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All Journal International Journal of Advances in Applied Sciences Bulletin of Electrical Engineering and Informatics Journal Industrial Servicess JUITA : Jurnal Informatika POSITIF CESS (Journal of Computer Engineering, System and Science) Jurnal The Messenger Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Informatika Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Indonesian Journal on Software Engineering (IJSE) Jurnal Manajemen STIE Muhammadiyah Palopo Bina Insani ICT Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Information System for Educators and Professionals : Journal of Information System JITK (Jurnal Ilmu Pengetahuan dan Komputer) Techno Nusa Mandiri : Journal of Computing and Information Technology Edukasi Islami: Jurnal Pendidikan Islam Jurnal Hukum Ekonomi Syariah Jurnal Riset Informatika Journal of Information System, Applied, Management, Accounting and Research Al Marhalah Kordinat : Jurnal Komunikasi antar Perguruan Tinggi Agama Islam JAMI: Jurnal Ahli Muda Indonesia Al-Liqo: Jurnal Pendidikan Islam Journal of Students‘ Research in Computer Science (JSRCS) Indonesian Journal of Networking and Security - IJNS Kontribusi: Jurnal Penelitian dan Pengabdian Kepada Masyarakat Paradigma INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System Journal of Training and Community Service Adpertisi TONGKONAN: Jurnal Pengabdian Masyarakat Jurnal Sistem Informasi dan Manajemen Ta'lim Ta'lim : Jurnal Multidisiplin Ilmu
Samudi Samudi
Universitas Nusa Mandiri
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Journal : CESS (Journal of Computer Engineering, System and Science)

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Analisis Sentimen Zoom Cloud Meetings di Play Store Menggunakan Naïve Bayes dan Support Vector Machine Nuraeni Herlinawati; Yuri Yuliani; Siti Faizah; Windu Gata; Samudi Samudi
CESS (Journal of Computer Engineering, System and Science) Vol 5, No 2 (2020): JULI 2020
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (83.303 KB) | DOI: 10.24114/cess.v5i2.18186

Abstract

Aplikasi zoom cloud meetings yang mulai booming digunakan sekarang ini karena adanya pandemi virus corona, sehingga membuat semua kegiatan dilakukan secara virtual. Zoom cloud meetings merupakan aplikasi yang memiliki berbagai fitur termasuk video & audio conference. Pada penelitian ini penulis menggunakan metode Naïve Bayes dan Support Vector Machine dalam menganalisa label sentimen positif atau negatif pada ulasan para pengguna aplikasi zoom di Google Play Store. Jumlah dataset setelah prepocessing menjadi 1.007 record. Data hampir seimbang dengan label positif sebanyak 546 dan label negatif 461 ulasan. Evaluasi model menggunakan 10 fold cross validation diperoleh nilai akurasi dan nilai AUC dari masing-masing algoritma yaitu untuk NB nilai akurasi = 74,37% dan nilai AUC = 0,659. Sedangkan untuk algoritma SVM nilai akurasi = 81,22% dan nilai AUC = 0,886. Dalam penelitian ini dapat diketahui bahwa tingkat akurasi yang didapatkan algoritma Support Vector Machine (SVM) lebih unggul 6,85% dibandingkan algoritma Naïve Bayes (NB). Kata Kunci— Zoom Cloud Meetings, Google Play Store, Virus Corona, Naïve Bayes, Support Vector Machine. Abstract— Zoom cloud meetings application that began to boom is used today because of the corona virus pandemic, so that all activities are carried out virtually. Zoom cloud meetings is an application that has various features including video & audio conferencing. In this study the authors used the Naïve Bayes method and Support Vector Machine in analyzing positive or negative sentiment labels on the zoom users' reviews on the Google Play Store. The number of datasets after prepocessing is 1,007 records. The data is almost balanced with 546 positive labels and 461 negative labels. Evaluation of the model using 10 fold cross validation obtained accuracy values and AUC values from each algorithm, namely for NB, the accuracy value = 74.37% and the AUC value = 0.659. As for the SVM algorithm the accuracy value = 81.22% and the AUC value = 0.886. In this study it can be seen that the accuracy obtained by the Support Vector Machine (SVM) algorithm is 6.85% superior to the Naïve Bayes (NB) algorithm.
Co-Authors - UBSI, Slamet Abd. Rahman ADHI DHARMA SURIYANTO Agus Junaidi Akmaludin Akmaludin, Akmaludin Ali Nurdin Ali Nurdin Alma Eka Ayuningtyas Anas, Anas Nasrudin Andi Saryoko Andy Widya Putera Anna Mukhayaroh Anna Mukhayaroh Anna Mukhayaroh Anna Mukhayaroh, Anna Arifin, Muhammad Arifin Budiman Budiman Efi Rokana Endang Retnoningsih Erni Ratna Dewi Erwina Erwina, Erwina Gunawan Witjaksana, Gunawan Harmono, Feri Prasetyo Hartawat, A. Sri Indira i Haryani Hasmirati Hayat, Husnul Heri, Heri Setiaji Herlambang Brawijaya Irawati, Titik Irfan, Noor Kudiantoro Widianto, Kudiantoro Liliek Budiastuti Wiratmo, Liliek Budiastuti M. Mujiono, M. Mujiono Mallapiang, Yassir Mohammad Badrul Muhammad Muharrom Nalendra, Adimas Nicodias Palasara Nuraeni Herlinawati Qalbi, Nur Qalbi, Nur Qalbi Qudsiyah Qudsiyah Ratna Dewi, Erni Riska Aryanti Rohmatulloh, Puri Rosidin Rosidin Siti Faizah Slamet Widodo Slamet Widodo Slamet Widodo Slamet Widodo Soleh, Soleh Sopiyan Dalis Suhardin Suhardin, Suhardin Sujariati Sujariati, Sujariati Syahruddin Mahmud, Syahruddin Taufik Baidawi, Taufik Ukun, Ukun Kurnia Windu Gata Yuliani, Yuri Yunia, Noorma Zulfikar, Rachmat