Evaluating the Effectiveness of Quantitative Earnings Management Detection Models: Evidence from Financial Statements of Fraud Litigated Public Companies in Indonesia

AISYAH AFIFAH DARMAWAN, Prof. Dr. Peter Mayer; Claudia Steinkuhl, M.A.

2025 | Skripsi | AKUNTANSI

Skripsi ini menyelidiki efektivitas model deteksi manajemen laba kuantitatif—Jones Model, Modified Jones Model, dan Beneish M-Score—dalam mendeteksi kecurangan laporan keuangan pada perusahaan di Indonesia. Seiring kondisi korporasi Indonesia yang terus mengalami kasus kecurangan keuangan berulang akibat lemahnya tata kelola serta praktik akuntansi manipulatif yang telah dinormalisasi, diperlukan peninjauan apakah model deteksi populer tersebut benar-benar mampu mengindikasikan manipulasi. Dengan menggunakan desain studi kasus, penelitian ini menelaah perusahaan-perusahaan yang terlibat dalam kasus kecurangan keuangan yang telah dikonfirmasi secara hukum, khususnya pada tahun-tahun terjadinya kecurangan. Analisis menunjukkan bahwa walaupun model-model ini banyak digunakan dan bermanfaat untuk mengidentifikasi manipulasi laba secara keseluruhan, kinerjanya sangat bervariasi ketika diterapkan pada kasus kecurangan nyata di Indonesia. Hal ini sebagian disebabkan oleh konteks ekonomi, regulasi, dan tata kelola perusahaan yang khas di Indonesia, yang menimbulkan keterbatasan model—termasuk tingginya frekuensi false negative. Selain itu, ada indikasi bahwa model-model kuantitatif tersebut mengabaikan skema manipulasi kecil dan penyimpangan operasional, sehingga mempertanyakan keandalan mereka jika digunakan secara tunggal. Pada akhirnya, studi ini memberikan pelajaran empiris mengenai kekuatan dan kelemahan metode deteksi yang ada, sekaligus menyoroti perlunya peningkatan fungsi auditor, penerapan skema regulasi yang lebih khusus, dan pengembangan model deteksi yang lebih baik untuk secara efektif menangani kecurangan keuangan di pasar Indonesia.

This paper investigates the efficacy of quantitative earnings management detection models—the Jones Model, Modified Jones Model, and Beneish M-Score—for the detection of financial statement fraud in companies in Indonesia. As Indonesia's corporate landscape continues to experience recurring financial fraud cases driven by lax governance and normalized manipulative accounting practices, there is a need to examine if popular detection models accurately indicate manipulation. Utilizing a case study design, this study investigates companies that were engaged in legally confirmed cases of financial fraud and examined in particular the years in which fraud was reported. The analysis indicates that although these models are widely used and useful in identifying overall earnings manipulation, their performance greatly differs as applied in real cases of fraud in Indonesia. This is partly attributed to specific economic, regulatory, and corporate governance environments in Indonesia that pose possible model shortcomings, including high frequencies of false negatives. Further, indications are that these quantitative models ignore slight manipulation schemes and operating irregularities, questioning their sole reliability. In the end, this study provides empirical lessons on the strengths and weaknesses of available detection methods, highlighting the need for better auditor functions, specialized regulatory schemes, and improved detection models for better addressing financial fraud in the Indonesian market.

Kata Kunci : Earnings Management, Financial Fraud, Jones Model, Modified Jones Model, Beneish M-Score, Indonesia, Corporate Governance, Fraud Detection.