Implementasi Deep Learning untuk Entity Matching pada Dataset Obat (Studi Kasus K24 dan Farmaku)

Authors

  • Rivanda Putra Pratama Departemen Sistem Informasi, Institut Teknologi Sepuluh Nopember
  • Rahmat Hidayat Departemen Sistem Informasi, Institut Teknologi Sepuluh Nopember
  • Nisrina Fadhilah Fano Departemen Sistem Informasi, Institut Teknologi Sepuluh Nopember
  • Adam Akbar Departemen Sistem Informasi, Institut Teknologi Sepuluh Nopember
  • Nur Aini Rakhmawati Departemen Sistem Informasi, Institut Teknologi Sepuluh Nopember

DOI:

https://doi.org/10.14421/jiska.2021.6.3.130-138

Keywords:

Entity Matching, Deep Learning, DeepMatcher, Dataset, Hybrid

Abstract

Data processing speed in companies is important to speed up their analysis. Entity matching is a computational process that companies can perform in data processing. In conducting data processing, entity matching plays a role in determining two different data but referring to the same entity. Entity matching problems arise when the dataset used in the comparison is large. The deep learning concept is one of the solutions in dealing with entity matching problems. DeepMatcher is a python package based on a deep learning model architecture that can solve entity matching problems. The purpose of this study was to determine the matching between the two datasets with the application of DeepMatcher in entity matching using drug data from farmaku.com and k24klik.com. The comparison model used is the Hybrid model. Based on the test results, the Hybrid model produces accurate numbers, so that the entity matching used in this study runs well. The best accuracy value of the 10th training with an F1 value of 30.30, a precision value of 17.86, and a recall value of 100.

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Published

2021-09-22

How to Cite

Pratama, R. P., Hidayat, R., Fano, N. F., Akbar, A., & Rakhmawati, N. A. (2021). Implementasi Deep Learning untuk Entity Matching pada Dataset Obat (Studi Kasus K24 dan Farmaku). JISKA (Jurnal Informatika Sunan Kalijaga), 6(3), 130–138. https://doi.org/10.14421/jiska.2021.6.3.130-138

Issue

Vol. 6 No. 3 (2021): September 2021

Section

Articles

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Copyright (c) 2021 Rivanda Putra Pratama, Rahmat Hidayat, Nisrina Fadhilah Fano, Adam Akbar, Nur Aini Rakhmawati

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