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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Bulletin of Computer Science Research
Yan Rianto
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Computer Science & IT

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Teknik Visualisasi Grafik Berbasis Web di Atas Platform Open Source Indri Juwita Asmara; Elmi Achelia; Wildan Maulana; Rini Wijayanti; Yan Rianto
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2009
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

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Abstract

Data dan informasi merupakan kebutuhan mendasar di era digital saat ini. Perkembangan sistem informasitelah mempengaruhi pola diseminasi data. Data dan informasi yang beragam di tampilkan di berbagai media,salah satunya internet. Bentuk penyajian informasi yang dinamis, interaktif, sistematis, dan mudahdiinterpretasi merupakan hal yang utama dalam pengolahan data menjadi informasi di dunia maya. Salah satucara atau teknik yang dapat digunakan adalah teknik visualisasi. Teknik visualisasi dapat diterapkan ke dalamsistem informasi atau aplikasi berbasis web dengan koneksi database. Hal ini bertujuan untuk memperluaspemanfaatan data. Sejalan dengan perkembangan open source, teknik visualisasi juga dikembangkan denganplatform open source dengan mengaplikasikan berbagai tools open source, hal ini dimaksudkan agar aplikasidapat dimodifikasi dan diimplementasi oleh berbagai pihak.Kata Kunci: data, infrormasi, grafik, teknik visualisasi, open source.
Analisis Sentimen Berita Online Terhadap Transportasi Online di Indonesia dengan Metode Naïve Bayes Classifier, Support Vector Machine dan K-Nearest Neighbor Selawati, Arina; Yan Rianto; Rachmawati Darma Astuti; Ainun Zumarniansyah; Deny Novianti
Bulletin of Computer Science Research Vol. 5 No. 2 (2025): February 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i2.477

Abstract

News about online transportation in Indonesia in 2019 until early 2020 has been published in various Indonesian online media, because there is enough information in the form of text without numerical scale, it is difficult to classify information information efficiently without reading the full text. Sentiment analysis is used to automate the process of assessing opinion whether it is positive or negative. Classifying sentiments on news from online news media with the Text Mining process and using the method of increasing the Classification Accuracy / Ensemble Method of Engineering by combining the classification algorithm naïve bayes method, classifier Supporting vector machines and k-nearest neighbors added with the Particle Swarm Optimization method and Vote method The next will be a comparative analysis. The results of the study above get an SVM exam accuracy value even after using the PSO selection feature with the ensemble. Select is still appropriate at 84.16%, Likewise for NB algorithm which gets 79.08% and KNN which gets approval 87.19%. These words will be used to see words related to sentiments that often appear and have the highest weight and can be used to find out positive news articles and negative news articles. And for this research the model that uses KNN algorithm gets the highest accuracy.
Co-Authors Ainun Zumarniansyah Arina Selawati Deny Novianti Elmi Achelia Indri Juwita Asmara Rachmawati Darma Astuti Rini Wijayanti Wildan Maulana