Analisis Sentimen Pelanggan Terhadap Layanan ShopeeFood Pada Media Sosial Twitter Menggunakan Algoritma Naïve Bayes dan Support Vector Machine (SVM)

SETIADI, KINDI (2022) Analisis Sentimen Pelanggan Terhadap Layanan ShopeeFood Pada Media Sosial Twitter Menggunakan Algoritma Naïve Bayes dan Support Vector Machine (SVM). S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

Most people the internet and technologies more advanced now, we can quickly find what we want from e-commerce and can be used as online shop. One of them is Shopee which has release ShopeeFood service as service food delivery. ShopeeFood has more than 500 merchant partners in Jabodetabek in a year. In this case most people give a lot of opinion in social media Twitter. Research purposes is can analyze opinion people and can be classified to naïve bayes and support vector machine and then the result has two class negative and positive. The research method used is data collection, data cleansing, and classification. As for the performance results of sentiment analysis using algorithm naïve bayes with level accuracy 90.43%, precission 99.74%, recall 76.65%, dan f1-score 86.68%. While the algorithm support vector machine has level accuracy 99.27%, presisi 99.60%, recall 98.60%, dan f1-score 99.10%. Key words: shopeefood, sentiment analysis, naïve bayes, support vector machine Banyaknya pengguna internet dan teknologi yang semakin canggih saat ini, kita dapat dengan cepat menemukan apa yang kita inginkan melalui ECommerce dan dapat digunakan sebagai peluang bisnis dengan membuka toko online. Salah satunya adalah Shopee yang telah merilis layanan ShopeeFood sebagai layanan pesan antar makanan secara online yang dapat memudahkan masyarakat. ShopeeFood memiliki kurang lebih dari 500 mitra merchant di Jabodetabek dalam setahun. Semakin banyaknya minat masyarakat terhadap layanan tersebut. Dalam hal ini masyarakat banyak memberikan pendapat mereka menggunakan media sosial terutama twitter. Tujuan penelitian ini adalah dapat menganalisis opini masyarakat yang nantinya dapat diklasifikasin oleh metode naïve bayes dan support vector machine, kemudian hasil klasifikasi terdapat 2 kelas negatif dan positif. Metode penelitian yang digunakan adalah pengumpulan data, pembersihan data, dan klasifikasi. Adapun hasil perfoma analisis sentimen menggunakan algoritma naïve bayes dengan tingkat akurasi 90.43%, presisi 99.74%, recall 76.65%, dan f1-score 86.68%. Sedangkan algoritma support vector machine memiliki tingkat akurasi 99.27%, presisi 99.60%, recall 98.60%, dan f1- score 99.10%. Kata kunci: shopeefood, analisis sentimen, naïve bayes, support vector machine

Item Type:	Thesis (S1)
Call Number CD:	FIK/INFO. 22 104
NIM/NIDN Creators:	41519120004
Uncontrolled Keywords:	shopeefood, analisis sentimen, naïve bayes, support vector machine
Subjects:	100 Philosophy and Psychology/Filsafat dan Psikologi > 150 Psychology/Psikologi > 154 Subconscious and Altered States and Process/Psikologi Bawah Sadar > 154.6 Sleep Phenomena/Fenomena Tidur > 154.63 Dreams/Mimpi > 154.634 Analysis/Analisis 500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika 700 Arts/Seni, Seni Rupa, Kesenian > 750 Painting and Paintings/Seni Lukis dan Lukisan > 751 Techniques and Procedures/Teknik Seni Lukis dan Lukisan, Prosedur Seni Lukis dan Lukisan > 751.4 Techniques and Procedures/Teknik dan Prosedur > 751.49 Other Methods/Metode Lainnya
Divisions:	Fakultas Ilmu Komputer > Informatika
Depositing User:	ADELINA HASNA SETIAWATI
Date Deposited:	05 Oct 2022 09:12
Last Modified:	05 Oct 2022 14:53
URI:	http://repository.mercubuana.ac.id/id/eprint/69948

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