FUNGSI-FUNGSI KERNEL PADA METODE REGRESI NONPARAMETRIK DAN APLIKASINYA PADA PRIEST RIVER EXPERIMENTAL FORESTS DATA

Siana Halim; Indriati Bisono

doi:10.9744/jti.8.1.pp. 73-81

Editor in Chief

Dr. Siana Halim, S.Si., M.Sc.nat.
Statistical Modeling & Industrial Mathematics, Industrial Engineering Department, Petra Christian University, Indonesia

Editors

I Gede Agus Widyadana, S.T., M.Eng.
Simulation, Scheduling, Production Planning and Control, Operational Research, Ergonomics, & Production System; Industrial Engineering Department, Petra Christian University, Indonesia

Iwan Halim Sahputra, S.T., M.Sc.
Product Design and Development, Information System, & Modeling; Industrial Engineering Department, Petra Christian University, Indonesia

Drs. Jani Rahardjo, MBA.tech.
Decision Science, Statistics, & Experiment Design; Industrial Engineering Department, Petra Christian University, Indonesia

Dra. Indriati Bisono, M.Sc.
Experiment Design, Quality Management, & Quality Engineering; Industrial Engineering Department, Petra Christian University, Indonesia

Reviewers

Prof. Hui Ming Wee
(Production/Inventory Control, Optimization, Supply Chain Management) Department of Industrial and System Engineering, Chung Yuan Christian University Chung Li 320, Taiwan

Darsono Tjokroamidjojo, Ph.D.
(Operations Research, Supply Chain Management). Assistant professor of North Dakota State University, USA.

Dr. Liem Ferryanto
(Complex Design of Experiments, Design for Six Sigma) Director of Six Sigma, Global Research, Development and Engineering. CIBA Vision, A Novartis Company, Atlanta Georgia, USA

Huynh Trung Luong, D.Eng.
(Industrial Systems Engineering) Industrial Systems Engineering, Asian Institute of Technology, Thailand.

Erwie Zahara, Ph.D.
(Heuristic optimization, data mining,marketing research) Department of Industrial Engineering and Management of St. John's University, Taiwan

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ejournal

FUNGSI-FUNGSI KERNEL PADA METODE REGRESI NONPARAMETRIK DAN APLIKASINYA PADA PRIEST RIVER EXPERIMENTAL FORESTS DATA

Siana Halim, Indriati Bisono

Abstract

In this paper we discuss some models for estimating the regression function, provided the data Y is given. The programming of these function are presented as well as the "tricks" in the R- programming, a statistical freeware. We applied these models to The Priest River Experimental Forest's data.

Abstract in Bahasa Indonesia :

Dalam paper ini akan diberikan beberapa model untuk mengestimasi fungsi regresi bila sebuah data Y diberikan. Pembuatan fungsi - fungsi estimasti tersebut juga diberikan dengan menggunakan freeware statistik R dan juga diberikan beberapa trik dalam pemrograman. Model-model ini diaplikasikan pada Priest River Experimental Forest's data.

Kata kunci: regresi nonparametrik, smoothing, kernel, R.

Keywords

nonparametric regression, smoothing, kernel, R.

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