Abstract
Twitter is the most popular microblogging service in Indonesia, with nearly 23 million users. In the era of big data such as the current tweets from customers, observers, potential consumers, or the community of users of products or services of a company will greatly help companies in knowing the industrial and consumer landscape, so as to determine strategic plans that will contribute to the company's growth. However, the use of data from social media such as Twitter is hampered by a number of technical difficulties in the process of collecting, processing, and analysing. Specifically, this research applies the Naïve Bayes Classifier algorithm in the process of sentiment analysis of tweets data into a prototype application that is intended to make it easier for companies / organizations to know people's perceptions of their products or services. The NBC algorithm was chosen because this algorithm is able to do a good classification even though it uses small training data, but has high accuracy and process speed for handling large training data. From the evaluation results found a prototype running well where the keywords entered will trigger the Twitter API to crawl the data then the mining process can be monitored at each stage and at the end of the process, the system will show the final sentiment level values and the representation of the calculation results log in a chart form over a certain period of time.
Highlights
Twitter is the most popular microblogging service in Indonesia, with nearly 23 million users
127 trigger the Twitter API to crawl the data the mining process can be monitored at each stage and at the end of the process, the system will show the final sentiment level values and the representation of the calculation results log in a chart form over a certain period of time
P. Wibawa , “Perbandingan Kinerja Metode Naive Bayes dan K-Nearest Neighbor untuk Klasifikasi Artikel Bahasa Indonesia,” Jurnal Teknologi Informasi dan Ilmu Komputer , vol 5, no
Summary
Riset dari Hootsuite, lembaga manajemen media sosial, dan We Are Social, perusahaan agensi global, di awal tahun 2020 menyebutkan bahwa hingga saat ini potensi pengguna media sosial di Indonesia mencapai 160 juta pengguna (kisaran lebih dari 59% dari total penduduk Indonesia) [1]. Twitter merupakan layanan microblogging terpopuler di Indonesia, dengan jumlah mencapai hampir 23 juta pengguna, dengan peningkatan mencapai dua kali lipatnya dari lima tahun sebelumnya [4]. Di era big data seperti saat ini tweets atau “kicauan” dari pelanggan, pemerhati, konsumen potensial, atau masyarakat dari pengguna produk atau layanan dari suatu perusahaan akan sangat membantu perusahaan dalam mengetahui lanskap industri dan konsumen, sehingga dapat menentukan langkah strategis yang akan menyumbangkan kontribusi terhadap pertumbuhan perusahaan. K-NN merupakan algoritma yang paling umum digunakan namun demikian K-NN memiliki kelemahan apabila menangani data training dalam jumlah yang kecil. Secara spesifik penelitian ini menerapkan algoritma NBC dalam proses analisa sentimen pada data tweets ke dalam sebuah prototipe aplikasi yang ditujukan untuk memudahkan perusahaan / organisasi mengetahui persepsi masyarakat terhadap produk atau layanan yang dimiliki. Kesimpulan dan usulan riset lanjutan dipaparkan pada bagian akhir laporan penelitian ini
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