scholarly journals Apakah PT Rekayasa Industri Merekayasa Laporan Keuangan? Sebuah Analisis Menggunakan Beneish M-Score

Jurnalku ◽  
2021 ◽  
Vol 1 (4) ◽  
pp. 278-286
Author(s):  
Kodirin
Keyword(s):  
Financial Distress ◽  
Secondary Data ◽  
Financial Statements ◽  
Financial Statement ◽  
Financial Report ◽  
Gray Area ◽  
Financial Difficulties ◽  
Bad Company ◽  
Score Model ◽  
Ammonia Plant

Penelitian ini bertujuan untuk mengetahui apakah laporan keuangan PT Rekayasa Industri (Rekind) tahun 2018 terindikasi dimanipulasi atau tidak.  Penelitian ini bersifat deskriptif dengan menggunakan data sekunder. Laporan keuangan komparatif Rekind tahun 2018 yang tersedia di website Rekind menjadi objek penelitian ini.  Rekind mengalami kesulitan keuangan akibat perselisihan dengan PT Amara Panca Utama terkait proyek Banggai Ammonia Plant (BAP).  Model Beneish M-Score digunakan untuk mengukur potensi manipulasi pada laporan keuangan. Dugaan penelitian ini adalah PT Rekayasa Industri terindikasi memanipulasi laporan keuangan tahun 2018 mengingat kesulitan keuangan yang dialami. Hasil analisis menyimpulkan bahwa berdasarkan model Beneish M-Score laporan keuangan Rekind tahun 2018 terindikasi telah dimanipulasi.  Kesimpulan ini diambil berdasarkan nilai Beneish M-Score laporan keuangan Rekind tahun 2018 sebesar -1,49, lebih besar daripada nilai patokan, -2,22.  Temuan ini sejalan dengan temuan Y. A. Nugroho (2017) bahwa perusahaan melakukan manipulasi laporan keuangan sebagai salah satu cara untuk memperbaiki kondisi perusahaan yang buruk akibat mengalami kesulitan keuangan dan Haq et al (2017) bahwa financial distress berpengaruh negatif terhadap integritas laporan keuangan.  Terdapat dua rasio yang mengindikasikan telah dimanipulasi yaitu GMI dan TATA; tiga  rasio yang mengindikasikan tidak dimanipulasi yaitu  DSRI, AQI, dan SGAI; dan tiga rasio yang berada pada “grey area” yaitu SGI, DEPI, dan LVGI.   This study aims to test whether there is an indication of manipulation in the financial statements of PT Rekayasa Industri (Rekind) in 2018 or not. This research is descriptive using secondary data. The object of this research is the 2018 Rekind comparative financial Report available on the Record website. Rekind has experienced financial difficulties due to disputes with PT Amara Panca Utama regarding the Project of the Banggai Ammonia Plant. The method used to measure manipulation potential is the Beneish M-Score model. Rekind allegedly conducted manipulation to "improve" financial statements in 2018 as a way out of financial difficulties that hit. The results of the analysis concluded that the account was indicated to carry out manipulation for the financial statements of 2018. This conclusion was taken based on the value of the Beneish M-score of the 2018 financial statement of -1.49, greater than the benchmark value, -222. This finding is in line with the research before which concludes that the company conducts financial statements manipulation as one way to cover the condition of a bad company due to experiencing financial difficulties and that financial distress influencing the integrity of financial statements negatively. There are two indexes that are indicated to be manipulated, namely GMI and TATA; three indexes indicated that are not manipulated, namely DSRI, AQI, and SGAI; and three indexes that are on gray area, SGI, DEPI, and LVGI.

scholarly journals Analysis of Accuracy Level of Altman Z-Score Model and Springate Model in Measuring the Potential of Financial Distress in Plantations Industries

2019 ◽  
pp. 16-25
Keyword(s):  
Financial Performance ◽  
Financial Distress ◽  
Secondary Data ◽  
Financial Data ◽  
Z Score ◽  
Financial Difficulties ◽  
Accuracy Level ◽  
Score Model

This study aimed to analyze the level of bankruptcy using Altman Z-Score model of modifications and models Springate, the Plantations Company period 2014-2017. The data used in this research is secondary data, financial data Plantations Company taken from the site www.idx.co.id. Based on the results of this study show that the model of the Altman Z-Score modification Plantations Industries was having financial difficulties which would be potentially bankrupt, it can be seen from the Z-Score of less than 1.1 in the period 2014-2017 and no different from using a model that generates value Springate S-Score <0.862 means that the financial performance Plantations company are experiencing financial difficulties during the 2014-2017 period and potentially going bankrupt.

