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All Journal Aptekmas : Jurnal Pengabdian Kepada Masyarakat Riau Jurnal Teknik Informatika
Ariansyah, Nova
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PENERAPAN DIGITAL MARKETING TERHADAP UMKM SEBAGAI PEMASARAN DALAM MENGHADAPI REVOLUSI Kelly, Angel; Hartati, Ery; Felicia; Ariansyah, Nova; Djunaidi, Sherdian
Aptekmas Jurnal Pengabdian pada Masyarakat Vol 7 No 3 (2024): APTEKMAS Volume 7 Nomor 2 2024
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36257/apts.v7i2.8737

Abstract

Micro, Small and Medium Enterprises (MSMEs) play a vital role in the economy and have great potential for significant growth. However, even though the digital era has penetrated various sectors, there are still many MSMEs that have not taken advantage of the marketing opportunities offered by digital marketing. Data from Kompas.id in 2022 reveals that around 65 million MSMEs have not adopted digital marketing strategies, which is largely due to a lack of technological understanding among business actors. Therefore, this Community Service Activity aims to provide direct training and guidance to MSMEs, such as Lin's Culinary, in utilizing social media such as Instagram and the graphic design tool Canva. It is hoped that through this activity, MSME owners can increase their understanding and skills in utilizing digital platforms for marketing purposes, and can increase the competitiveness and sustainability of their businesses. Keywords: Canva, Digital Marketing, Instagram, MSMEs
Klasifikasi Risiko Diabetes Menggunakan Support Vector Machine Berbasis Feature Selection dan Hyperparameter Tuning Ariansyah, Nova; Harmanto, Dedy
Riau Jurnal Teknik Informatika Vol. 5 No. 1 (2026): Maret 2026
Publisher : Prodi Teknik Informatika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/rjti.v5i1.4301

Abstract

Diabetes Mellitus merupakan penyakit metabolik kronis dengan prevalensi yang terus meningkat secara global. Deteksi dini risiko diabetes menjadi langkah strategis untuk mencegah komplikasi serius seperti penyakit kardiovaskular dan gagal ginjal. Penelitian ini bertujuan mengimplementasikan algoritma Support Vector Machine (SVM) dalam klasifikasi risiko diabetes serta menganalisis pengaruh Feature Selection dan Hyperparameter Tuning  terhadap kinerja model. Dataset yang digunakan berjumlah 100.000 data pasien yang diperoleh dari Kaggle  dengan distribusi kelas yang tidak seimbang antara pasien diabetes dan non-diabetes. Preprocessing dilakukan menggunakan Min-Max Normalization. Seleksi fitur diterapkan menggunakan metode ReliefF dan Mutual Information. Evaluasi model menggunakan 10-Fold Cross Validation untuk meminimalkan bias estimasi performa. Hyperparameter Tuning  dilakukan menggunakan Optuna dengan optimasi parameter C, gamma, dan degree pada kernel Polynomial dan Radial Basis Function. Hasil eksperimen menunjukkan bahwa Hyperparameter Tuning  meningkatkan recall kelas Diabetes dari 0,67 menjadi 0,94 serta meningkatkan akurasi keseluruhan dari 94,76% menjadi 98,90%. Jumlah false negative menurun dari 4.851 menjadi 915 kasus. Temuan ini menunjukkan bahwa optimasi parameter dan seleksi fitur berperan penting dalam meningkatkan sensitivitas model terhadap kelas minoritas pada dataset medis yang tidak seimbang.
Co-Authors Djunaidi, Sherdian FELICIA Harmanto, Dedy Hartati, Ery Kelly, Angel