Di antara banyaknya pilihan olahraga, <em>fitness</em> dipusat kebugaran menjadi salah satu opsi yang dapat di pilih. <em>Fitnes</em><em>s</em> bukan lagi olahraga berat hanya untuk laki-laki saja, kini perempuan pun dapat melakukannya untuk menjaga kebugaran tubuh, menurunkan berat badan dan membentuk tubuh ideal. Sebelum menetapkan pilihan untuk menjadi <em>member</em> disalah satu tempat kebugaran, perlu mempertimbangkan beberapa hal, seperti budget yang harus dikeluarkan dengan keuntungan yang akan diterima. semakin lengkap fasilitas penunjang di sebuah tempat <em>fitness</em>, maka semakin mahal tarif atau biaya yang dibayarkan setiap bulan sebagai <em>member</em>. Selain perlengkapan olahraga yang sudah tersedia dan memadai, ada instruktur atau <em>personal trainer</em> yang juga dapat memberikan arahan Program latihan, porsi latihan, tehnik melakukan fitness agar setiap gerakan yang dilakukan tidak salah dan malah berakibat cidera otot dan sendi. yang menjadi pertimbangan adalah kita akan memilih program pelatihan untuk mengetahui apa yang paling cocok untuk seseorang. Pada paper ini membahas tentang bagaimana metode <em>Finite State Automata </em>jenis NFA dapat diimplementasikan dalam Registrasi program latihan (<em>workout plan</em>) pada <em>member</em> tempat kebugaran.Dengan di terapkan metode ini, user diharapkan dapat terbantu dalam memilih program latihan (<em>workout plan</em>) sesuai kebutuhan dan dapat lebih memahami bagaimana proses pemilihan <em>workout plan</em> yang sesuai dan benar.
The pandemic that occurred in Indonesia has not yet subsided and far from under control. Indonesian Ministry of Health is most appropriate person to responsible for providing an explanation of actual situation and extent to which state has handled it. However, he has rarely appeared in public lately to explain about handling of Covid-19 pandemic. In response, many people are pros and cons come to give their opinions and feedback. The increasing use of internet during pandemic, especially on social media, where one of them is Twitter, which is a means of expressing opinions. Posting tweets is a community habit to assess or respond to events, as well as represent public's response to an event, especially Ministry of Health steps and policies in handling and breaking chain of Covid-19 pandemic.The tweet posts were taken only in Indonesian-language and also related to performance of Government, especially Ministry of Health. After that, a label is given so that sentiment of tweets is known. To test results of these sentiments, an algorithm is used by comparing two methods of Support Vector Machine (SVM) and Naïve Bayes (NB). Validation was carried out using k-Fold Cross Validation to obtain an accuracy value. The results show that accuracy value for NB algorithm is 66.45% and SVM algorithm has a greater accuracy value of 72.57%. So it can be seen that SVM algorithm managed to get the best accuracy value in classifying positive comments and negative comments related to sentiment analysis towards Ministry of Health. Keywords—Support Vector Machine, Naïve Bayes, Analisis sentimen, K-Fold Cross Validation
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