scholarly journals Analisis Potensi Kebangkrutan: Perbandingan Model Altman dengan Zavgren

PERSPEKTIF ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 447-452
Author(s):  
Wardayani Wardayani ◽  
Azhar Maksum
Keyword(s):  
Stock Exchange ◽  
Secondary Data ◽  
Identification Problem ◽  
Bankruptcy Prediction ◽  
Logit Analysis ◽  
Z Score ◽  
Gray Area ◽  
Financial Difficulties ◽  
Score Model ◽  
Analysis Models

This study is aimed to compare two methods to determine the potential for bankruptcy of the company. The method used is the Altman (Z Score) and Zavgren (Logit Analysis) models. The Z Score model is a method to predict the financial difficulties, where the score value on the Altman Z Score classifies whether a company being bankrupt or not. Zavgren developed bankruptcy prediction model with Logit Analysis which divide bankruptcy classifications. The identification problem in this research are the decline in profits occurred from the end of 2016 until 2018, and the mismatch of the increase in profits to the increase the number of assets in the Cosmetics Company, through the use of secondary data from the Indonesia Stock Exchange of companies with code MRAT, KINO, TCID, dan MBTO. Thus, the financial state of cosmetics companies listed on the Indonesia Stock Exchange (BEI) during the 2016 to2018, according to the Altman Z Score model can be categorized into 2 criteria, they are: Gray Area; MBTO and Sound Area: MRAT, KINO and TCID. Meanwhile, based on the Zavgren model, MRAT, KINO, TCID and MBTO were declared as Sound.

scholarly journals Dewan Komisaris Independen sebagai Pemoderasi Pengaruh Financial Distress pada Kecepatan Publikasi Laporan Keuangan

2018 ◽  
pp. 2204
Author(s):  
Ni Putu Wanda Anggeliana Putri ◽  
Yenni Latrini
Keyword(s):  
Financial Distress ◽  
Sampling Technique ◽  
Financial Statements ◽  
Financial Statement ◽  
Financial Report ◽  
Asymmetry Of Information ◽  
The Public ◽  
Analysis Technique ◽  
The Impact ◽  
Positive Effect

Financial statement is an important instrument, because it can reduce the asymmetry of information that occurs between companies and the public. The velocity of publication of the financial statements may affect the users trust in the financial statements, this is because the information contained in the financial statements is required by the user to  take an economic decision. The purpose of this study is to prove empirically and explain the impact of financial distress on the velocity of publication of financial statements with independent board of commissioners as a moderator variabel. This research was conducted at company of consumer goods industry sector which listed in Bursa Efek Indonesia in 2012-2016. The samples of research taken with non probability sampling method with purposive sampling technique, so that obtained sample of 22 companies with 110 observation. Moderate Regression Analysis is a data analysis technique to obtain the results, the result of research is financial distress have positive effect on the velocity of publication of financial report and independent board of commissioner weaken the effect of financial distress on the velocity of publication of financial statement. Keywords: independent commissioners, financial distress, velocity of publication of the financial statements

scholarly journals Aplikasi Data Mining Pada Analisis Financial Distress Model Altman z-score Untuk Memprediksi Potensi Kebrangkutan Pada Industri Properti Go-Public Di Indonesia

Jurnal INFORM ◽  
2019 ◽  
Vol 4 (2) ◽  
Author(s):  
Billy Montolalu
Keyword(s):  
Financial Distress ◽  
Financial Management ◽  
Financial Statements ◽  
Gray Zone ◽  
Z Score ◽  
Financial Ratio ◽  
Financial Report ◽  
Industrial Operations ◽  
Report Data ◽  
Score Model

Early thought systems are needed in companies to overcome financial difficulties that can challenge industrial operations. Altman Z Score is one model that can be used to predict financial distress in a company by analyzing the company's financial statements. This research was conducted to analyze financial distress in property companies going public using the Altman Z Score model. In this model there are 5 financial ratio indicators that are used to predict financial distress. The financial report data used is the financial statements for 2015-2016 and there are 23 companies. The results of these calculations are then clustered with Fuzzy C-Means in two, namely safe zone and gray zone. Cluster validation testing uses the Silhouetee Index with a validation value of 0.9541 which indicates that the cluster process is valid. The results of this study indicate that there is one company that is included in the cluster gray zone, namely Intiland Development Tbk. Analysis of financial ratios found that the most influential is the variable X3 where the results of profits before tax are very small can affect payment of obligations. So it's easy to bring up financial distress conditions. And for those companies that have been in the gray zone condition, they are expected to be careful in financial management to anticipate financial distress.

