This study aimed at analyzing how the results of the Grover, Springate and Zmijewski models predict the bankruptcy of PT Citra Maharlika Nusantara Corpora Tbk for the period of June 2013 - September 2016. This study also aimed at measuring the accuracy of the bankruptcy prediction model and determined which predictive model of the three models was the most accurate. From the data analysis, it was found that Springate model was the most accurate prediction model with 100% accuracy rate to predict the bankruptcy of PT Citra Maharlika Nusantara Corpora Tbk compared to the Grover model with an accuracy rate of 71.48% and Zmijewski model with the lowest accuracy rate of 21.48%. The limitations of this study was this study only carried out in one company, thus in the future it is expected that the model will be tested in more than one company and type of business sector.Keywords: Financial Distress, Grover, Springate, Zmijewski ModelsPenelitian ini bertujuan untuk menganalisis bagaimana hasil dari model Grover, Springate dan Zmijewski dalam memprediksi kebangkrutan PT Citra Maharlika Nusantara Corpora Tbk periode Juni 2013 – September 2016 serta mengukur tingkat akurasi model prediksi kebangkrutan tersebut dan menentukan model prediksi manakah diantara ketiga model tersebut yang paling akurat. Model Springate menjadi model prediksi paling akurat dengan tingkat akurasi 100% untuk memprediksi kebangkrutan PT Citra Maharlika Nusantara Corpora Tbk dibandingakan dengan model Grover dengan tingkat akurasi 71,48% dan model Zmijewski dengan tingkat akurasi paling rendah sebesar 21,48%.Keterbatasan penelitian ini terletak pada pengujian model pada satu perusahaan di satu unit sektor usaha, kedepan bisa dilakukan pengujian pada berbagai jenis sektor usaha.Kata kunci: Financial Distress, Model Grover, Springate, Zmijewski
Abstrak Multivariate Discriminant Analysis (MDA) model Altman atau yang sering disebut dengan MDA Altman merupakan salah satu alat analisis di dalam memprediksi kebangkrutan perusahaan melalui kombinasi persamaan rasio likuiditas, profitabilitas, leverage dan aktivitas. Selain sebagai alat analisis, persamaan MDA Altman juga dipergunakan untuk mencirikan atau membedakan satu group perusahaan dengan group perusahaan lainnya. Dari tahapan tehnik analisa data diperoleh hasil yakni terdapat perbedaan kinerja keuangan antara perusahaan delist dan non-delist berdasarkan perhitungan MDA Altman serta diperoleh tingkat keakuratan MDA Altman dalam memprediksi kesulitan keuangan dan kebangkrutan suatu perusahaan untuk mendiskriminasikan 2 group perushaaan (delist dan non-delist) tingkat akurasi mencapai rata-rata 90%. Sehingga dapat dikatakan bahwa persamaan MDA Altman yang diteliti dalam penelitian ini layak untuk digunakan memprediksi kesulitan dan kebangkrutan perusahaan Kata Kunci: Analisis Akurasi, Uji Beda, MDA Altman PENDAHULUAN Bursa efek adalah merupakan sebuah fasilitas tempat bertemunya perusahaan dengan investor dalam rangka memperoleh modal. Di dalam bursa efek terjadi hubungan timbal balik antara investor dengan emiten, dimana investor menanamkan modalnya pada perusahaan dengan maksud untuk mendapatkan keuntungan sementara perusahaan memperoleh tambahan modal untuk ekspansi ataupun operasi perusahaan. Namun, satu hal penting yang harus diperhatikan oleh investor sebelum melakukan investasi terhadap perusahaan tertentu, perlu dilakukan prediksi dan perhitungan untuk menghindari kerugian yang bisa terjadi di kemudian hari.
The concept of the efficient capital markets has become a topic of debate is fascinating and quite controversial in the field of finance. Since the introduction his the efficient market hypothesis, comes a variety of behavior of irregularity or discrepancy in the capital markets. Irregularity is referred to as a market anomaly (market anomaly). The Market anomaly that became a lot of attention is the anomalous effect of calendar. These anomalies are the day of the week effect and the month of the year effect. This research was conducted due to the results of several studies that are not consistent on the day of the week effect and the month of the year effect in obtaining the return of shares in Indonesia stock exchange.
This study aimed at examining the effect of financial inclusion on the financial stability of banks in Indonesia. The data panel used in the study during the period 2007-2017 and were analyzed using multiple regression, financial inclusion variables using MSME credit growth indicators and GDP growth rates', while the dependent variable banking financial stability used the non-performing loan ratio (NPL) indicator. The results showed that MSME credit growth had a negative influence on credit risk which was associated with better stability. GDP growth rates had a positive and significant direct effect on financial stability (NPL) of banks in Indonesia. At the same time, it had a significant influence as a moderating variable on the relationship between financial inclusion and financial stability of banks in Indonesia.
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