Modeling Indonesian Gold Price Dynamics Using Artificial Intelligence and Vector Error Correction Model (VECM)
DOI:
https://doi.org/10.3333/jmpl.v12i1.132Keywords:
Model Koreksi Kesalahan Vektor, Harga Emas, Kecerdasan Buatan, Python, Nilai TukarAbstract
ABSTRACTThis study aims to examine the extent to which key macroeconomic variables namely inflation, the USD exchange rate, and interest rates significantly influence gold prices in Indonesia. By identifying price trends and patterns, the research seeks to determine the most relevant variables for inclusion in subsequent studies focused on forecasting future gold prices for Bullion Business.
The study employs the Vector Error Correction Model (VECM) to analyze long-term relationships, utilizing monthly time-series data from 2013 to 2025. Additionally, it incorporates Artificial Intelligence techniques to enhance predictive analysis. This research also addresses the limited contribution of Indonesian scholars over the past three years, both in Indonesian- and English-language publications, particularly in studies integrating long-term time-series data and advanced analytical methods. The results indicate that all datasets are nonlinear and non-stationary, making the VECM approach unsuitable, despite conducting the Augmented Dickey-Fuller test and applying second-order differencing.
Keyword: Vector Error Correction Model; Gold Price; Artificial Intelligence; Python; Exchange Rate
ABSTRAK
Penelitian ini bertujuan untuk mengkaji sejauh mana variabel-variabel makroekonomi utama, yaitu inflasi, nilai tukar USD, dan suku bunga, secara signifikan memengaruhi harga emas di Indonesia. Dengan mengidentifikasi tren dan pola harga, penelitian ini berupaya menentukan variabel yang paling relevan untuk dimasukkan dalam studi lanjutan yang berfokus pada peramalan harga emas di masa depan untuk Pebisnis Emas Batangan.
Penelitian ini menggunakan metode Vector Error Correction Model (VECM) untuk menganalisis hubungan jangka panjang dengan memanfaatkan data runtun waktu bulanan periode 2013 - 2025. Selain itu, penelitian ini juga mengintegrasikan teknik Artificial Intelligence untuk meningkatkan akurasi analisis prediktif. Penelitian ini turut menjawab keterbatasan kontribusi akademisi Indonesia dalam tiga tahun terakhir, baik dalam publikasi berbahasa Indonesia maupun Inggris, khususnya pada studi yang menggabungkan data runtun waktu jangka panjang dan metode analisis lanjutan. Hasil penelitian menunjukkan bahwa seluruh dataset bersifat nonlinier dan tidak stasioner, sehingga pendekatan VECM tidak sesuai digunakan, meskipun telah dilakukan uji Augmented Dickey-Fuller dan penerapan diferensiasi dua kali.
Kata kunci: Model Koreksi Kesalahan Vektor; Harga Emas; Kecerdasan Buatan; Python, Nilai Tukar
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