Pengelompokan Ulasan Aplikasi PeduliLindungi dengan Algoritma K-Medoids

  • Ahmad Habib Husaini University of Singaperbangsa Karawang
  • Rini Mayasari Universitas Singaperbangsa Karawang
  • Susilawati Susilawati Universitas Singaperbangsa Karawang

Abstract

By looking at the reviews of potential users, you can see the responses of other users who have used the application first, besides the application reviews can be used as input for developers. Clustering reviews can use text mining. In this study, the Kmedoids algorithm was used to cluster reviews with Fasttext  word embedding to represent the review's word units into vectors. The data used in this study amounted to 2,729 taken from the PeduliLindung application comment column on the Google Playstore. The results of the evaluation using the Davies Bouldin index or abbreviated as DBI by comparing sixteen trials and the best experiment was obtained, namely, an experiment using data without stemming, cbow architecture, using the Manhattan distance metric, and an experiment using data without stemming, cbow architecture, and using the cityblock distance metric with the same DBI value of 2.93 which resulted in two clusters of reviews. In the first cluster there were 2,183 reviews while in the second cluster there were 546 reviews.

References

Chollisni, A., Syahrani, S., Dewi, S., Utama, A. S., & Anas, M. (2022). The concept of creative economy development-strengthening post covid-19 pandemic in Indonesia: Strategy and public policy management study. Linguistics and Culture Review, 6, 413-426.
Farhadloo, M., & Rolland, E. (2016). Fundamentals of sentiment analysis and its applications. Studies in Computational Intelligence, 639(August 2018), 1–24. https://doi.org/10.1007/978-3-319-30319-2_1
Gata, W. (2016). Akurasi Text Mining Menggunakan Algoritma K-Nearest Neighbour pada Data Content Berita SMS.
Haerani, E., & Rahmatulloh, A. (2021). Analisis User Experience Aplikasi Peduli Lindungi untuk Menunjang Proses Bisnis Berkelanjutan. SATIN-Sains dan Teknologi Informasi, 7(2), 01-10.
Herdiana, D. (2021). Aplikasi peduli lindungi: perlindungan masyarakat dalam mengakses fasilitas publik di masa pemberlakuan kebijakan ppkm. Jurnal Inovasi Penelitian, 2(6), 1685-1694.
Hertina, H., Nurwahid, M., Haswir, H., Sayuti, H., Darwis, A., Rahman, M., ... & Hamzah, M. L. (2021). Data mining applied about polygamy using sentiment analysis on Twitters in Indonesian perception. Bulletin of Electrical Engineering and Informatics, 10(4), 2231-2236.
Imberman, S. P. (2001). Effective Use Of The Kdd Process And Data Mining For Computer Performance Professionals. Effective Use Of The Kdd Process And Data Mining For Computer Performance Professionals. https://www.researchgate.net/publication/221445402
Karsito, & Sari, W. M. (2018). Prediksi Potensi Penjualan Produk Delifrance Dengan Metode Naive Bayes Di Pt. Pangan Lestari. SIGMA –Jurnal Teknologi Pelita Bangsa, 67–78.
Ndwandwe, D., & Wiysonge, C. S. (2021). COVID-19 vaccines. Current opinion in immunology, 71, 111-116.
Nurdin, A., Anggo, B., Aji, S., Bustamin, A., & Abidin, Z. (2020). Perbandingan Kinerja Word Embedding Word2vec, Glove, Dan Fasttext Pada Klasifikasi Teks. Jurnal TEKNOKOMPAK, 14(2), 74.
Roziqin, A., Mas’udi, S. Y., & Sihidi, I. T. (2021). An analysis of Indonesian government policies against COVID-19. Public Administration and Policy, 24(1), 92-107.
Sabrina, A., Siregar, I., & Sosrohadi, S. (2021). Lingual Dominance and Symbolic Power in the Discourse of Using the PeduliLindungi Application as a Digital Payment Tool. International Journal of Linguistics Studies, 1(2), 52-59.
Yudiarta, N. G., Sudarma, M., & Ariastina, W. G. (2018). Penerapan Metode Clustering Text Mining Untuk Pengelompokan Berita Pada Unstructured Textual Data. Majalah Ilmiah Teknologi Elektro, 17(3), 339. https://doi.org/10.24843/mite.2018.v17i03.p06
Published
2022-12-12
How to Cite
Husaini, A., Mayasari, R., & Susilawati, S. (2022). Pengelompokan Ulasan Aplikasi PeduliLindungi dengan Algoritma K-Medoids. INTECOMS: Journal of Information Technology and Computer Science, 5(2), 131-139. https://doi.org/https://doi.org/10.31539/intecoms.v5i2.4410
Abstract viewed = 0 times
PDF downloaded = 0 times