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All Journal SINTECH (Science and Information Technology) Journal Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat
Ferlian Seftianto
Universitas Sriwijaya
Religion Humanities Computer Science & IT Education Languange, Linguistic, Communication & Media Nursing Public Health Social Sciences

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Deep Learning Berbasis CNN Untuk Pengenalan Pola Partial Discharge Isolasi Silicone Rubber Ferlian Seftianto; Sukemi Sukemi; Zainuddin Nawawi
SINTECH (Science and Information Technology) Journal Vol. 6 No. 2 (2023): SINTECH Journal Edition Agustus 2023
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v6i2.1390

Abstract

Partial discharge (PD) activity measurements have been carried out by selecting noise signals (de-noising) using Support Vector Machine (SVM)and then recognized using Convolutional Neural Network (CNN). CNN testing was carried out using various models such as activation methods: Sigmoid, Softmax, Relu, Tanh, Swish. Number of layers used is 1, 2, 3, 4 with filter sizes of 32, 64, 128, 256  and kernel sizes 3x3, 2x2, 1x1, 1x2,  1x3 in the MaxPooling and AveragePooling pooling methods. The results obtained, On sigmoid method the MaxPooling and AveragePooling with  1 layers  having a low accuracy around 14.40% but the other layers configurations gets a high accuracy around 98.99% both has been done with or without de-noising. In Softmax activation method, MaxPooling pooling method has an accuracy around 84.94% and has de-noising 90.66%. The AveragePooling pooling method has an accuracy 65.25% and around 75.29% with de-noised. The result shows that SVM de-noising increases the accuracy around 11.12% in the Softmax activation method. In the Tanh, Relu, and Swish activation methods, a low level of accuracy is obtained with an average of 14.40%, and SVM de-noising doesn’t increase the accuracy, so CNN-based deep learning with SVM de-noising is more suitable using the Sigmoid and Softmax.
Pelatihan dan Pendampingan Transformasi Digital untuk Penguatan Pemasaran Produk UMKM Melalui Website M Fachrurrozi; Ferlian Seftianto; Andre Hardoni; Habi Baturohmah; Trional Novanza; Redho Aidil Iqrom; Femilia Hardina Caryn; Mgs. M. Luthfi Ramadhan; Rahma Satila Passa
Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Vol. 6 No. 2 (2026): Maret 2026 - Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/altifani.v6i2.1094

Abstract

Banyak UMKM di Sumatera Selatan belum mampu memanfaatkan teknologi digital untuk pemasaran karena rendahnya literasi digital, tidak adanya platform promosi online, serta minimnya pendampingan teknologi. Hal ini membuat jangkauan pasar terbatas dan menghambat peningkatan daya saing. Untuk meningkatkan daya saing UMKM dilakukan pendekatan Participatory Action Approach melalui empat tahap: (1) sosialisasi dan pemetaan kebutuhan (2) pelatihan literasi digital dan pembuatan website (3) pendampingan pengelolaan website (4) evaluasi serta perencanaan keberlanjutan. Kegiatan berlangsung Juli–November 2025 di UMKM Bingkai Kaca Anugrah Jaya, Palembang. Mitra berhasil membuat dan mengelola website https://tokobingkaiplg.com/. Website menampilkan profil usaha, katalog produk, serta integrasi dengan media sosial. Terdapat peningkatan kemampuan literasi digital mitra, peningkatan interaksi pengunjung website rata-rata sekitar 20% dalam dua bulan awal. Program Transformasi digital melalui website ini berhasil meningkatkan jangkauan pemasaran serta memperkuat daya saing produk lokal. Model pelatihan dan pendampingan terbukti efektif dan dapat direplikasi pada UMKM lain.
Co-Authors andre hardoni Femilia Hardina Caryn Habi Baturohmah M Fachrurrozi Mgs. M. Luthfi Ramadhan Rahma Satila Passa Redho Aidil Iqrom Sukemi Sukemi Trional Novanza Zainuddin Nawawi