Pemodelan Prediksi Ekspor Kopi Indonesia Berbasis Algoritma Machine Learning
Authors
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Hilda Yulia Novita,
Universitas Buana Perjuangan Karawang,
Indonesia
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Tatang Rohana,
Universitas Buana Perjuangan Karawang,
Indonesia
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Euis Nurlaelasari,
Universitas Buana Perjuangan Karawang,
Indonesia
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Elsa Elvira Awal,
Universitas Buana Perjuangan Karawang,
Indonesia
Hilda Yulia Novita,
Universitas Buana Perjuangan Karawang,
Indonesia
Tatang Rohana,
Universitas Buana Perjuangan Karawang,
Indonesia
Euis Nurlaelasari,
Universitas Buana Perjuangan Karawang,
Indonesia
Elsa Elvira Awal,
Universitas Buana Perjuangan Karawang,
Indonesia
DOI:
https://doi.org/10.55338/jumin.v6i6.7097Keywords:
Machine Learning, Linear Regression, Neural Networks, Gradient Boosting, Prediksi Ekspor KopiAbstract
Penelitian ini bertujuan untuk membangun model prediksi ekspor kopi di Indonesia dengan menggunakan tiga algoritma machine learning, yaitu regresi inier, neural networks, dan gradient boosting. Data yang digunakan berasal dari data historis ekspor kopi Indonesia. Penelitian dilakukan melalui tahapan pra-pemrosesan data, pemodelan, dan evaluasi kinerja masing-masing algoritma. Hasil penelitian menunjukkan bahwa ketiga algoritma mampu memprediksi ekspor kopi dengan performa yang cukup baik. Algoritma Linear Regression memberikan hasil terbaik dengan nilai mean squared error (MSE) sebesar 0.0000867, mean absolute error (MAE) sebesar 0.00766, dan skor R² sebesar 95%. neural networks menghasilkan MSE sebesar 0.000171, MAE sebesar 0.01196, dan skor R² sebesar 91%. Sementara itu, gradient boosting menunjukkan performa terendah dengan MSE sebesar 0.01918 dan skor R² sebesar 74%. Temuan ini menunjukkan bahwa pendekatan machine learning dapat digunakan sebagai alat bantu dalam memprediksi tren ekspor komoditas secara akurat.
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