Peramalan Penentuan Jumlah Permintaan Konsumen Berbasis Teknologi Informasi Terhadap Produk Bordir Pada Kota Tasikmalaya

Abstract

Forecasting the determination of the consumer demand number of information technology for products of embroidery on the city of Tasikmalaya, has a special purpose to determine the amount of consumer demand needs periodically, periodic and pattern of consumer demand needs in the future as the trend, seasonal. This study started from the concept of thinking how to make embroidery manufacturers in Tasikmalaya obtain optimal revenue and efficiency in the production cost of their embroidery.Forecasting approach in this study was Time Series by using the Single Exponential Smoothing model to get forecasting value periodically, Double Exponential Smoothing model to get the forecasting value in trend and Triple Exponential SmoothingModel with Multiplicative seasonal mode to get forecasting value seasonal, as well as testing forecasting by using MAD, MAPE and MSE to search for the smallest error. In the next stage, it is built a forecasting system of determining consumer demand by using the method of waterfall development system and the making of softwarewhich is designed by using the Java programming language with the NetBeans editor and MySQL database.

Spatial Insights Into Earthquake Strength: A Sulawesi Case Study Using Ordinary and Robust Kriging Methods

“…Evaluation of prediction accuracy serves to measure how well the prediction method performs in predicting data. A measure of the accuracy of prediction results is a measure used to compare prediction models and monitor predictive activity to ensure that the predicted activity operates properly and produces accurate values [32]. The following are several types of measurements of the accuracy of prediction methods…”

Sistem Informasi Manajemen Inventori Obat dan Bahan Medis Habis Pakai di UPT Puskesmas Ibrahin Adjie Kota Bandung

“…Dalam pengambilan keputusan manajemen dalam suatu organisasi, peramalan (forecasting) menjadi salah satu solusi yang akan mempengaruhi kemajuan suatu organisasi. Peramalan dapat memprediksi ketidakpastian suatu peristiwa di masa mendatang berdasarkan penggunaan data sebelumnya maupun data saat ini [7] [8]. Dengan kata lain peramalan dapat memperkirakan data runtut waktu (time series) untuk periode mendatang dengan menggunakan data di masa lalu maupun data di masa ini.…”

“…Metode ini memberikan nilai bobot berdasarkan konstanta (α) sebagai nilai dari perameter pemulusan (smoothing). Nilai bobot dapat berubah secara eksponensial berdasarkan data masa lalu [7] [8]. Single exponential smoothing dihitung dengan persamaan [8][5]:…”

Peramalan Produksi Pempek Dengan Metode Moving Average Dan Exponential Smoothing

“…Setelah dilakukan peramalan maka dilanjutkan dengan proses perhitungan persentase kesalahan dari hasil peramalan. Tiga ukuran yang paling terkenal adalah deviasi rata-rata yang absolut (mean absolute deviation- MAD), kesalahan rata-rata-rata yang dikuadratkan (mean squared error-MSE), dan kesalahan persentase ratarata yang absolut (mean absolute percent error-MAPE) [14]. Menurut Margie, Mean Absolute Percentage Error (MAPE) dihitung dengan menggunakan kesalahan absolut pada tiap periode dibagi dengan nilai observasi yang nyata untuk periode itu [15].…”