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Taksiran Parameter Multinomial Logit Dengan Menggunakan Generalized Method Of Moment Nur Fathanah; Erna Tri Herdiani; Georgina Maria Tinungki
Jurnal MSA ( Matematika dan Statistika serta Aplikasinya) Vol 8 No 1 (2020): Volume 8 Nomor 1
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v8i1.12247

Abstract

Regresi logistik multinomial merupakan perluasan dari regresi logistik biner yang memungkinkan lebih dari dua kategori variabel dependen. Pada paper ini akan membahas penaksiran parameter regresi logistik multinomial melalui Generalized Method of Moment  (GMM). Generalized Method of Moment (GMM) merupakan salah satu metode yang dapat mengatasi pelanggaran asumsi pada data seperti autokorelasi dan heteroskedastisitas
Peramalan Jumlah Penumpang Kapal Laut Menggunakan Metode Fuzzy Runtun Waktu Chen Orde Tinggi Rizki Adiputra; Erna Tri Herdiani; Sitti Sahriman
ESTIMASI: Journal of Statistics and Its Application Vol. 2, No. 1, Januari, 2021 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v2i1.10328

Abstract

The port has become an important part of people's lives. On certain days there is an increase in the number of ship passengers which can slow down operational activities from the port, thus causing a buildup of passengers at the port. therefore, the port must be prepared to deal with the buildup of passengers at the port. Based on this, the researchers made a prediction or forecasting the number of ship passengers at Makassar Soekarno Hatta Port in the coming period to find out how much the estimated number of passengers at Makassar Soekarno Hatta Port. The results of these studies can be input to the PT. Pelabuhan Indonesia IV (Persero ) Makassar if there will be a surge in passengers in the future period. researchers used the fuzzy method of high order chen time series in forecasting or prediction in this study . The researcher divides the data onto training and testing data . The results of the study using fuzzy time series with the best high order chen are that the second order produces MAPE error size of 0,143 , MSE 13470993,9 and MAE of 9478,52 . The result of prediction of testing data onto one period in the future is 52.608.