Peluang penggunaan pupuk organik akan semakin besar dengan sadarnya para petani pengaruh buruk kimia pada tanah yang bisa membuat menjadi tidak subur. Tetapi untuk jumlah permintaan fluktuatif PT. Petrokopindo Cipta Selaras (PCS) harus perencanaan produksi terencana sehingga menjual sesuai Petrokimia Gresik (PG) selaku penyalur organik. Penelitian ini dilakukan pabrik berada di Kabupaten Sidoar...

Multi-Task Learning (MTL) is a growing subject of interest in deep learning, due to its ability train models more efficiently on multiple tasks compared using group conventional single-task models. However, MTL can be impractical as certain dominate training and hurt performance others, thus making some perform better model multi-task one. Such problems are broadly classified negative transfer,...

Semantic Differencing for Numerical Programs Nimrod Partush and Eran Yahav

The purpose of this study is to compare the 3 forecasting methods Linear Regression, Exponential Smoothing and Weighted Moving Average based on smallest error value or close zero. From results study, Regression method was obtained as correct with a predicted 502 students, MAD 27.83, MSE 1152.1 MAPE 8.1%. Tracking Signal moves between 1 -1, movement within control limits tracking signal standard...

This article investigates a Cautious Minimum Variance (CMV) control approach for controlling industrial process variability when the model parameters are estimated from data and subject to uncertainty. CMV control has a number of advantages over traditional robust control methods. It incorporates probabilistic, as opposed to deterministic, measures of parameter uncertainty, which are more consi...

Nonstationary ARIMA processes and nearly nonstationary ARMA processes, such as autoregressive processes having a root of the AR polynomial close to the unit circle, have sample autocovariance and spectral properties that are, in practice, almost indistinguishable from those of a stationary longmemory process, such as a Fractionally Integrated ARMA (ARFIMA) process. Because of this, model misspe...

In this paper we examine the ̄nite-sample properties of the approximate maximum likelihood estimate (MLE) of the fractional di®erencing parameter d in an ARFIMA(p, d, q) model based on the wavelet coe±cients. Ignoring wavelet coe±cients of higher order of resolution, the remaining wavelet coe±cients approximate a sample of independently and identically distributed normal variates with homogeneo...

This paper provides a Bayesian analysis of Autoregressive Fractionally Integrated Moving Average (ARFIMA) models. We discuss in detail inference on impulse responses, and show how Bayesian methods can be used to (i) test ARFIMA models against ARIMA alternatives, and (ii) take model uncertainty into account when making inferences on quantities of interest. Our methods are then used to investigat...