (04) ◽  
Author(s):  
Hantono .

This study aims to detect the possibility of fraud on BUMN companies listing on the Indonesia Stock Exchange 2012-2016 by using eight of Beneish's Model.The object of this study is all BUMN companies listing on the Indonesia Stock Exchange which publishes audited financial statements for fiscal year 2012 - 2016, which amounted to 20 (twenty) companies. The sampling technique is by using purposive sampling method where the sample is determined based on certain criteria determined by the researcher and has limitations in terms of generalization. The sample of research is 50 (fifty companies) Data collection method using documentation method Data analysis technique used is descriptive quantitative analysis using Beneish Ratio Index Variable in this research is Days' Sales In Receivables Index (DSRI), Gross Margin Index ( GMI), Asset Quality Index (AQI), Sales Growth Index (SGI), and Total Accruals To Total Assets Index (TATA)) Based on the eight models of Beneish's Model, the Days' Sales In Receivables Index (DSRI), Gross Margin Index GMI), Asset Quality Index (AQI), Sales Growth Index (SGI), and Total Accruals To Total Assets Index (TATA) have no effect on fraud.Keywords:   financial statement, fraud, Beneish’s Model


2021 ◽  
Vol 9 (1) ◽  
pp. 1
Author(s):  
Aris Sanulika ◽  
Wahyu Nurul Hidayati

ABSTRACTFraudulent Financial Reporting is a deliberate attempt by a company to deceive and mislead users of financial statements, especially investors and creditors, by presenting and manipulating the material value of financial statements. This study aims to determine how the auditor's opinion can moderate the comparative analysis of the pentagon fraud with the beneish ratio in the detection of fraudulent financial reporting. The type of data used in this study is comparative quantitative data. The data source in this study is secondary data. The population in this study are banking companies listed on the IDX. With a sample of 16 publicly traded companies engaged in financial and banking institutions and were listed on the Indonesia Stock Exchange in 2014-2017. The results of this study indicate that of 64 samples there were 12.5% which indicated that the financial statements had been manipulated. Auditor opinions can increase the influence of Financial Stability, external auditor quality, change in auditor, change of directors, days sales in receivables index, sales gross margin Index, Asset Quality Index, growth index, depreciation index, sales, and general administration expenses index, leverage index, total accrual to fraudulent financial reporting. Beneish Ratio affects Fraudulent Financial Reporting while Fraud Pentagon does not affect Fraudulent Financial Reporting


2021 ◽  
Author(s):  
Ponny Harsanti ◽  
Ulva Rizky Mulyani

Fraudulent financial statements are disclosures of a company’s financial condition which are intentionally made inaccurate by eliminating values. This study aimed to examine the effect of using the Beneish M-Score model against fraud reports of manufacturing companies listed in the Indonesian Stock Exchange in 2016 -2018. Purposive sampling was used and the sample consisted of 69 companies. The results showed that the Days Sales in Receivables Index, Gross Margin Index and Total Accrual to Total Asset had a significant positive effect on financial statement fraud, while the Asset Quality Index, Sales Growth Index, Depreciation Index, Sales General and Administrative Expenses Index, and Leverage Index did not affect fraudulent financial statements. Keywords: fraud, Beneish, logistic regression


2019 ◽  
Vol 8 (2) ◽  
pp. 66
Author(s):  
Rezky Febriendy Darise

Fraud is an action taken intentionally and it is done for personal or other people's purposes, where the action has caused harm to certain parties or certain institutions. Misstatements contained in fraudulent financial statements are intentional misstatements to deceive users of financial statements. The source of this misstatement includes manipulation or falsification of accounting records, intentional misstatements or omissions from financial statements, and / or incorrect application of accounting principles. In Indonesia, accounting fraud also occurs at the company level, both private and government companies. On December 6, 2012, the announcement of Indonesia's score in the Corruption Perception Index (CPI) was 32 and ranked 118th out of 176 countries which measured the level of corruption (Transparency International, 2012). In 2001, a fraud scandal occurred by PT Kimia Farma Tbk. PT Kimia Farma is a state-owned company whose shares have been traded on the exchange to become public company. Based on indications by the Ministry of BUMN and Bapepam's examination, it was found that there were misstatements in the financial statements which resulted in overstatement of net income for the year ended 31 December 2001 of Rp. 32.7 billion, which represented 2.3% of sales and 24.7% from net income. The author's purpose of this study is to discuss about detecting fraud in financial statements by using 5 (five) of the 8 (eight) Beneish ratio indices, because Beneish's research states that the Days Sales in Receivables Index (DSRI) ratio index, the Gross Margin Index ( GMI), Asset Quality Index (AQI), Sales Growth Index (SGI), and Total Accrual to Total Asst Index (TATA) have significant results to detect financial report manipulation.


Risks ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 116
Author(s):  
Andrada-Ioana Sabău (Popa) ◽  
Codruța Mare ◽  
Ioana Lavinia Safta

Tax avoidance is one of the most frequent reasons for which companies tend to resort to creative accounting techniques. The purpose of the study is to identify which of the eight-variables from the Beneish influences the most or least the outcome of the final score, as a percent, by developing a statistical model. The sample was selected from the Bucharest Stock Exchange and consists of 66 companies traded on the main market, for the years 2015–2019. The results show that from the total of the eight variables, GMI (Gross Margin Index), AQI (Asset Quality Index), DEPI (Depreciation Index) and TATA (Total Accruals to Total Assets) are significantly influencing the probability to commit fraud. The developed model is validated with only 10% of the non-fraud companies being mistakenly considered as fraud based on our model and vice versa.


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