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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
Citation: 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
URI: http://hdl.handle.net/1942/25507
DOI: 10.1109/ICTCS.2017.33
ISI #: 000425843800017
ISBN: 9781538605271
Category: C1
Type: Proceedings Paper
Appears in Collections: Research publications

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