PREDIKSI FINANCIAL DISTRESS MENGGUNAKAN MODEL ALTMAN MODIFIKASI, GROVER, ZMIJEWSKI, SPRINGATE DAN CA-SCORE PADA INDEKS SAHAM SYARIAH INDONESIA (ISSI)

FAHRIZAL, NIM. 15840019 (2019) PREDIKSI FINANCIAL DISTRESS MENGGUNAKAN MODEL ALTMAN MODIFIKASI, GROVER, ZMIJEWSKI, SPRINGATE DAN CA-SCORE PADA INDEKS SAHAM SYARIAH INDONESIA (ISSI). Skripsi thesis, UNIVERSITAS ISLAM NEGERI SUNAN KALIJAGA YOGYAKARTA.

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Abstract

Bankruptcy risk is a threat that always looms over the company. Not only small companies, but also large companies hardly can escape from the shadow of bankruptcy. The objective of this study was to determine the level of financial distress using the Altman Modified Model, Grover, Zmijewski, Springate and Ca-Score on the companies incorporated in the Indonesian Sharia Stock Index (ISSI). Purposive sampling techniques was used to take the samples by applying secondary data to result 131 companies as the study samples, i.e. 114 companies in the healthy category and 17 companies experienced financial distress. Data were processed using EVIEWS version 10 by applying logistic regression test data analysis techniques.The results showed that the Modified Altman Model, the Grover Prediction Model, the Zmijewski Prediction Model and the Springate Prediction Model were accurate in predicting financial distress on the Indonesian Sharia Stock Index (ISSI), while the Ca-Score prediction model was not. ( INDONESIA ) Risiko Kebangkrutan menjadi ancaman yang selalu membayangi perusahaan. tidak hanya perusahaan kecil, perusahaan besar sekalipun tidak luput dari bayang-bayang kebangkrutan. Penelitian ini bertujuan untuk mengetahui tingkat financial distress dengan menggunakan model Model Altman Modifikasi, Grover, Zmijewski, Springate dan Ca-Score pada perusahaan yang tergabung dalam Indeks Saham Syariah Indonesia (ISSI). Sampel di ambil dengan menggunakan teknik purposive sampling menggunakan data sekunder sehingga menghasilkan 131 perusahaan yang menjadi sampel penelitian, 114 perusahaan kategori sehat dan 17 perusahaan mengalami financial distress. Data diolah menggunakan EVIEWS versi 10 menggunakan teknik analisis data uji regresi logistik. Hasil penelitian menunjukan bahwa model Altman modifikasi, model prediksi Grover, model prediksi Zmijewski dan model prediksi Springate akurat dalam memprediksi financial distress pada Indeks Saham Syariah Indonesia (ISSI), sedangkan model prediksi Ca-Score tidak akurat dalam memprediksi financial distress.

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