ANALISIS INTANGIBLE FACTORS YANG MEMPENGARUHI PENENTUAN HARGA PRODUK KARYA SENI
Kusriniarti Dwi Lestariningsih(1*)
(1) Fakultas Teknik Universitas Gadjah Mada
(*) Corresponding Author
Abstract
This research aims to develop a new quantitative method to determine painting pricing based on 10 intangible factors, i.e. curator, amount of exhibition, painter’s year of birth, painting’s years of made, auction record,
estimation price, exhibition place, painting media, painting size, and previous sales record. The selling price data are obtained from six auction houses. Kano Model and Linear Regression Model are used to examine the relation
between pricing and each variable. Based on the model development scheme, there are 6 alternative models that can be obtained. Each model then was evaluated by cross-validation procedure using 21 data. Based on the value of R2for each model, the Kano Model with variable previous sales is the best model with R2 of 70%
estimation price, exhibition place, painting media, painting size, and previous sales record. The selling price data are obtained from six auction houses. Kano Model and Linear Regression Model are used to examine the relation
between pricing and each variable. Based on the model development scheme, there are 6 alternative models that can be obtained. Each model then was evaluated by cross-validation procedure using 21 data. Based on the value of R2for each model, the Kano Model with variable previous sales is the best model with R2 of 70%
Keywords
price, intangible factors, Kano Model, Linear Regression
Full Text:
PDFDOI: https://doi.org/10.22146/teknosains.5990
Article Metrics
Abstract views : 1940 | views : 2569Refbacks
- There are currently no refbacks.
Copyright (c) 2014 Kusriniarti Dwi Lestariningsih
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Copyright © 2024 Jurnal Teknosains Submit an Article Tracking Your Submission
Editorial Policies Publishing System Copyright Notice Site Map Journal History Visitor Statistics Abstracting & Indexing