scholarly journals ANALISIS PREDIKSI KEBANGKRUTAN MENGGUNAKAN MODEL ALTMAN Z-SCORE PADA PT EXPRESS TRANSINDO UTAMA (TAXI), TBK

2021 ◽  
Vol 1 (1) ◽  
pp. 36-44
Author(s):  
Anugrahwati Ariatma
Keyword(s):  
Secondary Data ◽  
Financial Statements ◽  
Analytical Tool ◽  
Operating Costs ◽  
Z Score ◽  
Financial Problems ◽  
Gray Area ◽  
A Value ◽  
Data Source ◽  
Score Model

This study aims to determine and analyze bankruptcy predictions at PT Express Transindo Utama (TAXI) Tbk using the Altman Z-score model, whether PT Express Transindo Utama (TAXI) Tbk is experiencing symptoms of financial problems and is in the bankrupt category or is included in the non-bankrupt category based on interpretation of the Altman Z-score model. The type of data used in this research is quantitative and the data source used is secondary data. The analytical tool in this study using the Altman Z-score model. From the results of the analysis based on calculations that have been carried out on the financial statements of PT Express Transindo Utama (TAXI) Tbk in 2015 and 2016 the company is included in the gray area category because the Z-score shows a value of 1.1 <Z <2.6. But in 2017 and 2018 the Z-score shows a Z value <1.1, so the company is in the bankrupt category or the company is experiencing serious financial problems. This is due to the larger current debt of the company compared to the current assets of the company as well as the less than maximum revenue earned and the large operating costs of the company. Companies can overcome this by reducing debt and increasing revenue.

scholarly journals Analisis Kebangkrutan dengan Model Altman Z-Score pada Perusahaan Sektor Industri Dasar dan Kimia di Bei Periode 2013-2014

2017 ◽  
Vol 26 (01) ◽  
pp. 136-163
Author(s):  
Suci Kurniawati
Keyword(s):  
Financial Distress ◽  
Quantitative Method ◽  
Stock Exchange ◽  
Secondary Data ◽  
Financial Statements ◽  
Z Score ◽  
Manufacturing Company ◽  
Score Model ◽  
Score Index

 The purpose of this study is to analyze the company's financial distress on basis industry and chemical sectors as many as 57 companies using the ALTMAN Z-Score model in 2013-2014. The data which used was secondary data, such as Financial Statements of manufacturing company publication issued by Indonesian Stock Exchange (BEI) and obtained by downloading the website: www.idx.com. This study uses descriptive quantitative method. The finding of Z-Score index in basis industry and chemical sector in 2013 is occupied by PT. Intan Wijaya Internasional Tbk on chemical subsector and 2014 is occupied by PT. Alakasa Industrindo Tbk on metal subsector and others, with the first highest rank and healthy condition, whereas the last and lowest rank on wood and processing sector  in 2013-2014 is PT. SLJ Global Tbk, with having financial distress condition. The findings of this study are not consistent or even  in accordance with the reality which shows that the Altman method can not be used as a tool to indicate a tendency towards company’s financial distress.

scholarly journals KETEPATAN MODEL PREDIKSI FINANCIAL DISTRESS PADA PERUSAHAAN RETAIL DI INDONESIA

2019 ◽  
Vol 4 (2) ◽  
pp. 117-127
Author(s):  
Kartikasari Kartikasari ◽  
Diyah Santi Hariyani
Keyword(s):  
Data Analysis ◽  
Financial Distress ◽  
Stock Exchange ◽  
Secondary Data ◽  
Financial Statements ◽  
Inferential Statistics ◽  
Accuracy Rate ◽  
Data Analysis Technique ◽  
Analysis Technique ◽  
Score Model

Abstract This study aims to analyze the condition of Financial Distress in retail companies listed on the Indonesian Stock Exchange in 2015-2017 using the Ohlson Model, Fulmer Model, CA-Score Model and Zavgren Model. The data used in this study was secondary data derived from the financial statements of retail companies found on the Indonesian Stock Exchange. The data analysis technique used was inferential statistics and Kruskal-Wallis test. The results of this study indicated that Ohlson's model is best at predicting Financial Distress in retail companies in Indonesia with an accuracy rate of 83.33%, CA-Score Model with 30% accuracy rate, as well as the Fulmer Model and Zavgren Model with an accuracy rate of 0.00 %    

scholarly journals PENERAPAN ALTMAN Z-SCORE DALAM MEPREDIKSI KEBANGKRUTAN PADA PT BANK DANAMON INDONESIA Tbk

