Wirawan, Nanda Cahyo (2017) Analisis Sentimen Dengan Query Expansion Pada Review Aplikasi M-Banking Menggunakan Metode Fuzzy K-Nearest Neighbor (Fuzzy K-Nn). Sarjana thesis, Universitas Brawijaya.
Abstract
Di era digital saat ini, bisnis berkembang semakin pesat memanfaatkan aplikasi digital. Dunia perbankan adalah satu lini bisnis yang memanfaatkan dengan baik kemajuan teknologi saat ini. Mobile banking adalah salah satu produk digital dalam perbankan yang paling populer karena tidak serumit SMS banking maupun internet banking. Demi menghadapi bisnis perbankan yang ketat, setiap perusahaan menerapkan feedback dari setiap nasabah. Saat ini nasabah dapat menggunakan fitur review yang sudah disiapkan. Review banyak yang masuk tiap harinya, akan membutuhkan waktu untuk memilah. Sistem dengan machine learning diharapkan mampu menghemat waktu untuk memilah data tekstual berpolaritas yang berupa review ini. Sistem dalam penelitian ini dibuat menggunakan metode fuzzy k-nearest neighbor (fuzzy k-NN). Metode fuzzy k-NN merupakan metode gabungan antara logika fuzzy dan algoritme k-Nearest Neighbor. Pembobotan yang dilakukan untuk mengolah data tekstual menjadi data numerik yang mampu dikomputasi menggunakan metode TF-IDF dengan Cosine similarity untuk menghitung jarak antar data. Berdasarkan hasil pengujian, sistem ini menghasilkan rata-rata akurasi terbaik sebesar 94% dengan F-Measure rata-rata sebesar 0,9273.
English Abstract
In this digital era, bussiness grow significantly by using digital application. Banking is one field of business that utilizes the current technological advances very well. Mobile banking is one of the most popular digital banking products, because it is not as complicated as SMS banking or internet banking. In order to face the strict banking business, every company applying feedback from their customers. Now customers can use the review feature that provided by apps store. There's a lot of reviews that received every day, and it takes some time to knowing what kind of review is that. Systems with machine learning are expected to save time to sort out textual data that containing polarity. The system’s machine learning in this study was made using fuzzy k-nearest neighbor (fuzzy k-NN) method. The fuzzy k-NN method is a combined method between fuzzy logic and the k-Nearest Neighbor algorithm. The weighting method for processing textual data into numerical data that can be computed is using TF-IDF method with Cosine similarity to calculate the distance between data. The output of this system is the classified data review. Based on the results of the tests, this system produces the best average accuracy 94% with an average F-Measure is 0.9273.
| Item Type: | Thesis (Sarjana) |
|---|---|
| Identification Number: | SKR/FTIK/2017/380/051706893 |
| Uncontrolled Keywords: | review aplikasi, analisis sentimen, fuzzy k-Nearest Neighbor |
| Subjects: | 000 Computer science, information and general works > 006 Special computer methods > 006.3 Artificial intelligence > 006.31 Machine learning |
| Divisions: | Fakultas Ilmu Komputer > Teknik Informatika |
| Depositing User: | Budi Wahyono Wahyono |
| Date Deposited: | 22 Aug 2017 02:38 |
| Last Modified: | 05 Nov 2024 03:00 |
| URI: | http://repository.ub.ac.id/id/eprint/1476 |
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