Klasifikasi Sentimen Masyarakat di Twitter terhadap Kenaikan Harga Bahan Bakar Minyak dengan Metode Modified K-Nearest Neighbor
نویسندگان
چکیده
Kenaikan harga Bahan Bakar Minyak menjadi salah satu tranding topic di kalangan masyarakat Indonesia, baik dunia nyata maupun maya khususnya media sosial Twitter. Perkembangan teknologi informasi yang sangat pesat memudahkan dalam menyebarkan media. Naiknya BBM memunculkan opini mengandung sentimen positif dan negatif. Penelitian ini dilakukan untuk mengetahui publik terkait kebijakan pemerintah menaikkan serta menerapkan metode Modified K-Nearest Neighbor pengklasifikasian pengguna Twitter terhadap kenaikan BBM. merupakan klasifikasi berdasarkan kemunculan kelas terbanyak pada data latih. Data digunakan adalah tweet bahasa Indonesia kata kunci “kenaikan BBM” dengan jumlah dataset sebanyak 3.000 tweet. Pembobotan menggunakan TF-IDF melakukan ke dua Hasil dari penelitian Akurasi tertinggi didapat 83.33% perbandingan 90:10 K=3.
منابع مشابه
Klasifikasi Data Cardiotocography Dengan Integrasi Metode Neural Network Dan Particle Swarm Optimization
Backpropagation (BP) adalah sebuah metode yang digunakan dalam training Neural Network (NN) untuk menentukan parameter bobot yang sesuai. Proses penentuan parameter bobot dengan menggunakan metode backpropagation sangat dipengaruhi oleh pemilihan nilai learning rate (LR)-nya. Penggunaan nilai learning rate yang kurang optimal berdampak pada waktu komputasi yang lama atau akurasi klasifikasi yan...
متن کاملA Modified Editing k-nearest Neighbor Rule
Classification of objects is an important area in a variety of fields and applications. Many different methods are available to make a decision in those cases. The knearest neighbor rule (k-NN) is a well-known nonparametric decision procedure. Classification rules based on the k-NN have already been proposed and applied in diverse substantive areas. The editing k-NN proposed by Wilson would be ...
متن کاملA Modified K-Nearest Neighbor Algorithm Using Feature Optimization
A classification technique is an organized approach for building classification model from given input dataset. The learning algorithm of each technique is employed to build a model used to find the relationship between attribute set and class label of the given input data. Presence of irrelevant information in the data set reduces the speed and quality of learning. The technique of feature sel...
متن کاملDrought Monitoring and Prediction using K-Nearest Neighbor Algorithm
Drought is a climate phenomenon which might occur in any climate condition and all regions on the earth. Effective drought management depends on the application of appropriate drought indices. Drought indices are variables which are used to detect and characterize drought conditions. In this study, it was tried to predict drought occurrence, based on the standard precipitation index (SPI), usin...
متن کاملFast Approximate Nearest-Neighbor Search with k-Nearest Neighbor Graph
We introduce a new nearest neighbor search algorithm. The algorithm builds a nearest neighbor graph in an offline phase and when queried with a new point, performs hill-climbing starting from a randomly sampled node of the graph. We provide theoretical guarantees for the accuracy and the computational complexity and empirically show the effectiveness of this algorithm.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: SATIN (Sains dan teknologi informasi)
سال: 2023
ISSN: ['2460-0822', '2527-9114']
DOI: https://doi.org/10.33372/stn.v9i1.988