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All Journal Jurnal Rekayasa Sistem Industri Gema Pendidikan International Journal of Artificial Intelligence Research SMARTICS Journal J-SAKTI (Jurnal Sains Komputer dan Informatika) M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika Jusikom: Jurnal Sistem Informasi Ilmu Komputer JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Infotek : Jurnal Informatika dan Teknologi Jurnal Cahaya Mandalika Jurnal Tika J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Inovasi Penelitian dan Pengabdian Masyarakat Journal of Informatics and Communication Technology (JICT) Malcom: Indonesian Journal of Machine Learning and Computer Science Golden Ratio of Data in Summary Innovative: Journal Of Social Science Research Journal of Informatics and Communication Technology (JICT)
Nurapriani, Fitria
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Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Public Health Social Sciences Other

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Journal : Jurnal Tika

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Analisis Sentimen, Text Mining Penerapan Analisis Sentimen Dan Naive Bayes Terhadap Opini Penggunaan Kendaraan Listrik Di Twitter Agustian, Adittia; Tukino; Nurapriani, Fitria
Jurnal Tika Vol 7 No 3 (2022): Jurnal Teknik Informatika Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim Bireuen - Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51179/tika.v7i3.1550

Abstract

Twitter is the most popular social media today. Can find out various Twitter responses that fall into the positive, neutral, or negative categories. Technological advances at this time are so rapid that vehicles will provide fuel for electric power or are called electric vehicles. Indonesia has become a country that encourages acceleration in the use of electric vehicles, according to the Minister of State-Owned Enterprises circular letter. The advancement of electric-powered vehicles is an innovation and technology that will continue to develop and transform. With the presence of the electric vehicle, the Indonesian government will serve as an important guest vehicle at the G20 Summit activities in Bali, Indonesia. The purpose of this study is to determine the public's response to electric vehicles which are currently widely used among the people of Indonesia. To find out the public response, sentiment analysis is needed through the responses of Twitter users. By generating positive, neutral, or negative categories. Based on the results of the classification of sentiment analysis on the support of electric vehicles. Data collection uses the Twitter API as an open source that can retrieve Twitter user responses, then the data cleaning process is carried out, converting Indonesian to English, then tested using the Naïve Bayes algorithm, and visualizing twitter data using python. Based on the classification results, public response to electric vehicles is more positive with 82% precision and 44% recall. By having 80% data accuracy through the Naive Bayes confusion matrix through the text mining process, python text blob, and word cloud as the relationship between words and twitter text
Clustering User Sentiment Transportasi Online Gojek Dan Grab Dengan Metode K-Means Annam, Dyno Syaiful; Hananto, Agustia; Nurapriani, Fitria; Tukino, Tukino
Jurnal Tika Vol 8 No 2 (2023): Jurnal Teknik Informatika Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim Bireuen - Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51179/tika.v8i2.2165

Abstract

As an online transportation service, people often discuss it by sharing their opinions through various social media platforms, one of which is Google Play reviews. The opinions given by the public regarding online transportation services are diverse. Users provide reviews about the application, and naturally, users will choose an application with good reviews. However, monitoring the opinions of the general public is not easy, given the large volume of data to be processed. Therefore, the researcher aims to obtain accurate and precise information from user reviews of Gojek and Grab using clustering techniques, specifically the K-means method, using the RapidMiner application. The results of the testing of both applications can be summarized as follows: Gojek and Grab receive reviews that are not significantly different, although Grab's reviews are slightly better. The classification using the K-Means method offers a solution to the issue of sentiment analysis in user reviews of online transportation applications.
Co-Authors -, Tukino AA Sudharmawan, AA Agustian, Adittia Ahnaf, Naufal Zubdi Alparizi, Muhamad Iqbal Annam, Dyno Syaiful April Lia Hananto Arkan Hilman Hakim Dwi Sulistya FIKRI HAIKAL Hananto, Agustia Hilabi, Shofa Shofiah Huda, Baenil Ikhsan, Muhammad Daffa kastiawan, Nurhayadi Kurniawan, Muhamad Dicky Kusumaningrum, Dwi Sulistya Lestari, Renita Lestari, Santi Arum Puspita Nijunnihayah, Uktupi Novalia, Elfina Nur ‘Azah Nurfauzi, Oka Muhamad Priatna, Bayu Priyatna, Bayu Ramadan, Mohamad Rizqulloh Saputri, Arini Sriardi, Mohammad Didit Tukino, Tukino Yulistina Nur DS Zulfiana, Rizka