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"ABSTRAKPenelitian ini bertujuan untuk menganalisis hubungan simultan antarakonservatisme akuntansi dan financial distress. Penelitian ini didasarkan padapemahaman bahwa antara kedua variabel tersebut dapat memiliki pengaruh satusama lain. Pengumpulan data menggunakan metode purposive sampling terhadapperusahaan manufaktur yang terdaftar di Bursa Efek Indonesia periode 2009-2010. Hasil penelitian menunjukkan bahwa konservatisme akuntansi tidakberpengaruh signifikan terhadap financial distress. Namun pada arah sebaliknya,financial distress berpengaruh signifikan negatif terhadap konservatismeakuntansi. Sehingga dapat disimpulkan bahwa antara konservatisme akuntansi danfinancial distress tidak memiliki hubungan dua arah.

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AbstractThe purpose of this research is to analyze the simultaneous relationship betweenaccounting conservatism and financial distress. This research is based on theunderstanding that between two variables may have influence with one another.Collecting data using a purposive sampling method to manufacturing companieslisted in Indonesian Stock Exchange period 2009-2010. The result suggests thataccounting conservatism have no significant on financial distress. In the oppositedirection, financial distress have significant negative impact on accountingconservatism. So, it can be concluded that the accounting conservatism andfinancial distress have no simultaneous relationship."

"Penelitian ini bertujuan untuk menganalisis hubungan simultan antara konservatisme akuntansi dan financial distress. Penelitian ini didasarkan pada pemahaman bahwa antara kedua variabel tersebut dapat memiliki pengaruh satu sama lain. Pengumpulan data menggunakan metode purposive sampling terhadap perusahaan manufaktur yang terdaftar di Bursa Efek Indonesia periode 2009- 2010. Hasil penelitian menunjukkan bahwa konservatisme akuntansi tidak berpengaruh signifikan terhadap financial distress. Namun pada arah sebaliknya, financial distress berpengaruh signifikan negatif terhadap konservatisme akuntansi. Sehingga dapat disimpulkan bahwa antara konservatisme akuntansi dan financial distress tidak memiliki hubungan dua arah.

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The purpose of this research is to analyze the simultaneous relationship between accounting conservatism and financial distress. This research is based on the understanding that between two variables may have influence with one another. Collecting data using a purposive sampling method to manufacturing companies listed in Indonesian Stock Exchange period 2009-2010. The result suggests that accounting conservatism have no significant on financial distress. In the opposite direction, financial distress have significant negative impact on accounting conservatism. So, it can be concluded that the accounting conservatism and financial distress have no simultaneous relationship."

"Financial distress is a condition where firms face difficulties to fulfill debt and facing risk of liquidation. This research provides a critical analysis of factors affecting the risk of financial distress which is represented by the interest coverage ratio. Lower interest coverage ratio will cause higher risk of financial distress. It used panel data regression of 78 manufacturing firms between the 2009-2011 period with a total of 234 observations. Independent variables analyzed were the debt to asset ratio, return on assets, current ratio, firm age, and firm size. Result shows that return on asset, current ratio, and firm age have significant effect on financial distress. It means firms must observe their profitability and liquidity so that firms can lessen the risk of financial distress. Aside from that, older firms tend to have lower risk of financial distress due to higher competitiveness and higher management experience."

"Krisis keuangan global yang terjadi sekitar tahun 2008 hingga 2009 menimbulkan dampak ke Indonesia, salah satunya ancaman kebangkrutan pada perusahaan publik. Penelitian ini bertujuan untuk menganalisis prediksi financial distress dengan menggunakan teknik analisis logistic regression dan discriminant analysis pada perusahaan publik yang terdaftar di Bursa Efek Indonesia periode 2005 hingga 2010.Hasilnya adalah dengan menggunakan teknik analisis logistic regression, tingkat akurasi prediksi financial distress dalam memprediksi jawaban yang benar adalah sebesar 89.3 persen dan dengan menggunakan teknik teknik analisis discriminant analysis, tingkat akurasi prediksi financial distress dalam memprediksi jawaban yang benar adalah sebesar 62 persen. Pada penggunaan teknik discriminant analysis, waktu yang terbaik untuk memprediksi adalah tiga tahun sebelum financial distress, dengan nilai persentase sebesar 66 persen yang merupakan angka tertinggi selama periode penelitian.

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Due to global financial crisis in 2008 until 2009 affects to Indonesia, one of them is the threat of financial distress which occures before bankruptcy. This research aimed to predict the financial distress using logistic regression and discriminant analysis to public companies listed in Indonesia Stock Exchange (IDX) in 2005-2010.The results are by using logistic regression, financial distress can be predicted 89.3% significantly. Moreover, by using discriminant analysis, financial distress can be predicted 62% significantly. Discriminant analysis approach gets best prediction in 3 years prior to occurence of financial distress with 66% correct percentage."

