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"Krisis ekonomi dan moneter yang melanda Indonesia sejak medio 1997 telah merontokkan sejumlah perusahaan di Indonesia, endemi kebangkrutan ini telah memberikan kerugian yang besar bagi para stakeholders perusahaan-perusahaan tersebut, mulai dari pemegang saham yang rugi karena nilai saham perusahaannya jatuh bebas, kreditur yang tidak dapat menagih piutangnya, sampai pegawai yang terpaksa di PHK-kan.Kebangkrutan massal tersebut menyadarkan masyarakat tentang pentingnya prediksi keadaan perusahaan di masa yang akan datang. Karena prediksi ini dilakukan oleh masyarakat umum maka data yang dipergunakan dalam prediksi tersebut haruslah data yang mudah diperoleh, seperti laporan keuangan yang dipublikasikan setiap tahunnya.Sebenarnya telah ada beberapa pemndelan prediksi kebangkrutan perusahaan yang umum dipakai, namun model-model tersebut dibuat berdasarkan data-data di negara lain dan pada tahun yang berbeda, sehingga sedikit banyak kurang sesuai dengan keadaan di Indonesia.Penelitian untuk memodelkan prediksi kebangkrutan ini dibatasi pada perusahaan-perusahaan dalam industri barang konsumsi, namun tidak tertutup kemungkinan dipergunakan pada industri lainnya. Sampel yang dipakai adalah dari 40 pemsahaan dalam kurun waktu 1999 sampai 2004, dan menggunakan 22 rasio-rasio keuangan sebagai indikator atas keadaan likuiditas, efisiensi, leverage, dan profitabilitas perusahaan.Penelitan ini menggunakan data tahun 2000 sebagai tahun dasar dan menghasilkan model:Z = 0.948X, +0.697X5 -1.195X5 +1.319X15 +4.599X17 dimana:Xa total liability/ total shareholder's equityX5 : long term liability/ long term liability + total shareholder's equityX6 : total liability/ total assetX15 net sales/ working capitalX17 net income/net salesModel diskriminan ini menunjukkan akurasi yang cukup balk jika diuji menggunakan sampel data tahun 2000 sampai 2004, dengan akurasi rata-ratanya berturut-turut adalah 100.00%, 97.44%, 97.44%, 97.37%, dan 91.89%.Penelitian ini menyimpulkan bahwa persamaan dengan data tahun 2000 sebagai tahun dasar merupakan prediksi kebangkrutan yang cukup akurat untuk perssaaan dalam industri barang konsumsi di Indonesia dengan menggunakan data tahun 1999-2004.

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Economic and monetary crises which came to Indonesia since mid 1997 have pulled several companies into bankruptcy. This bankruptcy endemic forced those companies' stakeholder to suffer a major loss, shareholders who suffer loss because their stock prices are free-falling, creditors who can't redeem their debt, and last but not least, employees who loss their job because their companies are bankrupt.

This massive bankruptcy endemic notices people about the importance of company future predictions. Since everybody should be able to do this prediction, therefore every data which required doing the prediction should be easily found, for example, financial report published on the internet.

There are some company bankruptcy models commonly used, but those models are built based on data from different countries and in different year. Therefore those models might not be suitable for Indonesia.

This research to model bankruptcy prediction is limited to companies under consumer goods industry, nonetheless it can be built using data from other industries. Samples to be used are from 40 companies from 1999 to 2004, also there are 22 financial ratios as indicator for liquidity, efficiency, leverage, and company profitability.

This research uses data from financial year 2000 as base year, and the research results:

Z = 0.948X4 +0.697X5 -1.195X5 +1.319X15 + 0.599X17 where:

X4 : total liability/ total shareholder's equity

X5 : long term liability/ long term liability + total shareholder's equity

A 6 : total liability) total asset

X15 : net sales/ working capital

X17 : net income/ net sales

This discriminate model shows a high accuracy when tested using data from year 2000 to 2004, with average accuracy consecutively, 100.00%, 97.44%, 97.44%, 97.37% and 91.89%.

This research concludes that model with year 2000 as base year is an accurate bankruptcy prediction for companies in consumer goods industry in Indonesia using data from year 1999-2004."

"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."

"[ABSTRAKPenelitian ini bertujuan untuk menganalisis bagi perusahaan untuk dapat mengantisipasi kebangkrutan. Penelitian ini menggunakan dari rasio-rasio keuangan dari tahun 2010 sampai 2014.Pada penelitian ini dalam melakukan analisis menggunakan model Altman untuk memprediksi kebangkrutan yang di batasi pada perusahaan-perusahaan pengembang properti. Dimana sampel yang digunakan adalah 35 perusahaan dengan menggunakan rasio-rasio keuangan sebagai indikator atas keadaan likuiditas, efisien, leverage, dan probabilitas perusahaan.Pemodelan ini menggunakan metode analisis diskriman untuk memperoleh model yang baik. Hasil dari analisis diskriminan ini didapat rasio yang berpengaruh yaitu Working Capital, Total liabilities, Retain Earning , Total Asset, MVE,EBIT terhadap kebangkrutan.

