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All Journal Prosiding Semnastek TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi, Kendali, Komputer, Elektrik, dan Elektronika JMECS (Journal of Measurements, Electronics, Communications, and Systems) Jurnal Nasional Teknik Elektro dan Teknologi Informasi SinarFe7 EPSILON: Journal of Electrical Engineering and Information Technology eProceedings of Engineering Jurnal INFOTEL
Edwar
Universitas Telkom
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology

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Journal : Jurnal INFOTEL

 1 
Analisis Pengaturan Sistem Catu Daya Pada Satelit Nano Fasny F. A Rafsanzani; Budi Syihabuddin; Edwar Edwar; Heroe Wijanto
JURNAL INFOTEL Vol 9 No 3 (2017): August 2017
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v9i3.261

Abstract

Keberhasilan suatu misi satelit nano sangat bergantung kepada keandalan Electrical Power System (EPS) untuk menjaga subsistem-subsistem pada satelit nano agar tetap berfungsi. Oleh karena itu dibutuhkan sebuah pengendalian distribusi daya yang efektif. Penelitian ini menjelaskan tentang bagaimana cara pendistribusian daya listrik yang efektif dan sesuai dengan kondisi satelit nano ketika terkena sinar matahari atau ketika kondisi gelap pada saat mengorbit diluar angkasa. Untuk menjelaskan hal tersebut dilakukan simulasi dan analisis pada perancangan modul power management EPS yang terdiri dari rangkaian boost converter LT3757 dan battery charger IC LT3652. Hasil simulasi menunjukan bahwa pada saat kondisi terang sistem akan mencatu daya beban menggunakan daya masukan panel surya yang sebelumnya telah melewati komponen boost converter (12 Volt), sekaligus mengisi daya batere hingga terisi penuh (7,4 Volt). Tetapi pada saat kondisi gelap sistem akan mencatu beban dengan daya yang dihasilkan oleh batere (7,4 Volt).
Early Detection of Deforestation through Satellite Land Geospatial Images based on CNN Architecture Nor Kumalasari Caecar Pratiwi; Yunendah Nur Fu'adah; Edwar Edwar
JURNAL INFOTEL Vol 13 No 2 (2021): May 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v13i2.642

Abstract

This study has developed a CNN model applied to classify the eight classes of land cover through satellite images. Early detection of deforestation has become one of the study’s objectives. Deforestation is the process of reducing natural forests for logging or converting forest land to non-forest land. The study considered two training models, a simple four hidden layer CNN compare with Alexnet architecture. The training variables such as input size, epoch, batch size, and learning rate were also investigated in this research. The Alexnet architecture produces validation accuracy over 100 epochs of 90.23% with a loss of 0.56. The best performance of the validation process with four hidden layers CNN got 95.2% accuracy and a loss of 0.17. This performance is achieved when the four hidden layer model is designed with an input size of 64 × 64, epoch 100, batch size 32, and learning rate of 0.001. It is expected that this land cover identification system can assist relevant authorities in the early detection of deforestation.
Vegetation classification algorithm using convolutional neural network ResNet50 for vegetation mapping in Bandung district area Rina Pudji Astuti; Ema Rachmawati; Edwar Edwar; Simon Siregar; Indra Lukmana Sardi; Arfianto Fahmi; Yayan Agustian; Agus Cahya Ananda Yoga Putra; Faishal Daffa
JURNAL INFOTEL Vol 14 No 2 (2022): May 2022
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v14i2.756

Abstract

Bandung District is one of crop provider for West Java Province. About 31.158,22 ha is used for crop. However, some of them are not maintained well due to lack of vegetation map information. Local authority has tried to map the vegetation in their area by using free license satellite images, and aerial images from Unmanned Aerial Vehicle (UAV). Despite both images being able to provide large plantation area images, both are unable to classify the vegetation type in those images. Telkom University with Bandung Agriculture Regional Office (Dinas Pertanian Kabupaten Bandung) has conducted joint research to develop algorithm based on 50-layer residual neural network (ResNet50) to classify the vegetation type. The input is of this algorithm is primarily aerial images are captured from different type, height, and position of crops. Seven different ResNet50 configurations have been set and simulated to classify the crop images. The result is the configuration with resized images, employing triangular policy of cyclic learning rate with rate 1.10−7 – 1.10−4 comes out as the best setup with more than 95% accuracy and relatively low loss.
Co-Authors Achmad Ali Muayyadi Agus Cahya Ananda Yoga Putra Agus Dwi Prasetyo Agus Prasetyo Ali Muayyadi Ali, Erfansyah Aloysius Adya Pramudita Analisa Nadhira Lestari Aqil Aztris Arfianto Fahmi Astenio Fahreza Dwiyuda Auzano Rabyndra Zhafiri Bambang Setia Nugroho Bambang Sumajudin Budi Syihabuddin Daniel Wardhana Dharu Arseno Dharu Dharu DHONI PUTRA SETIAWAN Dhoni Putra Srtiawan Dwi Desmelliana Dzulfikar Natya Afif Hakim Edward Natanael Ema Rachmawati Evan Benedick Nathaniel Fachrul Reiza Medina Faishal Daffa Fajar Gunawan Farhan Awwaliy Maulana Muhammad Farhan Maulana Akmal Fasny F. A Rafsanzani Gandaria Gandaria Harfan Hian Ryanu Heroe Wijanto Ig. Prasetya Dwi Wibawa Ihsan Nuur Razzak Hantriono Ikhwan Muzzaki Indra Lukmana Sardi Izzan Radhi Mafazi Lazuardi Rea Rizkina Levy Olivia Nur Lita Kurnia Fitriyanti M. Bayu Oktodwilavito M.R. Yusron Maryam Namira Miftahul Firdaus Muhammad Elsandrie Rakatama Muhammad Rustiyarso Nor Kumalasari Caecar Pratiwi Pasha Dani Pamungkas Porman Pangaribuan Primadita Banu Anggra R. Yunendah Nur Fu’adah Rina Pudji Astuti Sakti Oktawianto Sania Uswah Nafisah Satrio Yudo Prawiro Simon Siregar Siska Julita Andri Sitha Vrindhavani Devi Putri Sugito Sugito Wahyu Fadhilah Windi Andaresta Nurul Hakim Yayan Agustian Zilliah Mankusa Zilliah