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All Journal JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat) International Journal of Economics, Management and Accounting
Bahriddin Abapihi
Universitas Halu Oleo
Civil Engineering, Building, Construction & Architecture Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Public Health Social Sciences

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Edukasi Masyarakat Desa Kafoofoo di Kabupaten Muna Tentang Pencegahan Covid-19 Ida Usman; Mukhsar Mukhsar; Bahriddin Abapihi; Asrul Sani; Wa Ode Sunaria; Baharuddin Said
JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat) VOL. 5 NOMOR 1 MARET 2021 JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat)
Publisher : Lembaga Publikasi Ilmiah dan Penerbitan (LPIP)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (218.425 KB) | DOI: 10.30595/jppm.v5i1.8782

Abstract

COVID-19 adalah penyakit menular yang dapat menginfeksi banyak orang apabila tidak menerapkan protokol kesehatan yang ditetapkan oleh pemerintah. Penyakit ini telah menyebar dengan cepat ke berbagai daerah termasuk ke desa-desa. Kegiatan pengabdian ini bertujuan mengedukasi masyarakat Desa Kafoofoo Kabupaten Muna dalam pencegahan penyebaran COVID-19. Tahapan pengabdian meliputi: pembekalan tim pelaksana, koordinasi dengan aparat desa, pengukuran tingkat pengetahuan masyarakat, dan edukasi pencegahan penyebaran COVID-19 melalui poster, alat peraga, dan penyuluhan kepada perwakilan warga. Hasil kegiatan edukasi menunjukkan bahwa tingkat pengetahuan masyarakat terhadap COVID-19 telah meningkat, yang ditandai dengan meningkatnya penggunaan masker di luar rumah.
Support Vector Machine: Classification of Trade Balance of Provincies in Indonesia Based on Gross Regional Domestic Product and Large Trade Price Index in 2023 Rati Assyifa Putri; Bahriddin Abapihi; Dian Christien Arisona
International Journal of Economics, Management and Accounting Vol. 1 No. 2 (2024): June : International Journal of Economics, Management and Accounting
Publisher : Asosiasi Riset Ekonomi dan Akuntansi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/ijema.v1i2.68

Abstract

The aim of this research is to classify Indonesia's trade balance data using the SVM (Support Vector Machine) method with two features, namely Gross Regional Domestic Product (X1) and Wholesale Price Index (X2). Classification is carried out by comparing two types of kernels, namely polynomial kernels and RBF (Radial Basis Function) kernels. Equality Hyperplaneobtained from the polynomial kernel is: . The Hyperplane equation obtained from the RBF kernel is: Experimental results show that classification with polynomial kernels provides better performance than RBF kernels. This can be seen in the evaluation results which show that the Polynomial kernel has an average model goodness of 75.93% and for the RBF kernel the average model goodness is 74.07%. Leave One Out cross validation (LOOCV) simulation for training data obtained an average accuracy of 76.67% for the polynomial kernel and 66.67% for the RBF kernel. This shows that in this classification context, kernel polynomials are more effective in separating data classes.
Co-Authors Asrul Sani Baharuddin Said Dian Christien Arisona Ida Usman Mukhsar . Rati Assyifa Putri Wa Ode Sunaria