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All Journal Register: Jurnal Ilmiah Teknologi Sistem Informasi ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika INTEGER: Journal of Information Technology Jurnal Varian Jurnal Aplikasi Dan Inovasi Ipteks SOLIDITAS Jurnal Mnemonic Journal of Electrical Engineering and Computer (JEECOM) Journal of Applied Smart Electrical Network and System (JASENS) JASTEN (Jurnal Aplikasi Sains Teknologi Nasional Magnetika: Jurnal Mahasiswa Teknik Elektro
Irmalia Suryani Faradisa
Teknik Elektro, Institut Teknologi Nasional Malang
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Mathematics Physics Social Sciences Other

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Classification of Betel Leaf Diseases Based on Convolutional Neural Network to Increase Production Herbal Spice Materials Tri Wahyuningrum, Dr. Rima; Hamed Ayani, Irham; Bauravindah, Achmad; Siradjuddin, Indah Agustien; Faradisa, Irmalia Suryani
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 11 No 1 (2025): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v11i1.4653

Abstract

Traditional medicine is the practice of utilizing medicinal plants to treat various illnesses, passed down from generation to generation. In Indonesia, there are various traditional medicines, one of which is using green betel leaves. One part of the green betel plant that is commonly attacked by pests is the leaf. The Convolutional Neural Network (CNN) method is a very common method used for image classification because this method produces the highest accuracy in classification and pattern recognition. This research uses data totaling 4000 images which are divided into four classes: healthy green betel leaves, anthracnose green betel leaves, bacterial spot betel leaves, and healthy red betel leaves. Detecting the disease type facilitates farmers in acknowledging the necessary measures required to provide treatment. Therefore, this study utilizes the benefits of the CNN approach, specifically its capability to conduct precise object detection and classification in image data, to minimize the widespread of disease. The CNN architectures implemented are DenseNet201, EfficientNetB3V2, InceptionResNetV2, MobileNetV2 and XceptionResnet50V2. Based on our research, the InceptionResNetV2 model achieved the highest performance with an accuracy of 86.0%, loss of 0.3880, and ROC of 98.0%. In the other hand, the MobileNetV2 and EfficientNetV2B3 models suffered from overfitting and underfitting and the models failed to classify betel leaf diseases.
Analisa Ekonomi PLTS Off-Grid Dengan Teknologi Pumped Storage Di Mahakam Ulu Rifqi Fajriyansyah; Irmalia Suryani Faradisa
Journal of Applied Smart Electrical Network and Systems Vol. 6 No. 2 (2025): Vol. 6 No. 02 (2025): Vol 06, No. 02 Desember 2025
Publisher : Indonesian Society of Applied Science (ISAS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/7cp9b247

Abstract

Indonesia continues to face challenges in providing reliable and sustainable electricity, particularly in remote areas that are not yet connected to the main power grid. To support the transition toward clean energy, this study conducts a financial feasibility analysis for the planned development of an Off-Grid Solar Power Plant (PLTS) with Pumped Storage technology located in Batu Dinding, Ujoh Bilang, Long Bagun District, Mahakam Ulu Regency, East Kalimantan. The objective of this research is to evaluate the project’s economic feasibility using financial analysis methods, including calculations of Net Present Value (NPV), Internal Rate of Return (IRR), and Benefit-Cost Ratio (BCR). The study assumes a project lifetime of 50 years with a total investment cost of IDR 99,475,000,000, funded through a government grant. The analysis results show a positive NPV, an IRR of 11.2%, and a BCR of 2.60, indicating that the project is financially viable and profitable. Furthermore, the sensitivity analysis with variations in discount rates (3%–10%) and investment cost increases up to 8% demonstrates that the project remains stable and feasible under different economic conditions. Therefore, the development of the Off-Grid PLTS with Pumped Storage system can serve as a sustainable and clean energy solution for electricity supply in remote regions of Indonesia.
Co-Authors 1Mohamad Cholil Achmad Sahrul Afandi Agung Darmawan Ahmad Dony Mutiara Bahtiar Alfarid Hendro Yuwono Aryuanto Soetedjo Basuki Widodo Bauravindah, Achmad Bima Romadhon Parada Dian Palevi Budi Fathony DAMARDHI, SAHI RAFAEL Dyah Ayu Girindraswari Eko Yohanes Setyawan F. Yudi Limpraptono Febriana Santi W Febriana Santi Wahyuni Hamed Ayani, Irham I Komang Somawirata kukuh prayoga pangestu prastiyawan M. Ibrahim Ashari M. Imron Khoirus Saleh Mohammad Ibrahim Ashari Muljanto, Widodo Pudji Nicola Natha Teopilus Ginting Parama Diptya Widayaka Pradana, Yuditya Adi Pranata, Sandio Dwi Radimas Putra M. D. L. Radimas Putra Muhammad Davi Labib Rifqi Fajriyansyah Rizqi Cahyo Muflih Putra - Roichan Nafis Sandy Dwi Kurniawan Setiawan, Katon Bagus Siradjuddin, Indah Agustien Sirojul Hadi Sotyohadi Tri Wahyuningrum, Dr. Rima Yogi Nugraha Aditama Yoppy Aldya