Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/25507
Title: | Development of Customs Prediction Model for Online Ordering | Authors: | Sharawi, Lina I. QABBAAH, Hamzah SAMMOUR, George VANHOOF, Koen |
Issue Date: | 2018 | Publisher: | IEEE | Source: | Awajan, Arafat; Shaout, Adnan (Ed.). Proceedings: 2017 International Conference on New Trends in Computing Sciences (ICTCS), IEEE,p. 94-97 | Abstract: | As a result of the rapid increase of online shopping, and the movement of products in and out among various countries, governments made it mandatory to pay a certain fee referred to as customs to maintain each country’s economy, based on some rules i.e. weight and price. This paper proposes a model to anticipate and inform the customer if his order is going to be subject to customs or not based on some predefined rules. The model is built using a software called SPSS and data mining techniques such as; Decision Tree (DT) and logistic regression. A comparison between the two data mining techniques is made showing that the DT results were better than the logistic regression in terms of accuracy, precision, recall and f-score. | Notes: | Sharawi, LI (reprint author), PSUT, Software Engn Dept, Amman, Jordan. lin20148050@std.psut.edu.jo; Hamzah.qabbaah@uhasselt.be; George.sammour@psut.edu.jo; koen.vanhoof@uhasselt.be | Keywords: | data mining; customs; decision tree; logistic regression; classification measures | Document URI: | http://hdl.handle.net/1942/25507 | ISBN: | 9781538605271 | DOI: | 10.1109/ICTCS.2017.33 | ISI #: | 000425843800017 | Rights: | © 2017 IEEE | Category: | C1 | Type: | Proceedings Paper | Validations: | ecoom 2019 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
sharawi2017.pdf Restricted Access | Published version | 283.28 kB | Adobe PDF | View/Open Request a copy |
Page view(s)
76
checked on Sep 7, 2022
Download(s)
84
checked on Sep 7, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.