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All Journal E-Bisnis : Jurnal Ilmiah Ekonomi dan Bisnis Jurnal Informatika Jurnal Teknologi Informasi dan Ilmu Komputer Indonesian Journal on Software Engineering (IJSE) Jurnal Khatulistiwa Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA Techno Nusa Mandiri : Journal of Computing and Information Technology EVOLUSI : Jurnal Sains dan Manajemen Jurnal Mantik JAMI: Jurnal Ahli Muda Indonesia Jurnal Sistem Informasi Akuntansi Simpatik: Jurnal sistem Informasi dan Informatika Conten : Computer and Network Technology Jurnal Informatika Dan Tekonologi Komputer (JITEK) SENTRI: Jurnal Riset Ilmiah Jurnal Informatika Dan Tekonologi Komputer Jurnal Abdimas BSI: Jurnal Pengabdian Kepada Masyarakat Jurnal Elektronika dan Telekomunikasi
Mawadatul Maulidah
Universitas Bina Sarana Informatika
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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ANALISIS SENTIMEN MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR PADA REVIEW APLIKASI SHOPEE Fanny Fatma Wati; Nadiyah Hidayati; Mawadatul Maulidah; Andrian Eko Widodo; Rachmawati Darma Astuti
CONTEN : Computer and Network Technology Vol. 5 No. 2 (2025): Desember 2025
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/conten.v5i2.10116

Abstract

E-commerce merupakan media yang memfasilitasi transaksi komersial antara individu dengan individu maupun antara individu dan organisasi melalui sistem daring. Salah satu bentuk implementasi e-commerce adalah aplikasi Shopee. Shopee dikembangkan sebagai aplikasi berbasis perangkat mobile yang memungkinkan pengguna melakukan aktivitas belanja secara online dengan mudah, sehingga transaksi dapat dilaksanakan dimanapun dan kapanpun. Aplikasi tersebut tentunya mempunyai kekurangan dan kelebihan yang dirasa oleh masyarakat. Dari adanya kekurangan dan kelebihan aplikasi shopee tidak sedikit masyarakat yang memberikan ulasan negatif maupun positif terhadap aplikasi tersebut. Pemanfaatan data dalam jumlah besar dapat dilakukan melalui penerapan teknik Data Mining. Penelitian ini bertujuan untuk menganalisis berbagai masalah yang dituju terhadap pengguna terhadap aplikasi Shopee di Google Play Store serta mengukur tingkat akurasi analisis sentimen yang dihasilkan menggunakan algoritma K-Nearest Neighbors (KNN). Menghasilkan bahwa dengan algoritma KNN diperoleh nilai akurasi Pred.Negatif nilainya sebesar 69,59%. Hasil dari Pred.Positif nilainya sebesar 71,70%.  Sedangkan nila accuracy 70,51% dan nilai AUC sebesar  0.804 +/- 0.053 (mikro: 0.804) (positive class: Positif).   E-commerce is a means of commercial transactions between individuals and organizations or a buying and selling transaction conducted online. One example of e-commerce implementation is the Shopee application. Shopee is available in the form of a mobile phone application that makes it easier for users to shop online, allowing access anytime and anywhere. Of course, this application has advantages and disadvantages perceived by the public. Due to the application’s strengths and weaknesses, many users provide both positive and negative reviews of the app. Techniques for utilizing large amounts of data can be applied through Data Mining. The purpose of this research is to analyze issues related to several reviews of the Shopee application on Google Play Store and to determine the accuracy results of sentiment analysis generated using the KNN (K-Nearest Neighbors) algorithm. The result showed that with KNN algorithm obtained the value of Pred. Negative accuracy value of 69.59%. Results from Pred. Positive value of 71.70%.  While accuracy value 70.51% and AUC value of 0804 +/-0053 (Micro: 0804) (positive class: positives). 
Analisis Sentimen pada Ulasan Aplikasi Notion AI dengan Metode Support Vector Machine dan Random Forest Mawadatul Maulidah; Suleman Suleman; Angga Ardiansyah; Erina Rahma; Queen Elizabeth Anggiano Widodo
SENTRI: Jurnal Riset Ilmiah Vol. 5 No. 2 (2026): SENTRI : Jurnal Riset Ilmiah, Februari 2026
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/sentri.v5i2.5727

Abstract

In the digital era, the utilization of Artificial Intelligence (AI) has been rapidly expanding across various fields, including information management through applications such as Notion AI. This study aims to analyze user sentiment toward the Notion AI application based on review comments on the Google Play Store using two machine learning algorithms, namely Support Vector Machine (SVM) and Random Forest. The data were obtained via web scraping, comprising 300 review comments, 150 positive and 150 negative. The dataset was then divided into 80% training data and 20% testing data to ensure that the model evaluation was conducted objectively using data that were not involved in the training process. The research process included stages of data collection, preprocessing, classification modeling, model evaluation, data presentation, and analysis using the RapidMiner tool. The results showed that the Random Forest algorithm outperformed SVM, achieving an accuracy of 95.97%, a precision of 98.27%, a recall of 94.34%, and an AUC value of 1.000. Meanwhile, the SVM model produced an accuracy of 85.97% and an AUC of 0.954. This study indicates that Random Forest is more effective in handling variations in text data and provides more accurate classification results. Overall, the majority of user reviews of Notion AI are positive, particularly regarding the ease of AI writing features and productivity enhancement, while negative reviews generally relate to language limitations and paid features.
Co-Authors Andi Saryoko Andrian Eko Widodo Angga Ardiansyah Asna Mauhibah Maurani Cucu Ika Agustyaningrum Diantika, Sri Erina Rahma Fandhilah Fandhilah Fanny Fatma Wati Fauzi Ahmad Muda Galih Praditya Nugraha Gata, Windu Gemilang, Lina Putri Hilman Ferdinandus Pardede Hilman Ferdinandus Pardede Hiya Nalatissifa Husni Faqih Indriarti, Novi Fitria Nadiyah Hidayati Nafisah Muazarah Nugroho Adi Putro Nurlaelatul Maulidah Panca Saputra, Elin Queen Elizabeth Anggiano Widodo Rachmawati Darma Astuti Recha Abriana Anggraini Rendi Septian Ridan Nurfalah Riki Supriyadi Rizki Aulianita Rizki Aulianita Siti Khalimah Siti Nurajizah Sopiyan Dalis Suleman Suleman Suleman Suleman Taufik Rahman Ummu Radiyah Widiastuti Widiastuti Windu Gata