Analisis Sentimen Sunscreen Azarine dengan Naïve Bayes di Toko Aneka Kosmetik Kupang pada Marketplace Shopee

Authors

  • Adriana Yohana Sain Ilmu Komputer, Fakultas Sains dan Teknik, Universitas Nusa Cendana
  • Sebastianus Adi Santoso Mola Ilmu Komputer, Fakultas Sains dan Teknik, Universitas Nusa Cendana
  • Arni Yusfin Huan Ilmu Komputer, Fakultas Sains dan Teknik, Universitas Nusa Cendana
  • Inggi Rosina Nomleni Ilmu Komputer, Fakultas Sains dan Teknik, Universitas Nusa Cendana

DOI:

https://doi.org/10.33020/saintekom.v15i1.783

Keywords:

sentiment analysis, reviews, azarine sunscreen, naïve bayes classifier

Abstract

Advancements in information and communication technology have changed the way customers shop and share experiences through reviews. Marketplaces like Shopee allow customers to rate products through reviews, making sentiment analysis crucial for understanding consumer perceptions. The Naïve Bayes algorithm is used in this study to analyze 3,504 reviews of the Azarine sunscreen product from Aneka Kosmetik Kupang on Shopee, followed by a text preprocessing process. The dataset is then split into 80% for training and 20% for testing, with reviews categorized into three sentiment classes: positive, negative, and neutral. Evaluation with a Confusion Matrix resulted in an accuracy of 84%, demonstrating the reliability of this algorithm in analyzing customer reviews. The findings of this study offer fresh perspectives for brand owners and potential buyers regarding public perception of the Azarine sunscreen product at Aneka Kosmetik Kupang.

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References

Alfandi Safira, & Hasan, F. N. (2023). Analisis Sentimen Masyarakat Terhadap Paylater Menggunakan Metode Naive Bayes Classifier. ZONAsi: Jurnal Sistem Informasi, 5(1), 59–70. https://doi.org/10.31849/zn.v5i1.12856

Amory, J. D. S., Mudo, M., & J, R. (2025). Transformasi Ekonomi Digital dan Evolusi Pola Konsumsi: Tinjauan Literatur tentang Perubahan Perilaku Belanja di Era Internet. Jurnal Minfo Polgan, 14(1), 28–37. https://doi.org/10.33395/jmp.v14i1.14608

Aryanti, D. (2022). Analisis Sentimen Ibukota Negara Baru Menggunakan Metode Naïve Bayes Classifier. Journal of Information System Research (JOSH), 3(4), 524–531. https://doi.org/10.47065/josh.v3i4.1944

Ernawati, A., Sari, A. O., Sofyan, S. N., Iqbal, M., & Wijaya, R. F. W. (2023). Implementasi Algoritma Naïve Bayes dalam Menganalisis Sentimen Review Pengguna Tokopedia pada Produk Kesehatan. Bulletin of Information Technology (BIT), 4(4), 533–543. https://doi.org/10.47065/bit.v4i4.1090

Irwan Adhi Prasetya, Fadli Sukandiarsyah, Novi Aryani Fitri, & Safri Adam. (2024). Klasifikasi kualitas buah jeruk menggunakan computer vision dengan arsitektur YOLO V8. Jurnal Pendidikan Informatika dan Sains, 13(2), 187–201. https://doi.org/10.31571/saintek.v13i2.8346

Khairunnisa, S., Adiwijaya, A., & Faraby, S. A. (2021). Pengaruh Text Preprocessing terhadap Analisis Sentimen Komentar Masyarakat pada Media Sosial Twitter (Studi Kasus Pandemi COVID-19). JURNAL MEDIA INFORMATIKA BUDIDARMA, 5(2), 406. https://doi.org/10.30865/mib.v5i2.2835

Martantoh, E., & Yanih, N. (2022). Implementasi Metode Naïve Bayes Untuk Klasifikasi Karakteristik Kepribadiaan Siswa Di Sekolah MTS Darussa’adah Menggunakan Php Mysql. Jurnal Teknologi Sistem Informasi, 3(2), 166–175. https://doi.org/10.35957/jtsi.v3i2.2896

Merinda Lestandy, Abdurrahim Abdurrahim, & Lailis Syafa’ah. (2021). Analisis Sentimen Tweet Vaksin COVID-19 Menggunakan Recurrent Neural Network dan Naïve Bayes. Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 5(4), 802–808. https://doi.org/10.29207/resti.v5i4.3308

Nafiah, S., Fitraneti, E., Rizal, Y., Primawati, I., & Hamama, D. (2024). Pengaruh Paparan Sinar Ultraviolet terhadap Kesehatan Kulit dan Upaya Pencegahannya: Tinjauan Literatur.

Nafisyah, S., & Sulistiyowati, R. (2024). Analisis Sentimen Ulasan Produk Toko Online Esrocte untuk Peningkatan Pelayanan Menggunakan Algoritma Naïve Bayer. Blantika: Multidisciplinary Journal, 2(8). https://doi.org/10.57096/blantika.v2i8.189

Novitasari, D., Maulana, R., Hastuti, H., & Puspitasari, N. (2024). pengaruh Ulasan Dan Penilaian Produk Terhadap Keputusan Pembelian Di E-Commerce ShopeE.

Rizaldi, R., & Aryanti, R. (2024). Analisis Sentimen Pengguna Terhadap Aplikasi Indodana Di Google Play Store Menggunakan Metode Naive Bayes Classifier. 3(4).

Salsabila, S. M., Alim Murtopo, A., & Fadhilah, N. (2022). Analisis Sentimen Pelanggan Tokopedia Menggunakan Metode Naïve Bayes Classifier. Jurnal Minfo Polgan, 11(2), 30–35. https://doi.org/10.33395/jmp.v11i2.11640

Sari, D. N., Sari, D. N., Adelia, F., Rosdiana, F., Butar, B. B., & Hariyanto, M. (2020). Analisa Sentimen Terhadap Review Produk Kecantikan Menggunakan Metode Naive Bayes Classifier. JIKA (Jurnal Informatika), 4(3), 109. https://doi.org/10.31000/jika.v4i3.3086

Wp, D. A., Firizqi, J. D., & Amalia, Z. A. (2024). Analisis Sentimen Produk Skincare Somethinc Niacinamide di Female Daily dengan Naïve Bayes Classifier. JURNAL MEDIA INFORMATIKA BUDIDARMA, 8(2), 946. https://doi.org/10.30865/mib.v8i2.7571

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Published

31-03-2025

How to Cite

Sain, Adriana Yohana, Sebastianus Adi Santoso Mola, Arni Yusfin Huan, and Inggi Rosina Nomleni. 2025. “Analisis Sentimen Sunscreen Azarine Dengan Naïve Bayes Di Toko Aneka Kosmetik Kupang Pada Marketplace Shopee”. Jurnal Saintekom : Sains, Teknologi, Komputer Dan Manajemen 15 (1):94-105. https://doi.org/10.33020/saintekom.v15i1.783.

Issue

Vol. 15 No. 1 (2025): Maret 2025

Section

Articles

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Copyright (c) 2025 Adriana Yohana Sain, Sebastianus Adi Santoso Mola, Arni Yusfin Huan, Inggi Rosina Nomleni

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