ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI INDEK MUTU BENANG MENGGUNAKAN METODE POHON REGRESI (Studi Kasus di PT. Industri Sandang Nusantara Unit Patal Grati)

*Hesti Sari Dewi - 
Yuciana Wilandari - 
Sudarno Sudarno - 
Published: 17 Dec 2012.
Open Access
Citation Format:
Article Info
Section: Articles
Language: EN
Full Text:
Statistics: 288 2033
Abstract

Quality for ripe material (yarn) really necessary for the company, therefore needs to control the product (ripe material), so we are able to know the unmatched product percentage of the company standard and to know the cause of the unmatched. The appropriate method to know the influential factor to company yarn quality successes, among those regression tree method. Regression tree is one of CART’s classification method. CART is a useful non parametric statistical method to get an accurate data group as distinguishing as of a classification. Because it has continuous type of response variable, so that CART can create regression tree. Regression tree is utilized to figure relationship among one response variable with one or more predictor variable that gets continued character and also category. The variables that have influence for yarn quality index at PT. Industri Sandang Nusantara Patal Grati’s Unit are raw material, machine output year, air humidity (RH) and hall temperature. The result of the research is that the year of machine output variable is the most influence to foot up yarn quality index and has main contribution in the formation of regression tree.

 

Keywords : Regression tree, CART, Yarn quality index, Rayon.

Article Metrics: