Analisis Perkiraan Biaya F&B (Makanan & Minuman) Dengan Metode Moving Average Pada Pola E-Commerce Hotel XYZ
Indonesia
Abstract
Forecasting is made because of the complexity and uncertainty faced by decision makers (5 and = 0.9). The use of these two forecasting methods is to compare which forecasting method is more accurate and closer to the true value. The research method used starts from collecting data, determining forecast methods, calculating forecasts, selecting forecasts, and drawing conclusions. The calculation of the estimated results for F&B costs at Puri Santrian Hotel Sanur is based on the Single Moving Average MA. 3 of 1.143.941.601,89, the MAD value of 113.205.931, and the Single Moving Average (MA.3) of 112.700. Using exponential smoothing (ES=0.9), the forecast value for the period ending January 2017 is 898.343.836,01 with an MAD value of 115.870.591,88 and an MSE value (ES=0.9) of 21.219. Data series using the moving average method (Single Moving Average Method and Exponential Smoothing Method) can be done by calculating the minimum error values MAD and MSE, using the two methods above MAD and MSE after calculating the error, MAD is 3.686.238.23 (absolute value) and the MSE value is 13.588.352.306.255.
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References
D. Andelawati and M. V. Overbeek, “SISTEM PREDIKSI PENJUALAN MAKANAN DAN MINUMAN PADA KAFE DENGAN MENGGUNAKAN METODE TRIPLE EXPONENTIAL SMOOTHING,” Pros. SEMMAU, pp. 131–136, 2021.
A. A. SETYOWATI, “PENERAPAN METODE SINGLE EXPONENTIAL SMOOTHING DAN DOUBLE EXPONENTIAL SMOOTHING PADA PERAMALAN PENJUALAN PAKAIAN,” UNIVERSITAS NUSANTARA PGRI KEDIRI, 2017.
P. J. Brockwell and R. A. Davis, Springer Texts in Statistics Introduction to Time Series and Forecasting. 2016. [Online]. Available: http://www.springer.com/series/417
N. L. W. S. R. Ginantra and I. B. G. Anandita, “Penerapan Metode Single Exponential Smoothing Dalam Peramalan Penjualan Barang,” J. Sains Komput. Inform., vol. 3, no. 2, pp. 433–441, 2019.
M. Qamal, “Peramalan Penjualan Makanan Ringan Dengan Metode Single 10 Exponential Smoothing,” J. Penelit. Tek. Inform., pp. 25–35, 2019.
Sylvia, “Implementasi dan Analisa Metode Peramalan Exponential Smoothing dan Weighted Moving Average Untuk Permintaan Produk Minuman Kopi K di CV Fajar Timur Lestari,” vol. 3, no. 4, pp. 139–147, 2017.
A. Agnes and Manuharawati, “Forecasting Fitness Gym Membership pada Pusat Kebugaran ‘The Body Art Fitness, Aerobic & Pool’ menggunakan Metode Exponential Smoothing,” J. Ilm. Mat., vol. 3, no. 6, pp. 1–7, 2017.
N. P. L. Santiari and I. G. S. Rahayuda, “Analisis Perbandingan Metode Single Exponential Smoothing dan Single Moving Average dalam Peramalan Pemesanan,” Openjurnal, vol. 6, no. 2, p. 7, 2021, [Online]. Available: http://openjournal.unpam.ac.id/index.php/informatika/article/view/10135
R. D. Laksmana, E. Santoso, and B. Rahayudi, “Prediksi Penjualan Roti Menggunakan Metode Exponential Smoothing (Studi Kasus : Harum Bakery),” J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 3, no. 5, pp. 4933–4941, 2019, [Online]. Available: http://j-ptiik.ub.ac.id/index.php/j-ptiik/article/view/5375/2525
S. D. Pratiwi, “Peramalan Tingkat Penghunian Tempat Tidur Hotel Bintang Tiga Kota Surakarta Menggunakan Metode Autoregressive Integrated Moving Average (ARIMA),” Indones. J. Appl. Stat., vol. 2, no. 1, p. 53, 2019, doi: 10.13057/ijas.v2i1.31428.
A. Nurlifa and S. Kusumadewi, “Sistem Peramalan Jumlah Penjualan Menggunakan Metode Moving Average Pada Rumah Jilbab Zaky,” INOVTEK Polbeng - Seri Inform., vol. 2, no. 1, p. 18, 2017, doi: 10.35314/isi.v2i1.112.
J. Haiser and B. Render, Manajemen Operasi. Jakarta: Salemba Empat, 2015.
L. Arsyad, Peramalan Bisnis, First Edition, First Edit. Yogyakarta: Universitas Gajah Mada, 2001.
D. F. Maulana, Daryanto, and D. Lusiana, “PENERAPAN METODE SINGLE EXPONENTIAL SMOOTHING PADA PERSEDIAAN BAHAN BAKU IKAN PINDANG ASAPAN (STUDI : UMKM IKAN ASAPAN)”.
M. D. B. Barus, M. Mustafa, and F. S. Thahirah, “Single Eksponensial Smoothing: Analisis Forecasting Dalam Perencanaan Produksi (Studi Kasus Pt. Food Beverages Indonesia),” Semin. Soc. Sci. Eng. Hum., pp. 199–212, 2021.
R. Utami and S. Atmojo, “Perbandingan Metode Holt Eksponential Smoothing dan Winter Eksponential Smoothing Untuk Peramalan Penjualan Souvenir,” J. Ilm. Teknol. Inf. Asia, vol. 11, no. 2, p. 123, 2017, doi: 10.32815/jitika.v11i2.191.
A. Apriliani, H. Zainuddin, A. Agussalim, and Z. Hasanuddin, “Peramalan Tren Penjualan Menu Restoran Menggunakan Metode Single Moving Average,” J. Teknol. Inf. dan Ilmu Komput., vol. 7, no. 6, p. 1161, 2020, doi: 10.25126/jtiik.2020722732.
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