NELVI NURRIZQI M, NPM 2009100077 (2024) IMPLEMENTASI METODE NAIVE BAYES DAN NEURAL NETWORK UNTUK MENENTUKAN MINAT MASYARAKAT PADA HANDPHONE SAMSUNG. Tugas_Akhir (Artikel) INFORMATIKA Universitas Labuhanbatu, 12 (3). pp. 602-608. ISSN 2615-1855 (e-ISSN)/ 2303-2863 (p-ISSN)
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Abstract
Naive Bayes and Neural Network methods are used in analyzing people's interest in Samsung mobile phones to gain a better understanding of consumer preferences. Naive Bayes is a simple but very effective probability-based classification method. This method generates possible consumer interests by analyzing features such as price, specifications, and brands, and calculating the probability of different categories. Naive Bayes is very useful in situations where data has independent features, and can provide accurate results at high speed. By identifying patterns of people's preferences, this method can help Samsung adjust marketing and product strategies that are more in line with consumer needs. On the other hand, Neural Network offers more complex analytical capabilities by imitating the way the human brain works through a network of neurons. This method is used to process larger and more complex data in understanding consumer interest patterns in Samsung mobile phones. Neural Network can identify deeper relationships between various factors, such as the interaction between camera features and user needs, using deep learning processes. The purpose of using Neural Network is to capture nuances and trends that cannot be identified with simple methods, thereby providing a more comprehensive view of what drives consumer interest. The use of these two methods of analysis in public interest in Samsung mobile phones has provided very satisfactory results. The calculation values obtained from both methods show a high level of accuracy in the classification of consumer interest. The results of this analysis provide valuable insights for Samsung in understanding consumer preferences and needs, as well as helping the company in designing more effective products and marketing strategies. Thus, the combination of the use of Naive Bayes and Neural Networks not only provides stron g results, but also provides a more holistic approach to consumer data analysis. Keywords : Classification, Naive Bayes Method. Neural Network Method
Item Type: | Article |
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Uncontrolled Keywords: | Classification, Naive Bayes Method. Neural Network Method. |
Subjects: | Z Bibliography. Library Science. Information Resources > ZA Information resources Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources |
Divisions: | Fakultas Sains Dan Teknologi > Sistem Informasi |
Depositing User: | Unnamed user with email repository@ulb.ac.id |
Date Deposited: | 12 Sep 2024 09:23 |
Last Modified: | 12 Sep 2024 09:23 |
URI: | http://repository.ulb.ac.id/id/eprint/1094 |
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