?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=ESTIMASI+PARAMETER+PADA+MODEL+REGRESI%0D%0ADENGAN+METODE+JACKKNIFE+RIDGE+REGRESSION+DALAM%0D%0AMENGATASI+MASALAH+MULTIKOLINEARITAS&rft.creator=ALVIN+YUANDA%2C++1417031007&rft.subject=QA+Mathematics&rft.description=Metode+Kuadrat+Terkecil+dan+Jackknife+Ridge+Regression+adalah+metode%0D%0Apendugaan+parameter+pada+model+regresi.+Jackknife+Ridge+Regression+mengatasi%0D%0Amasalah+multikolinieritas+dengan+menambahkan+konstanta+bias+K(+%2C+%2C+%E2%80%A6+%2C+)%0D%0Apada+diagonal+utama+matrixs+.+Tujuan+penelitian+ini+adalah+membandingkan%0D%0Anilai+dugaan+parameter+MKT+dengan+JRR+serta+untuk+mengetahui+keakuratan%0D%0Ametode+Jackknife+Ridge+Regression+dalam+mengatasi+masalah+multikolinieritas.%0D%0AMetode+yang+digunakan+dalam+penelitian+ini+adalah+simulasi+data%2C%0D%0Amengidentifikasi+multikolinearitas%2C+melakukan+standarisasi+data%2C+melakukan%0D%0Aanalisis+MKT+dan+JRR%2C+identifikasi+multikolinieritas%2C+menghitung+nilai+SE+dan%0D%0AAMSE.+Hasil+analisis+menunjukkan+bahwa+parameter+dan+model+yang+dihasilkan%0D%0Aoleh+JRR+lebih+stabil+dan+konsiten+serta+metode+JRR+dapat+mengatasi%0D%0Amultikolinearitas+lebih+baik+dari+pada+MKT.%0D%0AKata+Kunci%3A+multikolinearitas%2C+konstanta+bias+K%2C+Metode+Kuadrat+Terkecil%2C%0D%0AJackknife+Ridge+Regression%0D%0A%0D%0Aabstract%0D%0A%0D%0AThe+Ordinary+Least+Square+Method+and+Jackknife+Ridge+Regression+is+a+parameter%0D%0Aestimation+method+in+the+regression+model.+Jackknife+Ridge+Regression+overcomes%0D%0Athe+problem+of+multicollinearity+by+adding+the+bias+constant+K(+%2C+%2C+%E2%80%A6+%2C+)+on%0D%0Athe+main+diagonal+of+matrixs+.+The+purpose+of+this+study+is+to+compare+the%0D%0AOLS+with+JRR+and+to+know+the+accuracy+of+Jackknife+Ridge+Regression+method+in%0D%0Aovercoming+multicollinearity+problem.+In+this+research%2C+simulated+data+are+used+and%0D%0Aestimate+the+regression+coefficient+using+OLS+and+JRR.+AMSE+value+are+used+to%0D%0Asee+the+performance+of+both+methods.+The+results+show+that+the+parameters+and%0D%0Amodels+produced+by+JRR+are+more+stable+and+consistent+in+estimatis+coefficient%0D%0Aregression+when+multicolinearity+exist+than+OLS.%0D%0AKeyword%3A+multicolinearity%2C+bias+constant+K%2C+Least+Square+Method%2C+Jackknife%0D%0ARidge+Regression&rft.publisher=FAKULTAS+MATEMATIKA+DAN+ILMU+PENGETAHUAN+ALAM&rft.date=2018-06-04&rft.type=Skripsi&rft.type=NonPeerReviewed&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F31870%2F1%2FABSTRAK.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F31870%2F2%2FSKRIPSI%2520FULL.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F31870%2F3%2FSKRIPSI%2520TANPA%2520BAB%2520PEMBAHASAN.pdf&rft.identifier=++ALVIN+YUANDA%2C+1417031007++(2018)+ESTIMASI+PARAMETER+PADA+MODEL+REGRESI+DENGAN+METODE+JACKKNIFE+RIDGE+REGRESSION+DALAM+MENGATASI+MASALAH+MULTIKOLINEARITAS.++FAKULTAS+MATEMATIKA+DAN+ILMU+PENGETAHUAN+ALAM%2C++UNIVERSITAS+LAMPUNG.+++++&rft.relation=http%3A%2F%2Fdigilib.unila.ac.id%2F31870%2F