Autokorelasi Pada Pembentukan Grafik Kendali Komponen Utama - Rasyid, Nur Ahniyanti; Wijaya, Dhian Eka; Firmayasari, Dian; Harianto; Pratama, Muhammad Isbar (Jurusan Matematika FMIPA UNM, 2022)
The formation of control chart for autocorrelated data can not be done. This research aims to analyse the effect of autocorrelated data on the formation of principal component control chart. A case study was performed on simulated data with two variables and they were applied on the data of climate elements in Makassar city including air temperature, solar radiation, air humadity,and wind speed. The analysis of the effect of the autocorrelated data was conducted inthree steps, namely: (1) the establishment of the structure of variance-covariance matrix of the autocorrelated data; (2) the establishment of principal component control chart based on the largest eigen valu; and (3) In forming of simulation with two variables. The result indicate that if the data are negatively autocorrelated with avalue of -0,9-(-0,5), the controllimits will be widened, and if the value is -0,5-(-0,1), the control limits will be narrowed.