Pemodelan dengan Algoritma Artificial Bee Colony: Prediksi Harga Logam Mulia (Emas) Ditinjau dari Nilai Tukar USD dan Transaksi Emas
DOI:
https://doi.org/10.55616/jitu.v7i1.1210Keywords:
Harga Emas, nilai tukar USD, Artificial Bee Colony, Regresi, PrediksiAbstract
Fluktuasi harga logam mulia dipengaruhi oleh kondisi ekonomi dan aktivitas pasar, terutama perubahan nilai tukar dolar Amerika Serikat dan voflume transaksi emas. Penelitian ini bertujuan membangun model prediksi harga emas menggunakan regresi yang parameternya dioptimasi dengan Algoritma Artificial Bee Colony (ABC) dan mekanisme Lévy Flight. Data sekunder mingguan periode Januari 2023 hingga September 2025 terdiri atas harga emas sebagai variabel dependen serta nilai tukar USD dan volume transaksi sebagai variabel independen. Data diperiksa, dikonversi ke tipe numerik, distandardisasi menggunakan Z-score, kemudian dimodelkan dengan regresi linear, log-linear, dan polynomial degree-2. ABC menggunakan fase employed bee, onlooker bee, dan scout bee untuk meminimalkan fungsi objektif, sedangkan Lévy Flight digunakan untuk memperluas eksplorasi ruang solusi. Kinerja model dievaluasi menggunakan koefisien determinasi, Root Mean Square Error, Mean Absolute Error, dan Mean Absolute Percentage Error. Hasil pengujian menunjukkan bahwa regresi linear merupakan model terbaik secara keseluruhan dengan R² sebesar 0,7372137, RMSE Rp354.149, MAE Rp277.395, dan MAPE 10,97%. Regresi log-linear menghasilkan RMSE sedikit lebih kecil, tetapi nilai R² dan MAPE-nya lebih rendah dibandingkan regresi linear. Model polynomial degree-2 menunjukkan performa terendah dengan R² mendekati nol dan MAPE 31,42%. Temuan ini menunjukkan bahwa ABC dapat digunakan untuk memperoleh parameter regresi yang stabil, sedangkan kompleksitas model yang lebih tinggi tidak selalu menghasilkan akurasi yang lebih baik pada karakteristik data penelitian ini.
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