Putri, Widya Amelia and Dr.Ir. Solimun,, MS. (2022) Penerapan Support Vector Machine Menggunakan Kernel Linier, Polinomial, Dan Radial Basis Function Untuk Klasifikasi Minat Berinvestasi Masyarakat Terhadap Pariwisata Di Wilayah Bali. Sarjana thesis, Universitas Brawijaya.
Abstract
Penelitian ini bertujuan untuk mengetahui tingkat ketepatan klasifikasi minat berinvestasi masyarakat terhadap pariwisata di wilayah Bali menggunakan metode Support Vector Machine dengan kernel linier, polinomial, dan Radial Basis Function (RBF) ditinjau dari nilai akurasi, spesifisitas, dan sensitivitas hasil klasifikasi. Data Daerah diperoleh dari data sekunder hibah Penelitian Dasar Kompetitif Nasional (PDKN) dengan judul “Sistem Pengulikan Potensi Investasi Berbasis Regulasi, SDM, SDA, dan Produk”. Penelitian PDKN tersebut dilakukan pada tahun 2022 sampai 2023. Data yang digunakan dalam penelitian ini adalah data variabel Sumber Daya Alam, Sumber Daya Manusia, dan minat berinvestasi masyarakat di wilayah Bali sebanyak 100 sampel. Data diolah dengan menggunakan analisis Support Vector Machine (SVM) dengan kernel linier, polinomial, dan kernel RBF. Hasil penelitian menunjukkan bahwa kernel polinomial kuadratik memiliki performa yang lebih baik dibandingkan kernel polinomial kubik. Namun, apabila dibandingkan dengan kernel linier dan RBF, kernel RBF memiliki performa yang lebih baik dalam mengklasifikasikan minat berinvestasi masyarakat terhadap sektor pariwisata di wilayah Bali.
English Abstract
This study aims to determine the accuracy of the classification of people's interest in investing in tourism in the Bali region using the Support Vector Machine method with linear, polynomial, and Radial Basis Function (RBF) kernels in terms of the accuracy, specificity, and sensitivity of the classification results. The data were obtained from secondary data from the National Competitive Basic Research (PDKN) grant with the title "Regulation-Based Regional Investment Potential Multiplication System, Human Resources, Natural Resources, and Products". The PDKN research was carried out from 2022 to 2023. The data used in this study is variable data on Natural Resources, Human Resources, and community investment interest in the Bali region as many as 100 samples. Data is processed using Support Vector Machine (SVM) analysis with linear kernels, polynomial kernels, and RBF kernels. The results showed that the quadratic polynomial kernel has better performance than the cubic polynomial kernel. However, when compared to the linear and RBF kernels, the RBF kernel has better performance in classifying people's interest in investing in the tourism sector in the Bali region.
| Item Type: | Thesis (Sarjana) |
|---|---|
| Identification Number: | 052209 |
| Uncontrolled Keywords: | ali, Minat berinvestasi, Pariwisata, Support Vector Machine,Bali, Interest in investing, Support Vector Machine, Tourism. |
| Subjects: | 500 Natural sciences and mathematics > 519 Probabilities and applied mathematics > 519.5 Statistical mathematics |
| Divisions: | Fakultas Matematika dan Ilmu Pengetahuan Alam > Statistika |
| Depositing User: | PKN 03 UB |
| Date Deposited: | 08 Jun 2023 07:26 |
| Last Modified: | 08 Jun 2023 07:26 |
| URI: | http://repository.ub.ac.id/id/eprint/201219 |
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Text (DALAM MASA EMBARGO)
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