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"ABSTRAKKarya akhir ini membahas mengenai 4 model prediksi kebangkrutan yang popular saat ini, dua model berdasarkan data akuntansi yaitu Altman Z scores (1968) dan Ohlson O scores (1980) dan dua model berdasarkan data pasar yaitu Merton model (1974) dan KMV model (1995). Penulis melakukan penelitian terhadap 4 model prediksi kebangkrutan pada 23 perusahaan bangkrut dan 40 perusahaan tidak bangkrut di Indonesia pada kurun waktu 2001-2011. Dari hasiltersebut kami menemukan bahwa KMV model mengungguli model-model yang lainnya dalam hal validasi model, dengan nilai akurasi tertinggi.

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ABSTRACTThis paper asses about 4 popular bankruptcy model, two was accounting based models Altman Z scores (1968) and Ohlson O scores (1980) and two was market based models Merton model (1974) and KMV model (1995). We measure this 4 bankruptcy model bya applied this model into 23 bankruptcy company and 40 non bankruptcy company in Indonesia from 2001-2011. From the result we find that KMV model has relative more explanatory power than other model, with the best accuracy ratio than others models."

"Masa kepemimpinan SBY memiliki pendekatan ekonomi jangka pendek sementara Jokowi memiliki target perkembangan ekonomi jangka panjang agar terbangun lingkungan yang mendukung kegiatan bisnis di Indonesia. Di masa Jokowi, perusahaan konstruksi mengalami peningkatan kinerja operasi yang pesat, tetapi hal ini dibarengi dengan kenaikan tingkat utang perusahaan konstruksi. Dengan menggunakan 50 perusahaan sebagai observasi, dilakukan analisis prediksi kebangkrutan dengan model Altman Z-Score, Altman Z-Score EMS, dan Springate S-Score untuk mengetahui kondisi keuangan perusahaan konstruksi di Indonesia dan bagaimana pengaruh perbedaan periode kepemimpinan presiden terhadap tiga model tersebut.

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Susilo Bambang Yudhoyonos presidency period has target for short-term economic development while Jokowi has a target of long-term economic development in order to build an environment that supports business activities in Indonesia. During the era of Jokowis presidency, construction companies are developing their business activities more than during SBYs era, but the development is coma along with the increase in companys debt performance. By using 50 companies as observations, a prediction bankruptcy analysis is conducted using Altman Z-Score, Altman Z-Score EMS, and Springate S-Score  model to obtain financial information on construction companies in Indonesia and to analyze the relationship of the different presidency period to the three models."

"Penelitian ini dilakukan untuk melihat seberapa cocok model-model prediksi kebangkrutan yang ada dan selama ini digunakan di negara-negara lain untuk digunakan pada masa krisis di Indonesia. Adapun data yang digunakan dalam penelitian adalah perusahaan-perusahaan di Indonesia yang terdaftar pada Bursa Efek Indonesia (BEI) yang terkelompokkan ke dalam beberapa sektor. Re-estimasi koefisien variabel-variabel model dilakukan kepada masing-masing sektor untuk kemudian dilakukan prediksi kebangkrutan dari model re-estimasi tersebut. Hasil prediksi kebangkrutan model re-estimasi kemudian dibandingkan dengan hasil prediksi kebangkrutan dari model aslinya untuk melihat apakah model dapat digunakan pada masa krisis di Indonesia. Hasil dari penelitian adalah model Springate original merupakan model yang paling cocok dengan kondisi di Indonesia pada masa krisis akibat COVID-19. Model Springate memiliki akurasi prediksi kebangkrutan paling tinggi, sementara model Altman Emerging Market menghasilkan Error Type I paling tinggi.

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This research was conducted to see how suitable the existing bankruptcy prediction models that have been used in other countries to be used during the crisis in Indonesia. The data used in research are companies in Indonesia registered in the Indonesia Stock Exchange (IDX) which are grouped into several sectors. The re-estimate of the coefficient of variables models is carried out to each sector for then the bankruptcy prediction of the re-estimation model is carried out. The results of the bankruptcy prediction of the re-estimate model are then compared with the results of the bankruptcy prediction of the original model to see whether the model can be used during the crisis in Indonesia. The result of the study is the original Springne Model is the model that is most suitable for the conditions in Indonesia during the crisis due to Covid-19. The Springate model has the highest accuracy of bankruptcy predictions, while the Altman Emerging Market model produces the highest error type I."