2021 ◽  
Vol 5 (2) ◽  
pp. 60-66
Author(s):  
Eva Malina Simatupang
Keyword(s):  
Data Analysis ◽  
Balance Sheet ◽  
Secondary Data ◽  
Financial Statements ◽  
Financial Statement ◽  
Z Score ◽  
Financial Difficulties ◽  
Income Statement ◽  
Analysis Technique ◽  
Modification Method

The tittle of research was "The Implementation of Altman Z-Score in Predicting Bankruptcy at PT Bank Danamon Indonesia Tbk. The purpose of this research was conducted to determine the risk of bankruptcy of PT Bank Danamon Tbk according to Altman Z-Score. The population in this research was the financial statement of PT Bank DanamonTbk and the samples in this research were reports of financial position (balance sheet) and income statement of PT Bank Danamon Tbk period 2018 – 2020. The type of data used is secondary data and the data collection techniques used were the documentation of the financial statements published through website https://www.danamon.co.id . The data analysis technique uses descriptive statistics and the Altman Z-Score Modification method. Based on the results of the data processing obtained Z-Score results at 2018 was 2,251 ; at 2019 was 2,4424; at 2020 was 2,0052. Based on the results of data analysis, it can be concluded that PT Bank Danamon Tbk is in the gray zone because the standard cut off value is 1.1 < Z < 2.6. Bank Danamon is in a vulnerable condition (grey area) which means the company has the potential to experience financial difficulties but can still be overcome.

scholarly journals ANALISIS BENEISH M-SCORE UNTUK MENDETEKSI FINANCIAL STATEMENT FRAUD PADA PT. GARUDA INDONESIA Tbk PERIODE 2017-2019

2021 ◽  
Vol 6 (1) ◽  
pp. 44-51
Author(s):  
Dedi Julianto ◽  
Marjono Marjono ◽  
Aminullah Labangge
Keyword(s):  
Financial Statements ◽  
Financial Statement ◽  
Financial Statement Fraud ◽  
Gross Margin ◽  
Gray Area ◽  
Score Model

This study aims to detect financial statement fraud at PT. Garuda Indonesia in 2017-2019 used the Beneish M Score model and testing whether the Beneish M Score model can detect the occurrence of financial statement fraud at PT. Garuda Indonesia in 2018. The results of this study indicate that PT Garuda Indonesia was classified in the Gray criteria, that can be interpreted as manipulate or not manipule financial statements in 2017 and 2018 and classified in the criteria not manipulate financial statements in 2019. The results of this study also found that the Beneish M Score model could not accurately to detect the manipulation of financial statements at PT. Garuda Indonesia in 2018, because only two ratios are Gross Margin Index (GMI) and Days Sales in Receivable Index (DSRI) which detect manipulation of financial statements, so they are only classified in the gray area criteria

scholarly journals BANKRUPTCY ANALYSIS USING ALTMAN Z SCORE MODEL IN MANUFACTURING COMPANY AT INDONESIA STOCK EXCHANGE IN 2013-2014

2017 ◽  
Vol 5 (1) ◽  
pp. 1 ◽  
Author(s):  
Suci Kurniawati
Keyword(s):  
Financial Distress ◽  
Stock Exchange ◽  
Manufacturing Sector ◽  
Secondary Data ◽  
Financial Statements ◽  
Asia Pacific ◽  
Manufacturing Companies ◽  
Z Score ◽  
Score Model ◽  
Score Index

Analysis of financial distress is very important, because it enables to assess an indication of the company's financial distress, how the indication of financial distress using Altman z-score in industry manufacturing sector in 2013-2014, and whether the Altman z-score model can be used as a tool in predicting the tendency of financial distress. The purpose of this study is to analyze the financial distress of 125 manufacturing companies with different sectors and subsectors using Altman Z-Score model in 2013 and 2014. The source of data used was secondary data, such as financial statements of manufacturing companies’ publication issued by BEI and obtained from the internet by downloading through the website: www.idx.com. This study employed descriptive quantitative method. The findings of the Z-Score index on manufacturing companies in 2013 were occupied by PT. Intan Wijaya International Tbk. in chemical subsector, and in 2014 Herbal and Pharmaceutical Industry of PT Sido Muncul Tbk. was the first highest rank and healthy condition.  Whereas the lowest rank was PT. Asia Pacific Fiber Tbk. in textile and garment sub-sector in 2013 and 2014, having financial distress condition. The findings of this study are not consistent or even in accordance with the reality which shows that the Altman method cannot be used as a tool to indicate a tendency towards company’s financial distress.

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