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All Journal Jurnal Presipitasi : Media Komunikasi dan Pengembangan Teknik Lingkungan Jurnal Gaussian JURNAL TEKNIK SIPIL UNAYA
Sudarno Sudarno
Universitas Diponegoro
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Earth & Planetary Sciences Materials Science & Nanotechnology Other

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Journal : Jurnal Gaussian

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PEMODELAN UPAH MINIMUM KABUPATEN/KOTA DI JAWA TENGAH BERDASARKAN FAKTOR-FAKTOR YANG MEMPENGARUHINYA MENGGUNAKAN REGRESI RIDGE Hildawati Hildawati; Agus Rusgiyono; Sudarno Sudarno
Jurnal Gaussian Vol 5, No 1 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (543.998 KB) | DOI: 10.14710/j.gauss.v5i1.11035

Abstract

The least squares method is a regression parameter estimation method for simple linear regression and multiple linear regression. This method produces no bias and variance estimator minimum if no multicollinearity. But if it happens, it will generate a large variance and covariance. One way to overcome this problem is by using ridge regression. Ridge regression is a modification of the least squares by adding a bias constant  on the main diagonal Z'Z. So that estimation parameter  with . This method produces bias and variance estimator minimum. Results of the modeling discussion of minimum wage in the city of Semarang, Surakarta, Tegal and Banyumas as well as the factors that influence it, such as inflation, Gross Domestic Regional Product (DGRP) and the Desent Living Needs contained multicollinearity problem. The minimum wage is significantly influenced Semarang Desent Living Needs, while Surakarta and Banyumas significantly affected GDRP and Desent Living Needs. Keywords: multicollinearity, ridge regression, bias constants , the minimum wage
PERAMALAN DINAMIS PRODUKSI PADI DI JAWA TENGAH MENGGUNAKAN METODE KOYCK DAN ALMON Firdha Rahmatika Pratami; Sudarno Sudarno; Dwi Ispriyanti
Jurnal Gaussian Vol 5, No 1 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (558.564 KB) | DOI: 10.14710/j.gauss.v5i1.11032

Abstract

Paddy is one of the staple crops that have strategic value and has a great influence in economic, environmental, social and political. Almost of Indonesia's population consumes rice every day. Because of that, need models to determine or predict the amount of paddy production in Central Java for the future. Because the data used is the historical data, there will be a regression analysis that takes into account the time. If the regression model include not only the value of the independent variable X at this time, but also the value of the past (lagged), this model  called a distributed-lag model. The methods used in determining the equation of distributed-lag are Koyck and Almon method. Koyck method used to determine the estimated dynamic model of distributed-lag time difference (lag) is unknown. Almon method used to determine the estimated dynamic model of distributed-lag time difference (lag) is known. Selection of the best model is using Mean Absolut Percentage Error criteria. According the result of the analysis, using Almon model has better result than Koyck Model.Keyword: Paddy, Distributed-lag model, Koyck, Almon
Co-Authors Adranandini Noor Anisa Agus Rusgiyono Ajeng Arum Sari Amin Chegenizadeh Attaya Juliatiko Bagus Hario Setiadji Budi Prasetyo Samadikun Danar Aji Prasetyo Dwi Ispriyanti Fathan Syahreza Pratama Firdha Rahmatika Pratami Hildawati Hildawati Ika Bagus Priyambada Indah Sekar Arumdani Irawan Wisnu Wardhana Junaidi Junaidi Mochamad Arief Budihardjo Mochtar Hadiwidodo Muryanto Muryanto Nahyo Nahyo Ngakan Ade Rahmadiputra Nurandani Hardyanti Purwono Purwono Rahayu Puji Safitri Sri Sumiyati Sunu Pertiwi Syafrudin Syafrudin Tika Ayu Kusuma Wardani Yustina Metanoia Pusparizkita