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All Journal Techne : Jurnal Ilmiah Elektroteknika Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat
Office, Irfan Handy
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Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Law, Crime, Criminology & Criminal Justice Nursing

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Penerapan Pembangkit Listrik Tenaga Surya pada Aerator Budidaya Ikan Lele Setiawan, Aries Boedi; Riza, Muchammad Riza; Rozaq, Abdul; Alfayid, Aziz; Office, Irfan Handy
Abdimas Galuh Vol 6, No 2 (2024): September 2024
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/ag.v6i2.14962

Abstract

Kelurahan Dinoyo merupakan salah satu kelurahan yang terletak di Kota Malang, Jawa Timur, Indonesia. Kelurahan ini terletak di Kecamatan Lowokwaru, salah satu dari 11 kecamatan yang ada di Kota Malang. Di Kelurahan Dinoyo terdapat Kelompok PKK yang aktif pada pengembangan budidaya ikan dalam ember dan dalam kolam terpal bundar. Permasalahan yang dihadapi mitra antara lain; Pertama, pemanfaatan teknologi untuk budidaya ikan lele. Mitra yang yang sudah mencoba membudidayakan lele belum dilakukan secara optimal, masih sebatas budidaya dalam ember dengan lokasi budidaya tersebar di beberapa anggota mitra. Kedua, pengembangan obyek fisik; Tidak adanya fasilitas umum (fasum) aliran listrik PLN di lokasi kolam ikan lele. Hasil kegiatan pengabdian masyarakat yang telah dilakukan antara lain: (1) Memasang Pembangkit Listrik Tenaga Surya (PLTS) sebagai sumber energi listrik mandiri untuk aerator udara yang tidak bergantung pada pasokan listrik PLN, serta memberikan pelatihan operasional PLTS. (2) Memberikan edukasi (seminar) terkait peningkatan ekonomi kreatif di bidang budidaya ikan lele.
Klasifikasi Penyakit Pneumonia menggunakan Metode Convolutional Neural Network (CNN) Office, Irfan Handy; Arifuddin, Rahman; Hidayatulail, Basitha Febrinda
Techné : Jurnal Ilmiah Elektroteknika Vol. 23 No. 2 (2024)
Publisher : Fakultas Teknik Elektronika dan Komputer Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31358/techne.v23i2.491

Abstract

Pneumonia is an acute lung infection that affects lung tissue. The disease can be caused by various pathogens such as viruses, bacteria, fungi, and others. COVID-19 pneumonia is a serious condition that requires special attention because of its contagious nature and its severe symptoms, including high fever, difficulty breathing, and lack of oxygen. Diagnosis usually depends on clinical symptoms and imaging techniques such as chest x-rays. With automatic classification technology, pneumonia detection becomes more efficient. The study used Convolutional Neural Network (CNN) with ResNet50 architecture to classify types of pneumonia, including viral pneumony and COVID-19, from chest x-rays. Research methods include literature reviews, data collection, pre-processing, modeling, training, testing, and evaluation using metrics such as accuracy, precision, recall, and F1 scores. Experiments with different epochs yield 99% accurate training data, 81% accurate validation data, and a lack of learning on models that influence accurability on validation.
Co-Authors Abdul Rozaq Alfayid, Aziz Aries Boedi Setiawan Arifuddin, Rahman Hidayatulail, Basitha Febrinda Riza, Muchammad Riza