SAPUTRI, JULINDA IKA (2023) KLASIFIKASI TARGET PEMILIHAN SPESIFIKASI HANDPHONE MENURUT MASYARAKAT DI TOKO ERAFONE MENGGUNAKAN ALGORITMA C4.5 DAN SUPPORT VECTOR MACHINE. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
Handphone have become an important communication tool and are widely preferred by different groups of people, both children, teenagers and parents. Therefore, research on the selection of handphone based on the best specifications is very important. In this study, the classification method is used to help users choose a handphone based on the required specifications using the C4.5 Decision Tree and Support Vector Machine algorithm. The purpose of the research is to find out how to implement the C4.5 and SVM algorithms using Python programming and to find out the performance comparison or model performance generated by the C4.5 and SVM algorithms. The variables studied are Timestamp, Name, Gender, Age, Location, Job, First_Know, Stock_Complete, First_Imp, First_Spek, Brand, Price, Camera_Back, Camera_Front, Processor, RAM, Battery, Memory_Internal, and Classified. This sampling was done using the required questionnaire survey with a total of 1066 data. This research process uses the machine learning classification method. After analyzing the final results of the accuracy of the C4.5 and SVM algorithms, which are then divided into Confusion Matrix, Classification Report, Cross Validation. It was concluded that testing the C4.5 algorithm and the Support Vector Machine algorithm produced the highest model accuracy value, then in evaluating the Classification Report results it was found that the accuracy value of the C4.5 algorithm was 86.91% while the Support Vector Machine algorithm was 87.85%. When using Cross Validation with K-Fold = 5 where the resulting C4.5 algorithm averaged around 86.39% while the Support Vector Machine algorithm averaged around 89.20% accurate. In this study, it was found that the use of the Support Vector Machine algorithm is superior to that of the C4.5 algorithm. Keywords: Algorithm, C4.5, SVM, Handphone Specifications, Classification Handphone sekarang ini sudah menjadi alat komunikasi yang penting dan banyak digemari berbagai kalangan masyarakat, baik anak-anak, remaja maupun orang tua. Oleh karena itu, penelitian tentang pemilihan handphone berdasarkan spesifikasi terbaik menjadi sangat penting. Dalam penelitian ini, metode klasifikasi digunakan untuk membantu pengguna memilih handphone berdasarkan spesifikasi yang dibutuhkan dengan menggunakan metode Algoritma Decision Tree C4.5 dan SVM. Adapun tujuan dari penelitian adalah untuk mengetahui cara implementasi algoritma C4.5 dan SVM menggunakan pemrograman Python dan untuk mengetahui perbandingan kinerja atau performa model yang dihasilkan oleh algoritma C4.5 dan SVM. Adapun variabel yang diteliti adalah timestamp, Nama, Jenis Kelamin, Umur, Domisili, Pekerjaan, First_Know, Stock_Lengkap, First_Imp, First_Spek, Brand, Harga, Kamera_Belakang, Kamera_Depan, Processor, RAM, Battery, Memori_Internal, dan Tergolong. Pengumpulan sampel ini dilakukan dengan menggunakan survey kuesioner yang dibutuhkan dengan total data 1066. Proses penelitian ini menggunakan metode klasifikasi Machine Learning. Setelah dilakukan analisa hasil akhir akurasi dari algoritma C4.5 dan SVM yang kemudian dibagi menjadi Confusion Matrix, Classification Report, Cross Validation. Didapatkan kesimpulan bahwa pengujian Algoritma C4.5 dan Algoritma Suport Vector Machine menghasilkan nilai akurasi model tertinggi, kemudian pada evaluasi hasil Classification Report didapatkan bahwa nilai accuracy pada Algoritma C4.5 adalah 86,91% sedangkan Algoritma Support Vector Machine sebesar 87,85%. Pada penggunaan Cross Validation dengan K-Fold = 5 dimana dihasilkan pada Algoritma C4.5 rata-rata sekitar 86,39% sedangkan Algoritma Support Vector Machine rata-rata sekitar 89,20% akurat. Pada penelitian ini didapatkan hasil bahwa penggunaan Algoritma Support Vector Machine lebih unggul dari pada dibandingkan dengan Algoritma C4.5. Kata Kunci : Algoritma, C4.5, SVM, Spesifikasi Handphone, Klasifikasi
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