"Ekonomi global saat ini sedang berada pada titik perubahan besar, semakin majunya teknologi informasi menghadirkan suatu perubahan yang menggabungkan antara Manusia, Mesin, dan Internet of Things (IoT). perubahan ini disebut sebagai revolusi Industri 4.0 yang mana akan dapat mengubah seluruh aspek produksi. Namun perubahan ini tidak memberikan efek positif kepada semua pihak, terdapat berbagai pihak yang dirugikan akibat dari ketidakmampuan dalam mengikuti penyesuaian yang berdampak menurunkan kinerja perusahaan dan dapat meningkatkan risiko kebangkrutan perusahaan. Dengan prediksi kebangkrutan akan menilai apakah terdapat perubahan yang signifikan risiko kebangkrutan pada perusahaan pasca perubahan revolusi Industri 4.0. Metode Altman Z-Score adalah metode penilaian risiko kebangkrutan yang reliabel dan banyak digunakan dalam memprediksi risiko kebangkrutan perusahaan. Sehingga dilakukan pengujian perbandingan nilai Z-Score antar Industri dan Tahun untuk melihat perubahan risiko kebangkrutan pasca revolusi Industri 4.0.

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The global economy is currently at a point of great change, the more advanced information technology presents a change that combines human, machine, and the Internet of Things (IoT). this change is referred to as the Industrial 4.0 revolution which will be able to change all aspects of production. But this change does not have a positive effect on all parties, there are various disadvantaged parties due to incapacity to follow adjustments that have an impact on reducing company performance and can increase the risk of corporate bankruptcy. With the prediction of bankruptcy, it will assess whether there is a significant change in the risk of bankruptcy in the company after the change in the Industrial Revolution 4.0. The Altman Z-Score method is a reliable and widely used method of bankruptcy risk assessment in predicting the risk of corporate bankruptcy. So that a comparison test of the Z-Score between Industries and Years is carried out to see changes in the risk of post-revolutionary Industrial 4.0 bankruptcy."

"[Penelitian ini bertujuan untuk menganalisis prediksi kebangkrutan pada perusahaan di sektor konstruksi yang terdaftar pada Bursa Efek Regional Asia Tenggara (Filipina, Indonesia, Malaysia, dan Thailand). Metode prediksi kebangkrutan yang digunakan adalah model KMV (Kealhofer, McQuown and Vasicek) yang dibuat oleh Moodys. Dari hasil studi menujukan bahwa tingkat probability of default perusahaan sektor konstruksi di Bursa Efek Indonesia berada di posisi paling rendah jika dibandingkan dengan perusahaan sektor konstruksi di Bursa Efek Regional Asia Tenggara.;This research is aimed to analyze bankruptcy prediction on company who listed in Regional Stock Exchange of South East Asia (Filipina, Indonesia, Malaysia, and Thailand). KMV (Kealhofer, McQuown and Vasicek) method who published by Moodys used to predict the bancrupty. The results of this research found that level of probability of default construction sector companies in Indonesia Stock Exchange is in the lowest position when compared with the construction sector companies in Southeast Asia Regional Stock Exchange.;This research is aimed to analyze bankruptcy prediction on company who listed in Regional Stock Exchange of South East Asia (Filipina, Indonesia, Malaysia, and Thailand). KMV (Kealhofer, McQuown and Vasicek) method who published by Moodys used to predict the bancrupty. The results of this research found that level of probability of default construction sector companies in Indonesia Stock Exchange is in the lowest position when compared with the construction sector companies in Southeast Asia Regional Stock Exchange., This research is aimed to analyze bankruptcy prediction on company who listed in Regional Stock Exchange of South East Asia (Filipina, Indonesia, Malaysia, and Thailand). KMV (Kealhofer, McQuown and Vasicek) method who published by Moodys used to predict the bancrupty. The results of this research found that level of probability of default construction sector companies in Indonesia Stock Exchange is in the lowest position when compared with the construction sector companies in Southeast Asia Regional Stock Exchange.]"