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Segmen usaha kecil dan menengah saat ini terus berkembang di Indonesia. Berkontribusi lebih dari seperlima Produk Domestik Bruto Indonesia menjadikan segmen ini sangat berpotensi untuk terus dikembangkan. Perbankan dalam negeri dan asing melihat segmen usaha kecil menengah ini sebagai segmen yang menjanjikan sehingga membuat mayoritas Bank di Indonesia ikut bersaing dalam penyaluran kredit pada segmen ini. Namun, ditengah prospek yang menjanjikan, segmen ini juga memiliki tantangan tersendiri dimana rasio non-performing loan secara Nasional pada segmen ini melebihi rasio  non-performing loan seluruh kredit yang disalurkan. Penelitian ini bertujuan untuk meniliti reliabilitas metode Altman Z-Score serta Ohlson O-Score sebagai alat prediksi kebangkrutan pada perusahaan segmen Small Medium Enterprise di Indonesia serta reliabilitas laporan keuangan perusahaan di segmen Small Medium Enterprise dalam mencerminkan kondisi riil perusahaan sebagai data masukan untuk analisa prediksi kebangkrutan perusahaan. Data penelitian menggunakan data laporan keuangan dari perusahaan yang menjadi debitur segmen Small Medium Enterprise di Bank Mandiri. Hasil penelitian menunjukkan bahwa hasil perhitungan Z-Score mampu memprediksi kebangkrutan dengan akurasi  51,8%, 37,4%, 36,3%, dan 11,4% untuk satu, dua, tiga dan empat tahun sebelum kebangkrutan sedangkan Ohlosn O-Score memberikan hasil akurasi yang lebih baik yaitu 73,6%, 43,2%, dan 58,5% untuk satu, dua dan tiga tahun sebelum kebangkrutan. Berdasarkan hasil tersebut dan wawancara kepada pihak internal Bank dapat disimpulkan bahwa laporan keuangan untuk perusahaan segmen Small Medium Enterprise secara umum belum cukup reliable untuk mencerminkan kondisi perusahaan secara riil.

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Nowadays, small and medium enterprises continue to grow in Indonesia, contributing more than one fifth of Indonesia's Gross Domestic Product, making this segment very potential to continue to be developed. Domestic and foreign banks see this small and medium business segment as a promising segment, making the majority of banks in Indonesia compete in lending to this segment. However, amid a promising prospect, this segment also has its own challenges, where the national’s ratio of non-performing loans in this segment exceeds the ratio of non-performing loans of all loans disbursed. This study aims to assess the reliability of the Altman Z-Score and Ohlson O-Score methods as bankruptcy predictors in Small Medium Enterprise segment in Indonesia and the reliability of the company's financial statements in the Small Medium Enterprise segment in reflecting the company's real conditions as input data to analyze the possibility of the company going bankrupt. This research uses financial report data from companies that are debtors in the Small Medium Enterprise segment at Bank Mandiri. The results showed that the Z-Score calculation was able to predict bankruptcy with an accuracy of 51.8%, 37.4%, 36.3%, and 11.4% for one, two, three and four years before bankruptcy while Ohlson O-Score giving better accuracy results of 73.6%, 43.2%, and 58.5% for one, two and three years before bankruptcy. Based on these results and interviews with internal parties of the Bank it can be concluded that financial statements for Small Medium Enterprise segment companies in general have not been reliable enough to reflect the company's condition in real.

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"ABSTRAKThe economy of Indonesia has rapidly grown since its first economicturmoil in 1997/1998. The annual growth rate of the GDP exceeded 6% in the lastfour years despite the global economies slow down due to the consequences of‘bubble’ subprime mortgage that ruined most of the world’s financial institutions.The growth significantly energizes the local economic activities either in theindustrial market or in the capital market.In spite of the ‘bull’ market, the risk of financial distress remains alive andthe economic direction might change because of the volatility of businessenvironment. There is no firm protected or immune from financial adversity thatmay result in failure, insolvency, default or bankruptcy. Plummeting stock price,reduced dividend payment, consecutive net loss, massive lay-offs, pendingobligations and a fair number of other negative signs are common association withfinancial distress.Widely recognized, financial distress prediction models may be examinedto assess a firm’s economic situation for further purposes. Altman, Ohlson,Zmijewsky, Fulmer, and Springate are some of notable researchers to which theirmodels are referred to evaluating the soundness of a firm. However, each markethas its own financial distress environment that in consequence any financialdistress prediction model requires an evaluation whether or not the modeladequately fits to a certain market, in particular Indonesia for this case. Theimportance of predictors and accuracy will minimize producing misleading resultsfrom the economic forecast.The results of this testing against the first hypothesis showed that none ofthe adjusted models included all the variables of the base model, respectively.There were some variables with insufficient explanatory power to predict thecessation of activities of the tested firms. The second hypothesis argued that theadjusted models were less capable than those developed originally in terms ofaccuracy.

