Sistem Prediksi Penjualan Frozen Food dengan Metode Monte Carlo (Studi Kasus: Supermama Frozen Food)
DOI:
https://doi.org/10.24002/jbi.v13i02.6496Keywords:
forecasting, frozen food, Monte Carlo, prediksi penjualan, sales predictionAbstract
Abstract. Frozen Food Sales Prediction System Case Study of Supermama Frozen Food Using the Monte Carlo Method. Frozen processed food is increasingly popular, so frozen food stores are getting easy to find. Supermama Frozen Food is a store that sells a variety of frozen foods. Not all frozen food stocks can get sold out before their expiration dates. This causes the store's profits to decrease. Therefore, a frozen food sales prediction system was necessarily made to help the store estimate its stock to minimise store losses. The research method used in predicting sales was the Monte Carlo method. Testing methods used were accuracy and MAPE. The test results of using accuracy were 89.66%, and MAPE error accuracy test showed 12.6%. Based on the results, it is concluded that the Monte Carlo method can predict frozen food sales.
Keywords: forecasting, frozen food, Monte Carlo, sales prediction
Abstrak. Makanan yang diolah dengan cara dibekukan semakin digemari masyarakat sehingga toko makanan beku menjadi mudah ditemui. Supermama Frozen Food merupakan salah satu toko yang menjual aneka makanan beku. Tidak semua stok makanan beku terjual habis hingga masa konsumsi berakhir. Hal tersebut membuat keuntungan toko menurun. Oleh karena itu di buatlah sistem
prediksi penjualan makanan beku yang dapat mengestimasi stok sehingga meminimalisir kerugian toko. Metode yang digunakan dalam memprediksi penjualan yaitu metode Monte Carlo. Pengujian metode yang digunakan yaitu akurasi dan MAPE. Hasil pengujian menggunakan akurasi ialah 89.66% dan pengujian akurasi error MAPE menghasilkan nilai 12.6%. Berdasar hasil pengujian metode tersebu, metode Monte Carlo disimpulkan dapat digunakan dalam prediksi penjualan frozen food.
Kata Kunci: forecasting, frozen food, Monte Carlo, prediksi penjualan.
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