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All Journal Indonesian Journal of Tropical and Infectious Disease Abdimas Galuh : Jurnal Pengabdian Kepada Masyarakat
Adri Supardi, Adri
Physics Study Program, Faculty of Science and Technology, Universitas Airlangga, Surabaya
Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences Economics, Econometrics & Finance Health Professions Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health

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HEART ABNORMALITY CLASSIFICATIONS USING FOURIER TRANSFORMS METHOD AND NEURAL NETWORKS Purwanti, Endah; Nastiti, Amadea Kurnia; Supardi, Adri
Indonesian Journal of Tropical and Infectious Disease Vol 5, No 2 (2014)
Publisher : Institute of Topical Disease

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Abstract

Health problems with cardiovascular system disorder are still ranked high globally. One way to detect abnormalities in the cardiovascular system especially in the heart is through the electrocardiogram (ECG) reading. However, reading ECG recording needs experience and expertise, software-based neural networks has designed to help identify any abnormalities of the heart through electrocardiogram digital image. This image is processed using image processing methods to obtain ordinate chart which representing the heart’s electrical potential. Feature extraction using Fourier transforms which are divided into several numbers of coefficients. As the software input, Fourier transforms coefficient have been normalized. Output of this software is divided into three classes, namely heart with atrial fibrillation, coronary heart disease and normal. Maximum accuracy rate of this software is 95.45%, with the distribution of the Fourier transform coefficients 1/8 and number of nodes 5, while minimum accuracy rate of this software at least 68.18% by distribution of the Fourier transform coefficients 1/32 and the number of nodes 32. Overall result accuracy rate of this software has an average of 86.05% and standard deviation of 7.82.
HEART ABNORMALITY CLASSIFICATIONS USING FOURIER TRANSFORMS METHOD AND NEURAL NETWORKS Purwanti, Endah; Nastiti, Amadea Kurnia; Supardi, Adri
Indonesian Journal of Tropical and Infectious Disease Vol. 5 No. 2 (2014)
Publisher : Institute of Topical Disease Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (463.116 KB) | DOI: 10.20473/ijtid.v5i2.223

Abstract

Health problems with cardiovascular system disorder are still ranked high globally. One way to detect abnormalities in the cardiovascular system especially in the heart is through the electrocardiogram (ECG) reading. However, reading ECG recording needs experience and expertise, software-based neural networks has designed to help identify any abnormalities of the heart through electrocardiogram digital image. This image is processed using image processing methods to obtain ordinate chart which representing the heart's electrical potential. Feature extraction using Fourier transforms which are divided into several numbers of coefficients. As the software input, Fourier transforms coefficient have been normalized. Output of this software is divided into three classes, namely heart with atrial fibrillation, coronary heart disease and normal. Maximum accuracy rate of this software is 95.45%, with the distribution of the Fourier transform coefficients 1/8 and number of nodes 5, while minimum accuracy rate of this software at least 68.18% by distribution of the Fourier transform coefficients 1/32 and the number of nodes 32. Overall result accuracy rate of this software has an average of 86.05% and standard deviation of 7.82.
Pembuatan Pupuk Organik dengan Memperkecil Ukuran Bahan Baku Sebagai Upaya Mandiri Pupuk Di Desa Bulus, Bandung Tulungagung Siswanto, Siswanto; Hikmawati, Dyah; Aminatun, Aminatun; Djony Izak, Djony Izak; Ady, Jan; Ukhrowiyah, Nuril; Sapuan, Imam; Arifianto, Deny; Supardi, Adri; Rochman, Mochammad Nurur
Abdimas Galuh Vol 7, No 1 (2025): Maret 2025
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/ag.v7i1.17061

Abstract

Kelangkaan pupuk bersubsidi telah menjadi permasalahan bagi petani di seluruh Indonesia, termasuk di Desa Bulus, Bandung, Tulungagung. Terjadi ketidakseimbangan antara pasokan dan permintaan, yang berdampak pada produktivitas pertanian. Penggunaan pupuk urea yang berlebihan dapat merusak kesuburan tanah dan berkontribusi terhadap pencemaran lingkungan. Pupuk organik menjadi solusi alternatif bagi lingkungan dan kesehatan tanah jangka panjang. Selain itu dapat meningkatkan retensi air, dan keberagaman mikroba, sehingga mengurangi ketergantungan pada pupuk kimia. Salah satu metode yang menjanjikan untuk produksi pupuk organik adalah komposting, khususnya metode Takakura, yang menggunakan fermentasi terkontrol dari bahan organik. Selain itu, pengurangan ukuran sampah organik melalui perajangan dapat mempercepat proses dekomposisi, meningkatkan efisiensi dan kualitas kompos. Program pengabdian masyarakat di Desa Bulus ini bertujuan untuk mengedukasi petani tentang produksi pupuk organik yang efisien, menggunakan metode Takakura, tong komposter, dan pupuk cair organik. Pelatihan ini melibatkan 30 petani dan berfokus pada peningkatan efisiensi produksi pupuk melalui perajangan sampah organik. Evaluasi pasca-pelatihan menunjukkan peningkatan yang signifikan dalam pengetahuan dan keterampilan peserta, dengan rata-rata nilai meningkat sebesar 25-30 poin. Penggunaan bahan organik yang dipotong kecil-kecil mengurangi waktu pengomposan dan meningkatkan kualitas pupuk. Evaluasi program menunjukkan kepuasan yang tinggi di kalangan peserta, terutama terkait relevansi dan penerapan praktis materi yang disampaikan. Hasil ini menunjukkan bahwa produksi pupuk organik, bersama dengan teknik pengolahan sampah yang efisien, dapat mendukung pertanian yang berkelanjutan di komunitas pedesaan yang menghadapi kelangkaan pupuk.
Co-Authors Amadea Kurnia Nastiti, Amadea Kurnia Aminatun Aminatun Arifianto, Deny Djony Izak, Djony Izak Endah Purwanti Imam Sapuan Jan Ady Nuril Ukhrowiyah Rochman, Mochammad Nurur S Siswanto Solly Aryza