An Analysis Of Cash On Delivery (COD) Purchase Classification Using the C4.5 and ID3 Algorithms

Authors

  • Asrianda Asrianda Universitas Sumatera Utara Author
  • Herman Mawengkang Universitas Sumatera Utara Author
  • Poltak Sihombing Universitas Sumatera Utara Author
  • Mahyuddin K. M. Nasution Universitas Sumatera Utara Author

DOI:

https://doi.org/10.30743/gyne6v94

Keywords:

Normalization; C4.5 and ID3; Classification; COD

Abstract

This study investigates the prevalence of COD (Cash on Delivery) payment methods across different price categories of goods and the impact of normalization on classification accuracy using the C4.5 and ID3 algorithms. The data reveals that the majority of COD payments occur for items priced below 1,000 PKR, with a decreasing trend as the price increases. conversely, higher-priced items see more non-COD transactions. Monthly analysis shows the highest number of COD transactions in November. Among various product categories, Men's Fashion, Soghaat, and Beauty & Grooming dominate COD payments. The implementation of min-max normalization improves the accuracy of both C4.5 and ID3 algorithms, with C4.5 showing a notable improvement in precision and recall metrics.

References

. M. Halaweh, "Cash on delivery (COD) as an alternative payment method for e-commerce transactions: Analysis and implications," Int. J. Sociotechnology Knowl. Dev., vol. 10, no. 4, pp. 1–12, 2018, doi: 10.4018/IJSKD.2018100101.

. DI Hajati, "The Effect of Cash on Delivery, Online Consumer Ratings and Reviews on the Online Product Purchase Decisions," Bus. Innov. Entrep. J., vol. 4, no. 1, pp. 18–26, 2022, doi: 10.35899/biej.v4i1.348.

. B. Purwandari, SA Suriazdin, AN Hidayanto, S. Setiawan, K. Phusavat, and M. Maulida, “Factors Affecting Switching Intention from Cash on Delivery to E-Payment Services in C2C E-Commerce Transactions: COVID-19, Transaction, and Technology Perspectives," Emergency. Sci. J., vol. 6, no. Special Issue, pp. 136–150, 2022, doi: 10.28991/esj-2022-SPER-010.

. M. Alfarizi and RK Sari, "Adoption Of Cash on Delivery (COD) Payment System in Shopee Marketplace Transaction," Procedia Comput. Sci., vol. 227, pp. 110–118, 2023, doi: 10.1016/j.procs.2023.10.508.

. JR Quinlan, “Induction of decision trees,” Mach. Learn., vol. 1, no. 1, pp. 81–106, 1986, doi: 10.1007/bf00116251.

. HMS B, C. Lei, and D. Neagu, Computational Complexity Analysis of Decision Tree Algorithms. Springer International Publishing, 2018. doi: 10.1007/978-3-030-04191-5.

. JR Quinlan, “Improved use of continuous attributes in C4.5,” J. Artif. Intel. Res., vol. 4, no. 1996, pp. 77–90, 1996, doi: 10.1613/jair.279.

. S. STEVEN L., “Book Review : C4 . 5 : Programs for Machine Learning," Mach. Learn., vol. 240, pp. 235–240, 1994.

. HO Salami, RS Ibrahim, and MO Yahaya, "Detecting Anomalies in Students' Results Using Decision Trees,"Int. J. Mod. Educ. Comput. Sci., vol. 8, no. 7, pp. 31–40, 2016, doi: 10.5815/ijmecs.2016.07.04.

. S. Hamed and S. El-Deeb, “Cash on Delivery as a Determinant of E-Commerce Growth in Emerging Markets,” J. Glob. Mark., vol. 33, no. 4, pp. 242–265, 2020, doi: 10.1080/08911762.2020.1738002.

. NA Hamdani and GAF Maulani, "The influence of E-WOM on purchase intentions in the local culinary business sector," Int. J.Eng. Technol., vol. 7, no. 2, pp. 246–250, 2018, doi: 10.14419/ijet.v7i2.29.13325.

. TM Lakshmi, A. Martin, RM Begum, and VP Venkatesan, "An Analysis on Performance of Decision Tree Algorithms using Student's Qualitative Data," Int. J. Mod. Educ. Comput. Sci., vol. 5, no. 5, pp. 18–27, 2013, doi: 10.5815/ijmecs.2013.05.03.

. HA Prihanditya, “The Implementation of Z-Score Normalization and Boosting Techniques to Increase Accuracy of C4. 5 Algorithms in Diagnosing Chronic Kidney Disease," J. Soft Comput. Explore., vol. 5, no. 1, pp. 63–69, 2020, doi: https://doi.org/10.52465/joscex.v1i1.8.

. D. Rajeswari and K. Thangavel, “the Performance of Data Normalization Techniques on Heart Disease Datasets,” Int. J. Adv. Res. Eng. Technol., vol. 11, no. 12, pp. 2350–2357, 2020, doi: 10.34218/IJARET.11.12.2020.222.

. OpenDataPakistan, “No Title,” Pakistan Largest Ecommerce, 2021. https://opendata.com.pk/ dataset/pakistan-largest-ecommerce-dataset/resource/7395e1d0-c02b-4e1d-abb8-84ae52681ffb

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Published

2024-11-22

Issue

ICST UISU 2024

Section

Articles

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