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All Journal Jurnal Ilmiah Mahasiswa FEB Fair Value: Jurnal Ilmiah Akuntansi dan Keuangan
Farida Eka Putri
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Economics, Econometrics & Finance Education

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PREDIKSI KEBANKRUTAN PADA PERUSAHAAN AUTOMOTIVE AND ALLIANCES YANG TERDAFTAR DI BURSA EFEK INDONESIA DENGAN MENGGUNAKAN ANALISA DISKRIMINAN (Z-SCORE) Farida Eka Putri; Mychelia Champaca
Jurnal Ilmiah Mahasiswa FEB Vol 1, No 2: Semester Genap 2012/2013
Publisher : Fakultas Ekonomi dan Bisnis Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (153.557 KB)

Abstract

This study aims to determine the level of corporate bankruptcy using discriminant analysis in automotive companies listed on the Indonesia Stock Exchange. Because automotive companies have a considerable role in the Indonesian economy. This study uses discriminant analysis (Z-score) to see how the predictions of bankruptcy period 2008-2010 in automotive companies. Calculating each bankruptcy prediction on each company totaling 17 companies. The data used in this study were obtained annual financial statements in the book Indonesian Capital Market Directory. The analysis technique used is discriminant analysis using the variables of the Altman Z-score of five is X1 = Net Working Capital to Total Assets, X2 = Retained Earnings to Total Assets, X3 = EBIT to Total Assets, X4 = Market Value of Equity to Book Value of Liabilities and X5 = Sales to Total Assets. It has the formula Z-Score = - 4.267. X_1 x_2 1.26 1.78 1.663 0.842 X_3 X_4 X_5 1.049. With Z-Score criteria> 0.857 categorized as healthy companies <.857 financial distress category. The results of this study indicate that the Altman Z-Score models can be implemented in detecting the possibility of bankruptcy in automotive companies listed on the Indonesia Stock Exchange. Altman Z-Score model and discriminant analysis have similar results in predicting bankruptcy on 17 automotive companies. The results of Z-Score of discriminant analysis on the automotive companies were able to group two categories, namely health and financial distress. During the period of observation shows there are 7 companies included in a healthy condition and as many as 10 companies included in the category of financial distress. Keywords: Financial Distress, Z-Score, Bankruptcy Prediction, Discriminant Analysis
PREDIKSI KEBANKRUTAN PADA PERUSAHAAN AUTOMOTIVE AND ALLIANCES YANG TERDAFTAR DI BURSA EFEK INDONESIA DENGAN MENGGUNAKAN ANALISA DISKRIMINAN (Z-SCORE) Putri, Farida Eka; Champaca, Mychelia
Jurnal Ilmiah Mahasiswa FEB Vol. 1 No. 2
Publisher : Fakultas Ekonomi dan Bisnis Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to determine the level of corporate bankruptcy using discriminant analysis in automotive companies listed on the Indonesia Stock Exchange. Because automotive companies have a considerable role in the Indonesian economy. This study uses discriminant analysis (Z-score) to see how the predictions of bankruptcy period 2008-2010 in automotive companies. Calculating each bankruptcy prediction on each company totaling 17 companies. The data used in this study were obtained annual financial statements in the book Indonesian Capital Market Directory. The analysis technique used is discriminant analysis using the variables of the Altman Z-score of five is X1 = Net Working Capital to Total Assets, X2 = Retained Earnings to Total Assets, X3 = EBIT to Total Assets, X4 = Market Value of Equity to Book Value of Liabilities and X5 = Sales to Total Assets. It has the formula Z-Score = - 4.267. X_1 x_2 1.26 1.78 1.663 0.842 X_3 X_4 X_5 1.049. With Z-Score criteria> 0.857 categorized as healthy companies <.857 financial distress category. The results of this study indicate that the Altman Z-Score models can be implemented in detecting the possibility of bankruptcy in automotive companies listed on the Indonesia Stock Exchange. Altman Z-Score model and discriminant analysis have similar results in predicting bankruptcy on 17 automotive companies. The results of Z-Score of discriminant analysis on the automotive companies were able to group two categories, namely health and financial distress. During the period of observation shows there are 7 companies included in a healthy condition and as many as 10 companies included in the category of financial distress. Keywords: Financial Distress, Z-Score, Bankruptcy Prediction, Discriminant Analysis
Peran kompetensi dan motivasi kerja dalam meningkatkan etos kerja pada Politeknik Bisnis Digital Indonesia Putri, Farida Eka; Sari, Mega Puspita
Fair Value: Jurnal Ilmiah Akuntansi dan Keuangan Vol. 8 No. 3 (2025): Fair Value: Jurnal Ilmiah Akuntansi dan Keuangan
Publisher : Departement Of Accounting, Indonesian Cooperative Institute, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55904/fairvalue.v8i3.6050

Abstract

Penelitian ini bertujuan untuk mengetahui peran kompetensi dan motivasi kerja dalam meningkatkan etos kerja pegawai di Politeknik Bisnis Digital Indonesia. Kompetensi yang dimaksud mencakup pengetahuan, keterampilan, konsep diri dan sifat pribadi, sedangkan motivasi kerja meliputi tujuan karir, pengembangan diri, imbalan dan kondisi kerja. Penelitian menggunakan pendekatan kualitatif deskriptif dengan metode wawancara mendalam dan observasi kepada beberapa informan yang mewakili berbagai divisi, antara lain HRD, keuangan, humas, kaprodi, dosen, IT, dan marketing. Hasil penelitian menunjukkan bahwa secara umum kompetensi pegawai di Politeknik Bisnis Digital Indonesia telah memadai di masing-masing divisi. Pengetahuan dan keterampilan yang dimiliki sesuai dengan posisi kerja, serta didukung oleh pelatihan internal dan kesempatan pengembangan diri. Namun, motivasi kerja dinilai masih perlu ditingkatkan, terutama melalui kesadaran individu maupun organisasi. Etos kerja yang sudah diterapkan institudi berjaln dengan baik, tetapi diperlukan strategi tambahan berupa pelatihan berkelanjutan, suasana kerja yang positif, serta sistem penghargaan yang lebih optimal.
Co-Authors Mychelia Champaca Sari, Mega Puspita