Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Jurnal BETA (Biosistem dan Teknik Pertanian) Jurnal Pengabdian Magister Pendidikan IPA
Wahyu Nurkholis Hadi Syahputra
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Education

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Pelatihan Aplikasi Zat Pengatur Tumbuh Paclobutrazol pada Lima Varietas Tanaman Padi di Kecamatan Ledokombo, Kabupaten Jember Tanzil, Ahmad Ilham; Fanata, Wahyu Indra Duwi; Sholikhah, Ummi; Ratnasari, Tri; Sugiharto, Bambang; Nikmah, Nasilatun; Raharja, Ajung Gilang Putra; Asshidiqie, Wahyu Pratama; Ramadhani, Rifki Fahrisal; Muhammad, Adibillah; Ariyono, Alief Rizky; Neliana, Intan Ria; Hari Purnomo; Yusuf Rachmandika; Syafina Pusparani; Wahyu Nurkholis Hadi Syahputra
Jurnal Pengabdian Magister Pendidikan IPA Vol 8 No 1 (2025): Januari-Maret 2025
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpmpi.v7i3.8316

Abstract

Tanaman padi yang menghasilkan beras merupakan komoditas utama di Kecamatan Ledokombo. Kendala yang dihadapi petani dalam budidaya termasuk cekaman abiotik berupa angin kencang pada musim penghujan. Hal ini mengakibatkan tanaman padi lokal dengan postur tinggi rentan mengalami rebah. Untuk mengatasi masalah ini, diperlukan pelatihan terkait penggunaan zat pengatur tumbuh guna mengendalikan pertumbuhan tanaman yang tinggi. Paclobutrazol (PBZ), sebagai salah satu jenis zat pengatur tumbuh, berperan penting dalam mengurangi tinggi tanaman. Pelatihan dilakukan langsung di lahan petani dengan menggunakan lima varietas padi yang berbeda. Hasil aplikasi menunjukkan bahwa padi yang ditanam oleh petani menjadi lebih pendek dibandingkan yang tidak diberi perlakuan serupa.
Deteksi Residu InsektisidaProfenofos pada Cabai Merah (Capsium annumL.)melalui Augmentasi Citra dan CNN (Convolutional Neural Network) Zulfa Hana Maulida; I Putu Gede Budisanjay; I Made Supartha Utama; Chathawan Chaicana; Wahyu Nurkholis Hadi Syahputra
Jurnal BETA (Biosistem dan Teknik Pertanian) Vol 12 No 2 (2024): September
Publisher : Program Studi Teknik Pertanian dan Biosistem, Fakultas Teknologi Pertanian, Universitas Udayana, Badung, Bali, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JBETA.2024.v12.i02.p11

Abstract

The use of i nsecticide in agriculture is rapidly increasing but also faces challenges related to their negative impacts on human health and the environment. One commonly used insecticide is profenofos. Farmers frequently use Profenofo s to control pests on red chili plants in Indonesia. Therefore, detecting profenofos insecticide residue on chili is crucial to ensure the safety of chili consumption. This study aims to develop a new method for detecting profenofos insecticide residues on red chilies (Capsicum Ann um L.) through image augmentation and CNN (Convolutional Neural Network). In this study, insecticide solution preparation, chili image acquisition, testing with GC (Gas Chromatography) Agilent 6890 , image preprocessing, and CNN model implementation were co nducted. Insecticide solution spraying was conducted on 15 chili es with concentrations of 0 and 10 mg/l, followed by smartphone image acquisition, resulting in 30 images . Subsequently, each image was augmented 50 times, resulting in 1530 images. This proce ss involves rotation, shifting, zoom , a nd horizontal and vertical flipping. The CNN model, consisting of convolution layers and fully connected layers, was trained with the Adam optimizer, categorical cross - entropy loss function, the learning rate of 0,000 1, and trained for 20 epochs. The analysis results indicate that the model achieved an accuracy of 85% with precision, recall, and F1 - score values of 0,86 , 0,85, and 0,84, respectively. Based on these results, it can be concluded that the image augmentatio n and CNN method successfully detected profenofos insecticide residues on red chilies at concentrations of 0 and 10 mg/l.
Co-Authors Ahmad Ilham Tanzil Ariyono, Alief Rizky Asshidiqie, Wahyu Pratama Bambang Sugiharto Chathawan Chaicana Fanata, Wahyu Indra Duwi Hari Purnomo I Made Supartha Utama I Putu Gede Budisanjay Muhammad, Adibillah Neliana, Intan Ria Nikmah, Nasilatun Raharja, Ajung Gilang Putra Ramadhani, Rifki Fahrisal Ratnasari, Tri Syafina Pusparani Ummi Sholikhah Yusuf Rachmandika Zulfa Hana Maulida