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Galuh Saputri
Universitas Pamulang
Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Nursing Social Sciences Other

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Journal : Jurnal Sistem Komputer dan Informatika (JSON)

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Analisis Sentimen Komentar Youtube Tentang Relawan Patwal Ambulance Menggunakan Algoritma Naïve Bayes dan Decision Tree Abd Wahid; Galuh Saputri
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 2 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i2.4941

Abstract

The presence of the ambulance patrol is sometimes considered disturbing by the community, many people's opinions are still pro and contra about the actions carried out by civilian ambulance patrol volunteers because they are considered illegal and sometimes also arrogant. In this study. the researchers wanted to know the opinions and responses of the public about the actions taken by civilian ambulance patrol volunteers. The method used in this study is to perform sentiment analysis with data mining techniques to find the polarity of sentences in a document using the Naïve Bayes and Decision Tree algorithms. The initial steps in this research were collecting comment data by scraping YouTube comments using API Key Youtube V3, followed by manual data labeling, data cleaning, data preprocessing, and word weighting using TF-IDF. From the overall results of testing with 600 training data, the Naïve Bayes algorithm has a higher accuracy value of 66.72% while the Recall value is 64.98%. Testing with the Decision Tree algorithm in this study has a higher Recall compared to Naïve Bayes. %. From the results of the YouTube comment dataset used in this study, it can be concluded that the Naïve Bayes algorithm has a higher accuracy value than the Decision Tree algorithm, so it can be concluded that Naïve Bayes has the best accuracy in the YouTube comment dataset used in this study.
Co-Authors Abd Wahid Abdul Hafizh Ala’uddin Achmad Setya Budi Rojak Agi Nurpalin Agung Siswopranoto Agung Siswopranoto Agus Rahmawan Agusti Setiabudi Pramata Ahkmad Fazmi Septiandi Ahmad Doni Ahmad Nuryadi Ahmad Rifki Fachrudin Aldiansyah, Aldiansyah Alfan Akbar Halim Syakur Alva Herbart Miftahul Firdaus Alwiyah Rachman Anas, Irham Anggi Pradana Yoani, Anggi Ariz Nur Annafi Firman Aulia Ikhsan Barry Vasyah Bayu Urip Pandiangan Deni Setia Budi Diky Syafitra Diky Dimas Adiansyah Dimas Danang Aji W.I Yajid Dita Arysanti Emi Sita Eriana Fauzan Kholid Fauzan Musyaffa Fikri Agustiawan jumaidi Fitra Listiyono Haqun Baitika Iis Aisyah Ikhsannudin Ma'sum Ikhwan Naufal Yupi Imam Balda Pendo Intan Kamelasari Joko Suwarno Joko Suwarno Jonathan Jeremi Siagian Junaidi Junaidi Kayla Fadalwa Khofifah Nurfaisah Leonard Viffo Lisda Amalia Maria Elisabeth Taena Maulana Sandy Mochamad Masdarul Anwar Muhamad Fahmi Muhamad Rino Setiawan Muhammad Bintang Muhammad Hafidz Asyauri Muhammad Rafi Shiddiq Muhammad Raihan Muhammad Rizky Safrihza Nailan Shafa Noveindra Salim Nurohman Oktavia, Hani Paryanto, Agus Prasetyo , Andhika Rafi Ivan Alessandro Rapli Muhammad Ardiansah Umar Rapli Saputra Rayhan Bilal Alghifary Alghifary Remis Putra Tafonao Rescue Asmara Asmara Ria Ester Rica Rahim Rizky Ardiansyah Moh.Zubaidi Rizqa Rahmawati Rosa Shinta Putri Fairul Samsul Maarif Siti Raudhatul Syifa Siti Ulfiah Suci Ayu Peritami Suwely Suwely Syech Teguh Firmansyah Verolia Yunita Putri Wahyu Wibowo Wendy Kautsar Willis Puspita Sari Wirayuga Rizkia Suwahyo Yazid Azriel Yoel Michael Sihombing Yuke Pradikta, Arivansa Zidane Muhammad Azmi