ALFIA EGI PRASTIA BR. MUNTHE, NPM 2109100100 (2025) ANALISIS PERBANDINGAN ALGORITMA NAÏVE BAYES DAN SUPPORT VECTOR MACHINE DALAM MENENTUKAN PEMINAT PEMBELI SMARTPHONE DI ERAFONE SUZUYA BARU. Skripsi thesis, Universitas Labuhanbatu.
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Abstract
Penelitian ini bertujuan untuk menganalisis dan membandingkan kinerja dua algoritma klasifikasi populer, yaitu Naïve Bayes dan Support Vector Machine (SVM), dalam menentukan minat pembeli smartphone di Erafone Suzuya Rantauprapat. Data yang digunakan merupakan data penjualan smartphone dari berbagai merek seperti Apple, Oppo, Samsung, Vivo, dan Xiaomi yang telah melalui proses pra-pemrosesan meliputi pembersihan data dan normalisasi agar sesuai dengan kebutuhan model machine learning. Selanjutnya, dataset dibagi menjadi data pelatihan dan pengujian untuk menguji kemampuan prediksi masing-masing algoritma. Hasil eksperimen menunjukkan bahwa Naïve Bayes memiliki performa lebih unggul dibandingkan SVM pada dataset ini dengan nilai akurasi mencapai 85.71%, sedangkan SVM hanya memperoleh akurasi sebesar 57.14%. Selain itu, nilai F1-score Naïve Bayes juga lebih tinggi yaitu sebesar 88.89%, menandakan keseimbangan antara precision dan recall yang baik dalam memprediksi kategori minat pembeli seperti rendah, sedang maupun tinggi. Kata Kunci : Erafone, Machine Learning, Naïve Bayes, Smartphone, SVM. =================================================================================================== This study aims to analyze and compare the performance of two popular classification algorithms, namely Naïve Bayes and Support Vector Machine (SVM), in determining smartphone buyer interest at Erafone Suzuya Rantauprapat. The data used is smartphone sales data from various brands such as Apple, Oppo, Samsung, Vivo, and Xiaomi that have gone through a pre processing process including data cleaning and normalization to suit the needs of the machine learning model. Furthermore, the dataset is divided into training and testing data to test the predictive ability of each algorithm. The experimental results show that Naïve Bayes has a superior performance compared to SVM on this dataset with an accuracy value reaching 85.71%, while SVM only obtained an accuracy of 57.14%. In addition, the F1-score value of Naïve Bayes is also higher at 88.89%, indicating a good balance between precision and recall in predicting buyer interest categories such as low, medium and high. Keywords : Sentiment Analysis, Google Play Store, Naïve Bayes Classifier, Shopee, Support Vector Machine.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Uncontrolled Keywords: | Erafone, Machine Learning, Naïve Bayes, Smartphone, SVM. =============================================== Sentiment Analysis, Google Play Store, Naïve Bayes Classifier, Shopee, Support Vector Machine. |
| Subjects: | H Social Sciences > HF Commerce Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General) |
| Divisions: | Fakultas Sains Dan Teknologi > Sistem Informasi |
| Depositing User: | Unnamed user with email repository@ulb.ac.id |
| Date Deposited: | 26 May 2025 09:41 |
| Last Modified: | 26 May 2025 09:41 |
| URI: | http://repository.ulb.ac.id/id/eprint/1434 |
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