"ABSTRACTFinancial distress merupakan kondisi kesulitan keuangan yang pada umumnya dialami oleh perusahaan sebelum perusahaan tersebut dapat dinyatakan bangkrut. Dengan menggunakan laporan keuangan, kondisi tersebut pada dasarnya dapat diprediksi. Prediksi dari financial distress sangat berguna bagi manajemen perusahaan untuk melakukan tindakan korektif dalam antisipasinya menghadapi kebangkrutan. Model prediksi dari financial distress sendiri telah berkembang dari penggunaan statistik tradisional hingga artificial intelligence atau machine learning. Penelitian ini bertujuan untuk menganalisis model prediksi financial distress dengan menerapkan machine learning dan membandingkan tiga algoritma dari data mining yaitu decision tree, support vector machine, dan artificial neural network. Sampel dalam penelitian ini menggunakan 115 perusahaan distressed dan 115 perusahaan non-distressed yang aktif di Bursa Efek Indonesia selama periode 2011 hingga 2016 yang diteliti untuk dua tahun yaitu l-t dan t-1. Dalam penelitian ini, dari sebanyak 29 rasio keuangan akan dipilih rasio yang paling sesuai dengan menggunakan feature selection. Hasil dari penelitian menunjukkan bahwa algoritma decision tree dengan tingkat akurasi sebesar 86,37 untuk tahun l-t dan decision tree dengan tingkat akurasi sebesar 88,98 untuk tahun l t-1 memiliki tingkat akurasi yang paling tinggi dalam mengantisipasi financial distress di Indonesia.

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ABSTRACTFinancial distress is a condition of financial difficulties that generally a firm would have first go through before the company can be declared bankrupt. By using financial statements, this condition basically could be predicted. Prediction of financial distress is very useful as it could help firms rsquo management to take corrective actions in anticipation of bankruptcy. The predictive model of financial distress itself has evolved from the use of traditional statistics to artificial intelligence or machine learning. This study aims to analyze financial distress prediction model by applying machine learning and comparing three algorithms from data mining namely decision tree, support vector machine, and artificial neural network. The sample in this study used 115 distressed companies and 115 non distressed companies active on the Indonesia Stock Exchange during the period 2011 to 2016 studied for two years ie t and t-1 . In this research, from 29 financial ratios will be selected the most appropriate ratios by using feature selection. The result of this research shows that decision tree algorithm with 86.37 accuracy for year t and decision tree with accuracy of 88.98 for year t-1 has the highest accuracy in anticipating financial distress in Indonesia. "

"Masa pandemi COVID-19 yang berawal pada bulan Maret 2020 ini sudah banyak membuat tekanan di masyarakat, khususnya tekanan ekonomi. Berbagai peraturan ditetapkan, dalam rangka menekan angka penyebarannya, sehingga membuat banyak aktivitas terganggu, karena masyarakat dituntut untuk melakukan aktivitasnya dari rumah saja yang membuat aktivitas usaha tidak dapat dijalankan secara maksimal. Dalam usahanya beradaptasi, tidak jarang perusahaan gagal mencapai tujuannya dan menimbulkan kerugian operasional pada tahun berjalan. Kerugian yang dialami tidak jarang membawa perusahaan pada kebangkrutan. Namun data mencatatkan sebaliknya. Pada kuartal III tahun 2021, BPS mencatat pertumbuhan industri manufaktur sebesar 3,68 persen, peningkatan yang cukup baik di tengah banyaknya kasus COVID-19 di Indonesia. Penelitian ini ingin membuktikan apakah sektor manufaktur menunjukkan geliat positif selama pandemi dengan menggunakan metode Springate dan Altman. Perhitungan kondisi keuangan yang dilakukan pada perusahaan manufaktur yang terdaftar di BEI tahun 2016-2020 menunjukkan bahwa metode Springate mengelompokkan 282 observasi ke dalam kategori sehat dan 283 lainnya masuk ke dalam kategori distress. Sedangkan metode Altman mengelompokkan 235 observasi masuk kategori sehat, 136 observasi masuk kategori gray zone, dan 194 lainnya masuk kategori distress. Hasil penelitian juga menunjukkan bahwa metode Springate memiliki tingkat konsistensi yang lebih tinggi dibandingkan dengan metode Altman

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The COVID-19 pandemic, which began in March 2020, has created a lot of pressure on the community, especially economic pressure. Various regulations were enacted, in order to reduce the number of spreads, thus disrupting many activities, because people were required to carry out their activities from home which made business activities unable to run optimally. In its efforts to adapt, it is not uncommon for companies to fail to achieve their goals and incur operational losses in the current year. Losses experienced not infrequently bring the company to bankruptcy. However, the data says otherwise. In the third quarter of 2021, BPS recorded a manufacturing industry growth of 3.68 percent, a fairly good increase in the midst of the large number of COVID-19 cases in Indonesia. This study wants to prove whether the manufacturing sector shows a positive stretch during the pandemic by using the Springate and Altman methods. Calculations of financial conditions carried out on manufacturing companies listed on the IDX in 2016-2020 show that the Springate method groups 282 observations into the healthy category and another 283 into the distress category. While the Altman method groups 235 observations into the healthy category, 136 observations in the gray zone category, and 194 others into the distress category. The results also show that the Springate method has a higher level of consistency than the Altman method."