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ABSTRACTThis study aimed to analyze for companies to be able to anticipate bankruptcy. This study use financial ratios from 2010 to 2014. In this research using Altman model for bankruptcy in the limit on property development companies. The samples used were 35 companies using financial ratios as an indicator of the state of liquidity, efficient, leverage, and the probability of the company. This modeling a method discriminant analysis to obtain a good model. Results of discriminant analysis is obtained that affect the ratio current assets, current liabilities, net income, Retain Earnings, Total Assets, Operating Income, Net Sales for bankruptcy.;This study aimed to analyze for companies to be able to anticipate bankruptcy. This study use financial ratios from 2010 to 2014. In this research using Altman model for bankruptcy in the limit on property development companies. The samples used were 35 companies using financial ratios as an indicator of the state of liquidity, efficient, leverage, and the probability of the company. This modeling a method discriminant analysis to obtain a good model. Results of discriminant analysis is obtained that affect the ratio current assets, current liabilities, net income, Retain Earnings, Total Assets, Operating Income, Net Sales for bankruptcy.;This study aimed to analyze for companies to be able to anticipate bankruptcy. This study use financial ratios from 2010 to 2014. In this research using Altman model for bankruptcy in the limit on property development companies. The samples used were 35 companies using financial ratios as an indicator of the state of liquidity, efficient, leverage, and the probability of the company. This modeling a method discriminant analysis to obtain a good model. Results of discriminant analysis is obtained that affect the ratio current assets, current liabilities, net income, Retain Earnings, Total Assets, Operating Income, Net Sales for bankruptcy.;This study aimed to analyze for companies to be able to anticipate bankruptcy. This study use financial ratios from 2010 to 2014. In this research using Altman model for bankruptcy in the limit on property development companies. The samples used were 35 companies using financial ratios as an indicator of the state of liquidity, efficient, leverage, and the probability of the company. This modeling a method discriminant analysis to obtain a good model. Results of discriminant analysis is obtained that affect the ratio current assets, current liabilities, net income, Retain Earnings, Total Assets, Operating Income, Net Sales for bankruptcy., This study aimed to analyze for companies to be able to anticipate bankruptcy. This study use financial ratios from 2010 to 2014. In this research using Altman model for bankruptcy in the limit on property development companies. The samples used were 35 companies using financial ratios as an indicator of the state of liquidity, efficient, leverage, and the probability of the company. This modeling a method discriminant analysis to obtain a good model. Results of discriminant analysis is obtained that affect the ratio current assets, current liabilities, net income, Retain Earnings, Total Assets, Operating Income, Net Sales for bankruptcy.]"

"PT ABC merupakan distributor suku cadang alat berat produk Komatsu, salah satunya adalah komoditas GET (Ground engaging tools). Dalam penerapan pengelolaan Inventory serta supply chain management salah satu hal yang sangat penting yaitu forecasting, dimana dalam hal ini di PT ABC melakukan forecasting untuk suku cadang yang sangat dibutuhkan ketersediaannya dalam pemeliharaan alat berat dan dukungan layanan purna jual. Inventory merupakan suatu working capital yg cukup vital bagi PT ABC, sehingga diperlukan peningkatan efektifitas forecasting atau peramalan suku cadang yg sangat baik untuk mencapai inventory yang sehat dengan output ketersediaan suku cadang yang tinggi. Metode yang digunakan pada forecasting komoditas GET, yaitu metode Trend analysis dengan nilai safety stock dan lead time fix adjustment, dan Moving Average dengan menggunakan data aktual lead time serta safety stock dengan pertimbangan data historis fluktuasi demand. Analisis efektifitias forecasting dilakukan dengan melihat hasil dari akurasi, kontribusi, serta nilai error forecasting terhadap aktual demand yang terjadi, Berdasarkan hasil analisis menunjukkan bahwa metode forcasting moving average memiliki nilai error forecasting quantity lebih kecil, yaitu 35% dibandingkan metode trend analysis yang menghasilkan error forecasting quantity 98%.

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PT ABC as Distributor of Heavy equipment parts of Komatsu Product, such as GET (Ground engaging tools). In inventory controlling and supply chain managing, one of important thing is forecasting, while in this situation at PT ABC forecasting parts that is very use for Heavy equipment maintenance and also for supporting after sales services. Inventory is a vital working capital for PT ABC, it’s necessary to increase forecasting effectiveness to achieve health inventory with high Parts availability output. Forecasting method that use in GET commodity, are Trend analysis with safety stock and lead time number is fix adjustment, and moving average with lead time number is actual historical data and safety stock number considering fluctuating demand, this analysis carried out by analyze the result of accuracy, contribution, and also error number of forecasting quantity to the actual demand that occurs. Based on the results of the analysis, it shows that the forecasting moving average method has a smaller forecasting quantity error value, which is 35% compared to the trend analysis method which produces a forecasting quantity error of 98%."