ANALISIS SENTIMEN TINGKAT KEPUASAN PELANGGAN TERHADAP LAYANAN KURIR J&T EXPRESS MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (SVM) BERDASARKAN ULASAN PENGGUNA DI GOOGLE PLAYSTORE

Suzuki Syofian Norman; Saddam Mahendra

Suzuki Syofian Norman Universitas Darma Persada
Saddam Mahendra Program Studi Teknologi Informasi Universitas Darma Persada https://orcid.org/0000-0002-4064-0235

Keywords: analisys sentimen, crisp-dm, support vector machine, j&t express, google play store.

Abstract

Courier Service Is One Of The Services That Are Widely Used By The Public, Especially In The Current Digital Era. In This Context, Courier Services Allow Shippers To Deliver Goods Or Documents Without The Need To Be Present Directly To The Destination Location. J & T Express, As One Of The Shipping Expedition Service Providers In Indonesia, Is The First Choice For Many People. Although Technology Continues To Evolve And Competition Is Increasingly Fierce, The Quality Of Courier Services Is A Key Factor That Customers Need To Pay Attention To. However, It Should Be Noted That The J&T Express Application In The Google Play Store Received A Low Rating, And This Is The Background Of This Study. the main focus of this study was to identify the level of customer satisfaction with j&t express courier services through reviews available on the google play store. within the framework of this study, sentiment analysis was conducted using the support vector machine algorithm, by applying crisp-dm methodology. the results showed that from the business understanding stage to the modeling stage, the performance of the support vector machine can be considered good. in addition, this study also resulted in an implementation that can be accessed through a website with the address jnt-sentiment.streamlit.app. hopefully, this research can contribute to j & t express in understanding the views of customers and improving the quality of their services

References

Aziz, A. (2022). Analisis Sentimen Identifikasi Opini Terhadap Produk, Layanan dan Kebijakan Perusahaan Menggunakan Algoritma TF-IDF dan SentiStrength. Dalam Jurnal Sains Komputer & Informatika (J-SAKTI (Vol. 6, Nomor 1).

Deta Base – Space Docs (2023), Diakses pada 19 Juni 2023, dari https://deta.space/docs/en/build/reference/deta-base

Getting Started – Visual Studio Code Docs (2023), diakses pada 19 juni 2023, dari https://code.visualstudio.com/docs

Gifari, O. I., Adha, M., Rifky Hendrawan, I., Freddy, F., & Durrand, S. (2022). Analisis Sentimen Review Film Menggunakan TF-IDF dan Support Vector Machine. Jifotech (Journal Of Information Technology, 2(1).

Hasna, S. K. (2021). Analisis Sentimen Data Ulasan Menggunakan Algoritma Support Vector Machine. Tugas Akhir, Universitas Islam Indonesia

Kurniawan, D., & Yasir, D. M. (2022). Optimization Sentiment Analysis Using Crisp-Dm And Naïve Bayes Methods Implemented On Social Media. 6, 74–84.

Locarso, G. K. (2022). Analisis Sentimen Review Aplikasi Pedulilindungi Pada Google Play Store Menggunakan Nbc. Jurnal Teknik Informatika Kaputama (JTIK), 6(2).

Pasek, P., Mahawardana, O., Sasmita, G. A., Agus, P., & Pratama, E. (2022). Analisis Sentimen Berdasarkan Opini dari Media Sosial Twitter terhadap “Figure Pemimpin” Menggunakan Python. Dalam JITTER-Jurnal Ilmiah Teknologi dan Komputer (Vol. 3, Nomor 1).

Pratama, A. E., Ariesta, A., & Gata, G. (2022). Analisis Sentimen Masyarakat terhadap Tim Nasional Indonesia pada Piala AFF 2020 Menggunakan Algoritma K-Nearest Neighbors The researcher uses the Cross-Industry Standard Process for Data Mining (CRISP-DM) method and implements the K-Nearest. Jurnal TICOM: Technology of Information and Communication, 10(3), 187–196.

Ramadhani, S. H., & Wahyudin, M. I. (2022). Analisis Sentimen Terhadap Vaksinasi Astra Zeneca pada Twitter Menggunakan Metode Naïve Bayes dan K-NN. Jurnal Teknologi Informasi dan Komunikasi), 6(4), 2022.

Suryati, E., Ari Aldino, A., Penulis Korespondensi, N., & Suryati Submitted, E. (2023). Analisis Sentimen Transportasi Online Menggunakan Ekstraksi Fitur Model Word2vec Text Embedding Dan Algoritma Support Vector Machine (SVM). 4(1), 96–106.

Streamlit Documentation – Streamlit Docs (2023), Diakses pada 19 Juni 2023, dari https://docs.streamlit.io/

ANALISIS SENTIMEN TINGKAT KEPUASAN PELANGGAN TERHADAP LAYANAN KURIR J&T EXPRESS MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (SVM) BERDASARKAN ULASAN PENGGUNA DI GOOGLE PLAYSTORE