Tomasouw, B. P.
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Village Grouping In Southwest Maluku District Based On Poverty Characteristics Using Self Organizing Maps (SOM) Methods Rijoly, Monalisa E.; Lumalessil, F. L.; Tomasouw, B. P.
Zeta - Math Journal Vol 5 No 1 (2020): November
Publisher : Universitas Islam Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31102/zeta.2020.5.1.16-20

Abstract

Poverty is one of the fundamental problems that has become the center of attention of the Maluku Provincial government, especially Southwest Maluku Regency. This study aims to provide information to the government about village grouping based on poverty characteristics in Southwest Maluku Regency using the Self Organizing Map network method. In this network, a layer containing neurons will arrange itself based on the input of a certain value in a group known as a cluster. In the grouping process, 3 results were obtained with the best grouping II results because they had the smallest standard deviation ratio value.
PENERAPAN METODE SUPPORT VECTOR MACHINE (SVM) UNTUK MENDETEKSI PENYALAHGUNAAN NARKOBA Damasela, R; Tomasouw, B. P.; Leleury, Z. A.
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 1 No 2 (2022): Parameter: Jurnal Matematika, Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/parameterv1i2pp111-122

Abstract

Pada penelitian ini, metode Suport Vector Machine (SVM) diterapkan untuk mendeteksi jenis narkotika pada pemakai narkoba berdasarkan gejala-gejala yang dialami. Untuk memperoleh tingkat akurasi terbaik, maka data pelatihan dan pengujian dibagi ke dalam tiga skema pembagian data, yaitu 60/40, 70/30, dan 80/20. Setelah dilakukan proses pelatihan dan pengujian menggunakan metode SVM dengan berbagai variasi parameter, maka diperoleh tingkat akurasi terbaik sebesar 95% pada skema pembagian data 80/20 untuk model SVM non linier dengan kernel RBF.