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ABSTRACTThe economy of Indonesia has rapidly grown since its first economicturmoil in 1997/1998. The annual growth rate of the GDP exceeded 6% in the lastfour years despite the global economies slow down due to the consequences of‘bubble’ subprime mortgage that ruined most of the world’s financial institutions.The growth significantly energizes the local economic activities either in theindustrial market or in the capital market.In spite of the ‘bull’ market, the risk of financial distress remains alive andthe economic direction might change because of the volatility of businessenvironment. There is no firm protected or immune from financial adversity thatmay result in failure, insolvency, default or bankruptcy. Plummeting stock price,reduced dividend payment, consecutive net loss, massive lay-offs, pendingobligations and a fair number of other negative signs are common association withfinancial distress.Widely recognized, financial distress prediction models may be examinedto assess a firm’s economic situation for further purposes. Altman, Ohlson,Zmijewsky, Fulmer, and Springate are some of notable researchers to which theirmodels are referred to evaluating the soundness of a firm. However, each markethas its own financial distress environment that in consequence any financialdistress prediction model requires an evaluation whether or not the modeladequately fits to a certain market, in particular Indonesia for this case. Theimportance of predictors and accuracy will minimize producing misleading resultsfrom the economic forecast.The results of this testing against the first hypothesis showed that none ofthe adjusted models included all the variables of the base model, respectively.There were some variables with insufficient explanatory power to predict thecessation of activities of the tested firms. The second hypothesis argued that theadjusted models were less capable than those developed originally in terms ofaccuracy."

"Financial distress dapat dianggap sebagai peringatan dini masalah yang dapat menyebabkan kebangkrutan. Memprediksi kebangkrutan menjadi salah satu hal yang dapat dilakukan perusahaan untuk menemukan keadaan kesehatan keuangan perusahaan. Sebanyak 585 firm-year pada perusahaan manufaktur yang terdaftar di Bursa Efek Indonesia dijadikan sampel untuk penelitian ini di mana 113 di antaranya dikategorikan dalam kondisi financial distress. Model prediksi kebangkrutan dapat diperiksa untuk menilai situasi ekonomi perusahaan untuk tujuan lebih lanjut. Altman dan Ohlson adalah beberapa peneliti terkenal yang modelnya dirujuk untuk mengevaluasi kesehatan perusahaan.

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Financial distress can be regarded as an early warning of trouble that can lead to bankruptcy. Predicting bankruptcy becomes one thing that companies can do to discover the state of the company's financial health. A total of 585 firm-years of manufacturing companies that listed in Indonesia Stock Exchange are sampled for this research where 113 of them are categorized in financial distress state. Bankruptcy prediction models may be examined to assess a company's economic situation for further purposes. Altman and Ohlson are some of notable researchers to which their models are referred to evaluating the health of companies."

"Since year 1997 up to 1999, 64 banks in Indonesia have been liquidated/closed by Central Bank and numbers of bank have followed banking re-capitalization program or under control of Indonesian Banking Restructuring Agency/OKRA. It brings Indonesia into a big economic problem because Bank's role in Indonesian economy was very important. Indonesia becomes a country which has a big burden and very hard to recover from the crisis. That is the reason that the author intends to explore more precisely the condition of Indonesian Banking.This research is designed to make a model that can be used to predict Bank Failure with case study in Indonesian Banking 1997 - 1999. This research purpose is to differentiate good bank and failure bank, so the result of this research will contribute to banking knowledge in Indonesia and will help the Indonesian to select a good bank.This research uses Multiple Logistic Regression Model as a methodology with more than 2 (two) independent variables. The model had been chosen since the type of dependent variable is binary (Good bank or Failure bank) and allows us to use 'dummy data' that can not be possible in conventional model.The numbers of data sample in this research were 144 banks : 81 failure banks and 63 good bank. Data used in the model was the last published financial statement before the bank failure. The dependent variable is failure/good bank and there are 16 independent variables related to Capital, Asset Quality, Earning/ Profitability, Liquidity and Efficiency.The model was tested by determination coefficient Cox & Snell R Squared and Nagelkerke R Squared. The test shows that the model is significant (0.6 & 0.8). it means that independent variable used in the model has significant correlation to dependent variable. Kolmogorov Smimov Test shows that the model be able to differentiate failure bank and good bank. Hosmer & Lemeshow Test proves that the prediction of the model is fit with the actual data. The above tests summarize that the model can be used to predict and differentiate between failure bank and good bank."

