Prediksi Tren Risiko Keuangan Perusahaan Berdasarkan Model Machine Learning (ARIMA) : Tinjauan Literatur
Kata Kunci:
Machine Learning, ARIMA, Prediksi Risiko Keuangan, Model Keuangan, Kecerdasan Buatan, Deret WaktuAbstrak
Penelitian ini membahas peran teknologi kecerdasan buatan (AI) dalam meningkatkan prediksi risiko keuangan perusahaan melalui penerapan model Autoregressive Integrated Moving Average (ARIMA) yang didukung oleh machine learning. Menggunakan analisis literatur sistematis, penelitian ini mengeksplorasi bagaimana ARIMA, dengan bantuan AI, dapat diterapkan dalam manajemen risiko keuangan untuk mengidentifikasi tren jangka pendek dan jangka panjang, mendeteksi anomali keuangan, serta meningkatkan kualitas pengambilan keputusan. Model ARIMA berbasis machine learning memungkinkan identifikasi pola keuangan abnormal secara lebih cepat dan akurat, yang sangat penting dalam membantu perusahaan merespon risiko yang berpotensi mengganggu stabilitas finansial. Temuan utama menunjukkan bahwa kombinasi ARIMA dan AI tidak hanya mempermudah analisis data keuangan yang besar dan kompleks, tetapi juga memperluas potensi manajemen risiko keuangan berbasis data dengan memberikan wawasan yang lebih mendalam. Dengan mengintegrasikan machine learning, ARIMA menjadi lebih efektif dalam menangani data keuangan yang dinamis dan fluktuatif, sehingga perusahaan dapat mengantisipasi risiko secara lebih proaktif. Studi ini menggarisbawahi potensi besar AI dan ARIMA dalam membantu perusahaan membangun sistem prediksi risiko yang adaptif dan presisi tinggi, menawarkan peluang baru untuk memperkuat ketahanan finansial di lingkungan bisnis yang terus berubah.
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Referensi
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Hak Cipta (c) 2024 Deni Sunaryo, Hamdan, Alfina Anggriani, Cecilia Winata, Dian Denta Alumi
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