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All Journal JURNAL SISTEM INFORMASI BISNIS PROSIDING SEMINAR NASIONAL ILKOM Jurnal Ilmiah JOURNAL EQUITABLE Jurnal Ilmiah Hijau Cendekia Musamus Journal of Agribusiness Manajemen Agribisnis: Jurnal Agribisnis JURNAL ILMIAH AGRINECA JURNAL RECTUM: Tinjauan Yuridis Penanganan Tindak Pidana GANESHA: Jurnal Pengabdian Masyarakat PROFICIO: Jurnal Pengabdian Masyarakat Golden Ratio of Finance Management Jurnal Sylva Lestari Prosiding University Research Colloquium Journal of Biodiversity and Biotechnology Journal of Community Capacity Empowerment Journal of Rural and Urban Community Studies
Suswadi
Universitas Tunas Pembangunan Surakarta (UTP)
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Medicine & Pharmacology Social Sciences Other

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Journal : ILKOM Jurnal Ilmiah

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Sentiment Analysis of Shopee App Reviews Using Random Forest and Support Vector Machine Suswadi, Suswadi; Erkamim, Moh.
ILKOM Jurnal Ilmiah Vol 15, No 3 (2023)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v15i3.1610.427-435

Abstract

During the COVID-19 outbreak, Indonesian marketplaces were significantly impacted including Shopee app. It is necessary to evaluate the features and services of the Shopee application by looking at the feedback given by the public in Google Play Store reviews. This is what prompted research to be conducted from Kaggle data in the form of Shopee reviews. From this data, sentiment analysis is carried out utilizing the Support Vector Machine (SVM) and Random Forest methods. This method are used to classify reviews based on positive and negative sentiments. The results showed that the level of classification accuracy in the Random Forest model is 82.21%. While the SVM model provides a higher level of accuracy of 84.71%. Data exploration on positive and negative sentiment classes is used to find insight into this problem. In positive sentiment, words that often appear such as “belanja”, “aplikasi”, and “barang” are found. As for the negative sentiments, namely “ongkir”, “kirim”, “aplikasi”. These words can be used to be a quality improvement or evaluation for the Shopee company.
Co-Authors Aan Budi Santoso Abdul jalil Achmad Fatchul Aziez AF Aziez AF Aziez Agung Prasetyo Agung Prasetyo Agung Prasetyo Agung Prasetyo Agung Riyanto Agus Budiyono Agustina Tri Suryaningsih Akrom, Akrom Andi Walela Annida Fidiena Aprilia Yuanita Anwaristi Arbianti ARDIANSYAH ARDIANSYAH Arganata Yuda Prastya Yuana Aryani, Alina Dian ATIK NUR FARIDA Damayanti, Adhisty Puri Daryanti David Bagas Riyanto Dewi Gesang Nurlarasati Dewi Wulan Sari Diego Hermacho Dwanita Widodo, Zandra DWI SURYANTO Dwi Susilo Utami Dwi Wahyuni D` Kartikasari Eka Aprilliyanti Elviandri, Elviandri Endang Suprapti Erni Widarti Faustina Yuniastuti Faustina Yuniastuti Fidiena, Annida Handayani Handayani HARTOYO, EKO Haryuni Heriyanto Heriyanto Heriyanto Heriyanto Holyness Nurdin Singadimedja Ismail Aji Eko Cahyono Jalu Ariowibowo Jayawarsa, A.A. Ketut K Prasetyowati K. Prasetyowati K. Prasetyowati KHARISMA A.E.S KUSRIANI PRASETYAWATI Kusriani Prasetyowati Kusriani Prasetyowati Kusriani Prasetyowati Kusriani Prasetyowati Kusriani Prasetyowati KUSRIANI PRASETYOWQATI Latif Mahmudi, Wildana Lutfi Septi Mardiyanti M.Th Handayani M.Th. Handayani Mahananto Majasto Majasto Majasto Moh. Erkamim MTH HANDAYANI Muhammad Nurcholis Alhadi Muhammad Zidni Subarkah Mustaqim Mutiarra Ridyo Arum Nadian Nur Aulia Nadian Nur Aulia Ninda Beny Asfuri Norbertus Citra Irawan Nur Fauzi Permatasari, Dewi Rahmawati Intan Pratiwi Rahayuningsih R Soelistijono R.K. Ramadhani Rahmat Catur Haryadi Rahmat Catur Haryadi Raniasari Bimanti Esthi Ratih Dwi Kartikasari Ratih Dwi Kartikasari Riza, Wahyu Friyonanda ROHMAWAN HENDRIASTO S Sutarno S. SUTARNO Sahrifudin, Muhammad Angga Samuel Randamuluk Sapto Priyadi Sari, Y.E. Sekarani, Fadhilla Setie Harieni Shuwaifi, Ahmad Supartini Supartini Susilaningtyas Budiana Kurniawati sutarno Sutarno Sutarno R Sutarno Sutarno Sutarno Sutarno Suyanti T. Nurrokhim Tamalia Azzahra Wahyuningtyas Tanjung Kusumaningrum Teguh Supriyadi Teguh Supriyadi Tyas Soemarah K.D Tyas SOEMARAH KURNIA DEWI Tyas Soemarah Kurnia Dewi Utami, Rosita Tri Vynysha Maretha Enjellhyna Slamet Riyadi Warsina, W. Wiwik Handayani Wiyono Yulianingrum, Aullia Vivi Yuniastuti, Faustina Zahrul Yunus