"ABSTRAKPenelitian ini bertujuan untuk menganalisis adakah perilaku Myopic Loss Aversion pada Pasar Modal di Indonesia periode 2016-2017. Proksi yang digunakan untuk mengukur periode evaluasi adalah meanreturndaily dan meanreturnweekly dari marketbenchmark dan industrybenchmark, sedangkan untuk penghindaran kerugian, proksi yang digunakan adalah meanreturn volatitily, nilai regresi dan nilai residual dari marketbenchmark dan industrybenchmark. Penelitian ini menemukan bahwa perusahaan yang melakukan perilaku Myopic Loss Aversion karena dipengaruhi oleh periode evaluasi memiliki nilai meanreturndaily yang lebih besar dibandingkan nilai meanreturnweekly dari harga penutupan saham perusahaan. Hasil dari penelitian ini juga menemukan bahwa perilaku Myopic Loss Aversion juga terjadi karena dipengaruhi oleh penghindaran kerugian, hal tersebut terlihat pada nilai meanreturnvolatility, nilai regresi, dan nilai residual daily yang lebih besar dibandingkan nilai dari weekly ketiga mean tersebut. Kondisi ini menunjukkan bahwa terdapat perilaku Myopic Loss Aversionyang dipengaruhi oleh periode evaluasi dan penghindaran kerugian yang dilakukan oleh perusahaan. Dengan demikian, perusahaan perlu memperhatikan kondisi internal perusahaan dan peristiwa ekonomi relevan yang terjadi.

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ABSTRACTThis study aims to analyze whether there is a behavior of Myopic Loss Aversion in the Capital Market in Indonesia for the period 2016-2017. The proxy used to measure the evaluation period is the mean return daily and weekly from the market benchmark and industry benchmark, while for loss aversion, the proxy used is the mean return volatitily, the regression value and the residual value from the market benchmark and the industry benchmark. This study found that companies that conduct Myopic Loss Aversion behavior because it is influenced by the evaluation period has a mean return daily value that is greater than the mean return weekly value of the closing price of the company's stock. The results of this study also found that the behavior of Myopic Loss Aversion also occurs because it is influenced by loss aversion, it can be seen in the mean return volatility, regression value, and residual daily value that is greater than the value of the third mean weekly. This condition indicates that there is a behavior of Myopic Loss Aversion which is influenced by periods of evaluation and avoidance of losses carried out by the company. Thus, the company needs to pay attention to the internal conditions of the company and relevant economic events that occur."

"Kondisi harga minyak secara global dalam beberapa tahun terakhir mengalami pasang surut akibat harga minyak mengalami penurunan yang signifikan. Hal ini tentunya berimbas pada kesehatan keuangan perusahaan-perusahaan yang bergerak di industri migas. Penelitian ini bertujuan untuk memprediksikan kemungkinan kebangkrutan perusahaan migas di Indonesia selama periode tahun 2011 – 2017. Perusahaan yang diteliti adalah perusahaan migas yang terdaftar di BEI. Adapun tujuan lainnya adalah untuk melihat apakah fenomena global berupa penurunan harga minyak dunia berpengaruh terhadap kesehatan keuangan migas yang direpresentasikan dengan nilai Z-Score serta untuk melihat indikator apa saja yang dapat mempengaruhi kebangkrutan perusahaan migas. Data penelitian menggunakan data laporan keuangan dan laporan tahunan perusahaan yang diambil dari website IDX dan website masing-masing perusahaan. Hasil penelitian menunjukkan bahwa hasil perhitungan Z-Score mampu memprediksikan lima perusahaan berada pada kategori bangkrut sejak 2014 hingga 2017. Di tahun 2011 hanya dua perusahaan terprediksi bangkrut, tahun 2012 hanya memprediksi satu perusahaan, dan tahun 2013 diprediksi tiga perusahaan mengalami kebangkrutan. Penelitian juga menemukan bahwa penurunan harga minyak mempengaruhi hasil Z-Score untuk perusahaan E&P karena pendapatan perusahaan bergantung pada harga minyak di pasar. Sedangkan pada perusahaan jasa migas, penurunan harga minyak tidak terlalu berpengaruh kecuali pada APEX dan BIPI yang lini bisnisnya merupakan jasa pengeboran.

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Global oil price condition for these past few years has been fluctuating and has reached the lowest level. This condition will affect oil and gas companies financial health. This thesis aims to predict the bankruptcy probability of oil and gas companies in Indonesia during period of 2011 – 2017. The observed companies are oil and gas companies that are listed on IDX. Another aim of this thesis is to observe whether the decline in oil price would affect company Z-Score result or not, and to observe which variable that effect the bankruptcy to oil and gas companies. This research uses financial data that obtained from IDX website and company website. The result of the research figures out that Z-Score model could predict at least five companies are in the bankruptcy category since 2014 to 2017. In 2011, only two companies that are predicted will be bankrupt. In 2012, theres only one company will be bankrupt, and in 2013 three companies are predicted to be bankrupt. This research also figures out that the decrease in oil price effects the result of Z-Score for E&P companies as E&P companies revenue relies on oil price in the market. For service companies, the decrease in oil price doesnt give direct impact except for APEX and BIPI which their line business is providing services for drilling explorations."