Abstract

Sales Volume Forecasting Red Guava Fruit (Psidium Guajava Linn.)in CV Moena Abadi Sejahtera 1This study aims to determine the factors that affect the sales volume of fruit Guava Red and estimating sales volume Guava fruit Red 2016, 2017, and 2018 in CV Moena Abadi Sejahtera 1. The data were taken within the last six years the year 2010 until 2015. this study used two models of the sales function is a linear function of sales and sales functions are transformed into a form logharitma tested with three criteria to get the best sales function model. The independent variables that affect the price of fruit Guava Red (PJBM), the price of fruit Bark (PSB), the price of fruit Ambon Banana (PPA), the price fruit Lumajang Oranges (PJL), and the price fruits Kintamani oranges (PJK). Sales function model which is transformed into the shape of a model function logharitma valid sales are LogQJBM = -7.267 - 0,227 log PJBM + 1,798 log PSB - 0,102 log PPA + 0,136 log PJL + 0,379 log PJK ± e. Factors that influence is Red Guava fruit prices, the price of fruit Salak Bali, Lumajang Citrus fruit prices, and the price Citrus fruits Kintamani. Estimated sales of Red Guava fruit using trend analysis and multiple linear regression to see the value of the coefficient of determination (R2), the largest and the value of the standard error (SE), the smallest so get the best forecasting method. Methods exponential trend is the best forecasting method is Y = 502.34 + 1.0023 t ± e. The estimation results of the Red Guava fruit sales in 2016, 2017, and 2018 continue to rise. CV Moena Abadi Sejahtera 1 should use a forecasting method to maintain the availability of the fruit in the store, especially the Red Guava fruit.

Highlights

  • This study aims to determine the factors that affect the sales volume of fruit Guava Red and estimating sales volume Guava fruit Red 2016, 2017, and 2018 in CV Moena Abadi Sejahtera 1

  • Selain melihat nilai Se, ukuran akurasi peramalan dalam penelitian kali ini juga dilihat dari nilai R2

  • USU, Surabaya. http://repository.usu.ac.id/.pdf. diunduh pada tanggal 29 Februari 2016

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Summary

Polinomial Berganda

= peramalan penjualan buah Jambu Biji Merah = konstanta/Intercept = koefisien regresi/Slope = waktu (bulan) = error. B. Ukuran akurasi peramalan Secara sederhana, ukuran akurasi peramalan dapat diketahui dengan memiliki nilai R2 terbesar dan nilai Se (Standart error) terendah. Semakin besar Se, ini berarti prediksi yang akan dilakukan semakin tidak akurat. 3. Hasil dan Pembahasan 3.1 Identifikasi Model Fungsi Penjualan Buah Jambu Biji Merah. Penelitian ini menggunakan dua model fungsi penjualan yaitu fungsi penjualan yang ditransformasikan ke dalam bentuk Log dan fungsi penjualan linier berganda. Adapun hasil pengujian menggunakan kriteria statistik dapat dilihat pada Tabel 2

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Uji t B
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Fungsi peramalan
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