"Penelitian ini mengkaji penggunaan trade credit oleh perusahaan-perusahaan yang berada pada keadaan financial distress. Trade credit merupakan sumber pembiayaan jangka pendek yang dapat berguna bagi perusahaan yang mengalami financial distress. Proksi yang digunakan untuk variabel financial distress adalah coverage ratio. Tujuan dari penelitian ini adalah menganalisis pengaruh financial distress terhadap keputusan penggunaan trade credit. Penelitian ini memiliki 3 hipotesis: pertama, perusahaan yang financial distress berpengaruh positif terhadap ratio of trade payable to cost of good sold, kedua, perusahaan yang financial distress berpengaruh positif terhadap ratio of trade payable to equity dan yang ketiga, perusahaan yang financial distress berpengaruh positif terhadap ratio of trade payable to financial debt. Sampel penelitian diambil dari perusahaan-perusahaan non-keuangan yang tercatat di BEI pada periode tahun 2007-2016. Metode penelitian yang digunakan adalah regresi data panel dengan menggunakan model estimasi fixed effect model dan random effect. Penelitian ini menemukan bahwa perusahaan-perusahaan yang mengalami financial distress cenderung meningkatkan penggunaan trade credit. Hal tersebut tercermin dari hasil penelitian yang menunjukkan koefisien positif dan signifikan pada variabel financial distress terhadap ratio of trade payable to cost of good sold dan ratio of trade payable to equity.

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This study examines the use of trade credits by firms that are in a state of financial distress. Trade credit is a short term financing that can be useful for firms in financial distress. The proxy used for financial distress variables is coverage ratio. The purpose of this study is to analyze the effect of financial distress on trade credit. This research has 3 hypotheses first, the firms in financial distress have a positive coefficient on the ratio of trade payable to the cost of good sold, secondly, the firms in financial distress have a positive coefficient on the ratio of trade payable to equity and third, the firms financial distress have a positive coefficient on the ratio of trade payable to financial debt. The study sample was taken from non financial firms listed on the IDX in the period of 2007 2016. The research method is panel data regression by using estimation model of fixed effect model and random effect. This study found that firms in financial distress tend to increase the use of trade credit. This is reflected from the results of research showing the positive and significant coefficients on the variable financial distress on the ratio of trade payable to cost of good sold and the ratio of trade payable to equity."

"Penelitian ini bertujuan untuk mengetahui pengaruh financing restatement terhadap pertumbuhan dan risiko kebangkrutan pada perusahaan non-keuangan yang terdaftar di Bursa Efek Indonesia (BEI) periode 2008-2017. Pertumbuhan perusahaan diukur menggunakan pendekatan Internally Financed Growth (IFG) dan Externally Financed Growth (EFG), dimana pendekatan tersebut memiliki tiga proxy, serta risiko kebangkrutan diukur dengan Altman Z Score. Total sampel yang digunakan mencakup 256 perusahaan dengan gaps pada tahun 2013-2014. Metode yang digunakan untuk menentukan sampel menggunakan purposive sampling. Penelitian ini menggunakan regresi data panel, dengan data yang bersifat unbalanced panel sehingga jumlah observasi sebesar 2013 firm-year. Hasil yang ditemukan bahwa terdapat pengaruh negatif dan signifikan antara restatement terhadap pertumbuhan perusahaan. Berarti kegiatan restatement dapat menurunkan tingkat pertumbuhan perusahaan non-keuangan di Indonesia yang dibiayai secara eksternal. Namun tidak terdapat pengaruh yang signifikan antara restatement dan risiko kebangkrutan.

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This study aims to determine the effect of financing restatement on the growth and bankruptcy risk of non-financial companies listed on the Indonesia Stock Exchange (IDX) for the period 2008-2017. The company's growth is measured using the Internally Financed Growth (IFG) and Externally Financed Growth EFG approaches, where the approach has three proxies, and the risk of bankruptcy is measured by the Altman Z Score. The total sample used included 256 companies with gaps in 2013-2014. The method used to determine the sample using purposive sampling. This study using panel data regression that is unbalanced panel so that the number of observations is 2013 firm year. The results found that there is a negative and significant relationship between restatement on firm growth. Means that restatement activities can reduce the firm growth rate of non-financial companies in Indonesia which are externally financed. However, there is no significant influence between the restatement and the bankruptcy risk.

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