Estimasi Jumlah Work Order Project Konstruksi Menggunakan Metode ARIMA (Autoregressive Integrated Moving Average)
Journal: Jurnal Informatika Universitas Pamulang (Vol.4, No. 3)Publication Date: 2019-09-30
Authors : Hanik Azharul Hidayah Richa Fadlilatul Mu'affifah Umi Chotijah;
Page : 79-86
Keywords : ARIMA; Forecasting; Minitab; Work Order; Make to Order;
Abstract
A project consists of various types or work. Between one type of work with another type of work has a very close relationship. The types of work will show the scale or failure of a project. The more types of work to be done, the greater the scale of the project, and vice versa. The relationship between the type of work one with the other type of work on a large-scale project will be very complex, the smaller the scale, the relationship between types of work will be more simple. One of the construction companies in Gresik, namely CV. ANEKA JASA TEKNIK, applies the make to order strategy to respond to requests from consumers. That way, the company can send orders with quality and delivery time in accordance with the wishes of consumers. In this project the problem faced is how to forecast project work orders in the coming month. The data used in this study is work order data from January 2016 to April 2019. Data analysis uses the Autoregressive Integrated Moving Average (ARIMA) method. The tools used in this study are Minitab. The analysis obtained from calculations using the ARIMA model (1,1,1) and forecasting results until the month of October. The analysis results obtained from calculations using the ARIMA model (1,1,1) and forecasting results until October. Work order construction project is Zt = μ - 0,9647Zt-1 + at, Forecasting work order construction projects for the coming month, starting from January 2016 to April 2019 experiencing a gradual decline, comparison between work order forecast project construction not much different from the work order of the actual construction project.Output in the form of data prediction the number of work orders is displayed in the form of tables and graphs so that it is easy to understand.
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Last modified: 2019-10-11 20:52:40