Classification of Gimbal Stabilizer Products Using Naive Bayes Classification

Artika Surniandari, Hilda Rachmi, Suparni Suparni, Lisda Widiastuti, Haryani Haryani

Abstract


Menjadi videografer adalah hobi yang populer di masa pandemi ini karena berkreasi dalam bentuk video dan konten di YouTube menjadi alternatif selain sekedar mengisi waktu luang atau menghasilkan uang. Untuk mendukung kamera diperlukan perangkat pendukung, dalam hal ini seiring berjalannya waktu kamera yang mumpuni juga bisa didapatkan dari perangkat smartphone, teknologi perangkat tersebut harus diimbangi dengan kemampuan pengguna dalam mengoperasikannya. Gimbal Stabilizer salah satu jawabannya, menggunakan gimbal stabilizer menjadi salah satu alternatif karena dapat meredam getaran sehingga gambar yang dihasilkan lebih maksimal. Banyak website memberikan informasi tentang produk gimbal stabilizer dengan memberikan banyak informasi dalam gambar dan ulasan pengguna. Oleh karena itu, analisis sentimen merupakan solusi untuk masalah pengelompokan opini atau review menjadi opini positif atau negatif secara otomatis berdasarkan hal ini untuk mendapatkan penilaian penggunaan gimbal berdasarkan analisis sentimen yang diberikan melalui review produk, kami akan mencoba menguji parameter untuk menghasilkan n gram pada tahap pre-processing, k-fold pada cross validation dan penerapan particle swarm optimization untuk meningkatkan akurasi menggunakan metode Naive Bayes. Hasil dari tester ini menghasilkan akurasi sebesar 84,42. 


Becoming a videographer is a popular hobby during this pandemic because creating works in the form of videos and content on YouTube is an alternative to just filling your spare time or making money. To support the camera, the supporting device is needed, in this case, as time goes by, a capable camera can also be obtained from smartphone devices, the technology of the device must be balanced with the user’s ability to operate it. Gimbal Stabilizer is one of the answers, using a gimbal stabilizer is an alternative because it can reduce vibrations so that the resulting image is maximized. Many websites provide information about gimbal stabilizer products by providing a lot of information in images and user reviews. Therefore, sentiment analysis is a solution to the problem of grouping opinions or reviews into positive or negative opinions automatically based on this to get an assessment of the use of gimbals based on the sentiment analysis provided through product reviews, we will try to test the parameters to produce n grams at the pre-processing stage, k-fold on cross validation and the application of particle swarm optimization to increase accuracy using the Naive Bayes method. The results of this tester produce an accuracy of 84.42


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DOI: https://doi.org/10.31294/inf.v9i2.14064

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