ANALISIS TINGKAT AKURASI MODEL ALTMAN, SPRINGATE, GROVER, ZMIJEWSKI, OHLSON, DAN TAFFLER UNTUK MEMPREDIKSI FINANCIAL DISTRESS

ANURA, HAFIZH RAFI (2024) ANALISIS TINGKAT AKURASI MODEL ALTMAN, SPRINGATE, GROVER, ZMIJEWSKI, OHLSON, DAN TAFFLER UNTUK MEMPREDIKSI FINANCIAL DISTRESS. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

This research aims to measure the accuracy levels of each financial distress prediction model, namely the Altman, Springate, Grover, Zmijewski, Taffler, and Ohlson models, in predicting the likelihood of financial distress in pharmaceutical sub-sector companies on the Indonesia Stock Exchange (IDX) during the period 2019-2023. The population in this study consists of all pharmaceutical sub-sector companies listed on the IDX. The research sample was selected based on specific criteria (purposive sampling), resulting in a total of 9 company samples. The researcher utilized archival data collection methods in the form of secondary data. The data analysis techniques employed include scoring each model, descriptive analysis test, panel data regression analysis, and accuracy and error level tests. The results of this study indicate that the Grover model is the financial distress prediction model with the highest accuracy rate at 97,5%. Followed by the Taffler model at 95%, the Zmijewski model at 90%, the Ohlson model at 87,5%, the Altman model at 77,5%, and finally the Springate model at 75%. Keywords: financial distress, Altman, Springate, Grover, Zmijewski, Taffler, Ohlson Penelitian ini bertujuan untuk mengukur tingkat akurasi masing-masing model prediksi financial distress, yaitu model Altman, Springate, Grover, Zmijewski, Taffler, dan Ohlson, dalam memprediksi kemungkinan terjadinya financial distress pada perusahaan sub sektor farmasi di Bursa Efek Indonesia (BEI) periode 2019- 2023. Populasi dalam penelitian ini adalah semua perusahaan sub sektor farmasi di BEI. Sampel penelitian ini diambil berdasarkan kriteria tertentu (purposive sampling), dimana hasilnya terdapat 9 sampel perusahaan. Peneliti menggunakan metode pengumpulan data arsip berupa data sekunder. Teknik analisis data yang dipakai yaitu lewat menghitung score tiap model, uji analisis deskriptif, analisis regresi data panel dan uji tingkat akurasi dan error. Hasil dari penelitian ini menujukkan bahwa Grover merupakan model prediksi financial distress yang memiliki tingkat akurasi tertinggi yaitu 97,5%. Disusul oleh model Taffler sebesar 95%, model Zmijewski 90%, model Ohlson 87,5%, model Altman 77,5%, dan terakhir model Springate sebesar 75%. Kata Kunci: financial distress, Altman, Springate, Grover, Zmijewski, Taffler, Ohlson

Item Type:	Thesis (S1)
Call Number CD:	FE/MJ. 24 478
NIM/NIDN Creators:	43121110138
Uncontrolled Keywords:	financial distress, Altman, Springate, Grover, Zmijewski, Taffler, Ohlson
Subjects:	000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 020 Library and Information Sciences/Perpustakaan dan Ilmu Informasi > 025 Operations, Archives, Information Centers/Operasional Perpustakaan, Arsip dan Pusat Informasi, Pelayanan dan Pengelolaan Perpustakaan > 025.1 Administration and Library Management/Administrasi dan Manajemen Perpustakaan > 025.11 Finance/Keuangan 300 Social Science/Ilmu-ilmu Sosial > 330 Economics/Ilmu Ekonomi 300 Social Science/Ilmu-ilmu Sosial > 330 Economics/Ilmu Ekonomi > 332 Financial Economics, Finance/Ekonomi Keuangan dan Finansial, Ekonomi Biaya dan Pembiayaan 600 Technology/Teknologi > 610 Medical, Medicine, and Health Sciences/Ilmu Kedokteran, Ilmu Pengobatan dan Ilmu Kesehatan > 615 Pharmacology and Therapeutics/Farmakologi dan Terapi Farmakologi > 615.4 Practical Pharmacy/Farmasi Praktis
Divisions:	Fakultas Ekonomi dan Bisnis > Manajemen
Depositing User:	khalimah
Date Deposited:	12 Oct 2024 01:32
Last Modified:	12 Oct 2024 01:32
URI:	http://repository.mercubuana.ac.id/id/eprint/92455

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