Please use this identifier to cite or link to this item: https://repositori.uma.ac.id/handle/123456789/30851
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dc.contributor.advisorAnanda, Rana Fathinah-
dc.contributor.authorFebryna, Annisa Nanda-
dc.date.accessioned2026-08-07T04:02:07Z-
dc.date.available2026-08-07T04:02:07Z-
dc.date.issued2026-03-
dc.identifier.urihttps://repositori.uma.ac.id/handle/123456789/30851-
dc.description119 Halamanen_US
dc.description.abstractPenelitian ini bertujuan untuk memprediksi kondisi financial distress serta melihat tingkat akurasi masing masing metode yaitu metode Altman Z-Score dan Zmijewski pada perusahaan subsektor otomotif yang terdaftar di Bursa Efek Indonesia periode 2023–2024. Populasi dalam penelitian ini berjumlah 20 perusahaan, dengan 17 perusahaan yang dipilih sebagai sampel melalui teknik purposive sampling. Penelitian ini menggunakan pendekatan kuantitatif dengan data sekunder berupa laporan keuangan perusahaan. Metode analisis yang digunakan adalah analisis deskriptif kuantitatif melalui perhitungan rasio-rasio keuangan sesuai dengan model Altman Z-Score dan Zmijewski. Hasil penelitian menunjukkan bahwa berdasarkan metode Altman Z-Score, seluruh perusahaan sampel berada dalam kondisi non-financial distress pada tahun 2023, sedangkan pada tahun 2024 terdapat satu perusahaan yang berada pada kategori grey area. Sementara itu, berdasarkan metode Zmijewski, seluruh perusahaan berada dalam kondisi non-financial distress pada tahun 2023, dan pada tahun 2024 terdapat dua perusahaan yang terindikasi mengalami financial distress. Berdasarkan Tingkat akurasi metode Altman Z-Score dalam memprediksi kondisi perusahaan sebesar 94,12%, sedangkan metode Zmijewski sebesar 88,24% dalam memprediksi kebangkrutan perusahaan subsektor otomotif. This study aims to predict financial distress conditions and to examine the level of accuracy of the Altman Z-Score and Zmijewski methods in automotive sub-sector companies listed on the Indonesia Stock Exchange during the 2023–2024 period. The population of this study consisted of 20 companies, with 17 companies selected as samples using purposive sampling technique. This research employed a quantitative approach using secondary data in the form of companies’ financial statements. The data were analyzed using descriptive quantitative analysis through the calculation of financial ratios based on the Altman Z-Score and Zmijewski models. The results indicate that based on the Altman Z-Score method, all sample companies were categorized as non-financial distress in 2023, while in 2024 one company was classified in the grey area category. Meanwhile, based on the Zmijewski method, all companies were categorized as non-financial distress in 2023, and in 2024 two companies were indicated to be experiencing financial distress. The accuracy level of the Altman Z-Score method in predicting company conditions was 94.12%, while the Zmijewski method showed an accuracy level of 88.24% in predicting bankruptcy among automotive sub-sector companies.en_US
dc.language.isoiden_US
dc.publisherUniversitas Medan Areaen_US
dc.relation.ispartofseriesNPM;228330015-
dc.subjectFinancial Distressen_US
dc.subjectAltman Z-Scoreen_US
dc.subjectZmijewskien_US
dc.subjectKebangkrutanen_US
dc.titleAnalisis Prediksi Financial Distress Dengan Metode Altman Z-Score Dan Zmijewski Pada Perusahaan Subsektor Otomotif Yang Terdaftar Di Bursa Efek Indonesia Periode 2023-2024en_US
dc.title.alternativeFinancial Distress Prediction Analysis Using the Altman Z-Score and Zmijewski Methods In Automotive Subsector Companies Listed on the Indonesia Stock Exchange for the 2023-2024 Perioden_US
dc.typeSkripsi Sarjanaen_US
Appears in Collections:SP - Accountancy

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