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All Journal Jurnal Ilmu Komputer dan Informasi Jurnal Simetris TELKOMNIKA (Telecommunication Computing Electronics and Control) Journal of Telematics and Informatics Proceeding of the Electrical Engineering Computer Science and Informatics Kilat Energi & Kelistrikan TEKNOLOGIA JURNAL TEKNIK TERANG : Jurnal Pengabdian Pada Masyarakat Menerangi Negeri Indonesian Community Journal
Herminarto Nugroho
Universitas Pertamina
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences Other

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Deep Learning for Tuning Optical Beamforming Networks Herminarto Nugroho; Wahyu Kunto Wibowo; Aulia Rahma Annisa; Hanny Megawati Rosalinda
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 4: August 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i4.8176

Abstract

In communication between planes and satellites, Optical Beamforming Networks (OBFNs), which rely on many small and flat Phased Array Antennas (PAAs), need to be tuned in order to receive signals from specific angles. In this paper, we develop a deep neural network representation of tuning OBFNs. The problem of tuning an OBFN is in many aspects similar to training a deep neural network. We present a way to exploit the special structure of OBFNs into deep neural network and an algorithm for tuning OBFNs based on feedback that can be easily measured in real system. Training data, which consists of full signals, can be measured, and therefore is used in this paper. For pilot signals, the desired signal is known explicitly. Given the configuration of OBFNs and all nominal parameters required, it was verified in simulation that the deep neural network can be used to tune large scale OBFNs for any desired delays.
Feasibility Study: Online Learning for Supporting Rural Renewable Energy Projects Meredita Susanty; Erwin Setiawan; Ariana Yunita; Herminarto Nugroho
Journal of Telematics and Informatics Vol 7, No 2: JUNE 2019
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jti.v7i2.

Abstract

Indonesian government set the target for new and renewable energy (NRE) is expected to be 23% in 2025 and 31% in 2050, where in 2017, NRE was only 12,5%. Building a new and renewable energy project is the easy part. Keeping the generator working over time, however, is a complex business that requires money, training and innovative thinking. One of essential parameters that can help in achieving a successful sustainable project is community involvement. If the community feels a strong sense of ownership, they'll see their generator as a critical asset to everyone and take good care of it collectively. Training and educating the community about how to take care of the generator after the project construction has completed becomes important. Considering Indonesia’s geographical location, e-learning might be a potential tool to reduce training and education cost in new and renewable project. This study aims to identify whether e-learning is an effective and efficient method to deliver training material and educate local people which will improve renewable energy project’s sustainability in Indonesia.
Fully Convolutional Variational Autoencoder For Feature Extraction Of Fire Detection System Herminarto Nugroho; Meredita Susanty; Ade Irawan; Muhamad Koyimatu; Ariana Yunita
Jurnal Ilmu Komputer dan Informasi Vol 13, No 1 (2020): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information
Publisher : Faculty of Computer Science - Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (579.884 KB) | DOI: 10.21609/jiki.v13i1.761

Abstract

This paper proposes a fully convolutional variational autoencoder (VAE) for features extraction from a large-scale dataset of fire images. The dataset will be used to train the deep learning algorithm to detect fire and smoke. The features extraction is used to tackle the curse of dimensionality, which is the common issue in training deep learning with huge datasets. Features extraction aims to reduce the dimension of the dataset significantly without losing too much essential information. Variational autoencoders (VAEs) are powerfull generative model, which can be used for dimension reduction. VAEs work better than any other methods available for this purpose because they can explore variations on the data in a specific direction.
Robust Principal Component Analysis for Feature Extraction of Fire Detection System Herminarto Nugroho; Muhamad Koyimatu; Ade Irawan; Ariana Yunita
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v5.1716

Abstract

Fire detection system with deep learning-based computer vision (DLCV *) algorithm is proposed in this paper. It uses visible light sensor charged-coupled device (CCD) which can be usually found in closed circuit television camera (CCTV). The performance of this DLCV fire detection depends on how many fire image datasets are trained that might lead to the curse of dimensionality. To tackle the curse of dimensionality, Principal Component Analysis (PCA) will be used. PCA is a technique for feature extraction in which the dimensionality of such datasets is reduced significantly. This will results in increasing interpretability but at the same time minimizing information loss.
Mengoptimalkan Posisi Robot Dalam Sistem Visible Light Communication (VLC) Menggunakan Metode Particle Swarm Optimization (PSO) Jonathansori Panuturan; Panji Rendika; Herminarto Nugroho
JURNAL TEKNOLOGIA Vol 2 No 2 (2020): Jurnal Teknologia
Publisher : Aliansi Perguruan Tinggi Badan Usaha Milik Negara (APERTI BUMN)

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Abstract

Visible Light Communication (VLC) merupakan cara untuk berkomunikasi lewat data seperti mengirim atau menerima sinyal dengan cahaya. Pada penelitian kali ini, dilakukan proses optimasi VLC untuk aplikasi yang menentukan posisi dari robot di permukaan tanah. Robot ini dilengkapi fotodioda pada bagian atas yang berfungsi untuk mengukur kekuatan sinyal yang diterima. Optimasi pada aplikasi dilakukan dengan cara Particle Swarm Optimization (PSO) yang ditujukan untuk radius robot supaya nilai sinyal yang diterima sama atau mendekati dari nilai sinyal yang diterima secara teoritis. Metode PSO dipilih karena memiliki algoritma dan perhitungan yang sangat sederhana untuk mendapatkan tingkat optimasi yang lebih tinggi dibandingkan metode lainnya.
Penggunaan Metode Optimasi Particle Swarm Optimization (PSO) Untuk Menentukan Nilai Fasa Optik Optimum Pada Optical Ring Resonators Anggita Permatasari; Daffi Insan Alif; Herminarto Nugroho
JURNAL TEKNOLOGIA Vol 2 No 2 (2020): Jurnal Teknologia
Publisher : Aliansi Perguruan Tinggi Badan Usaha Milik Negara (APERTI BUMN)

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Abstract

In communication between airplanes and satellite, phased array antennas were needed to receive signals from a specific angle. To satisfy that condition, a controller called Optical Beamforming Network (OBFN) is needed. Process of tuning the OBFN is done by choosing the most suitable parameter as the delay element. Optical Ring Resonators can be used as the delay element. Delay element serves to make the input signal of each PAAs have a same time. This paper will discuss about determination of optical phace optimum value using Particle Swarm Optimization (PSO) method, which has advantages such as fast computing time.
Studi Komparasi Metode Optimisasi Daya Pada Optical Ring Resonator Herminarto Nugroho; Tamarindanara Prillyastraya Astarine; Anggerdini Wahyudi
JURNAL TEKNOLOGIA Vol 2 No 2 (2020): Jurnal Teknologia
Publisher : Aliansi Perguruan Tinggi Badan Usaha Milik Negara (APERTI BUMN)

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Abstract

Optical Ring Resonators (ORRs) can be used as delay elements to form Optical Beamforming Network (OBFN). The ORR function is to ensure that the received signal will have the appropriate delay value so that the signal will be constructive. This study aims to compare the optimization method in obtaining the maximum power value of the magnitude of the phase shift and the optimal power coupling coefficient from the angle (θ) of the signal. The power criterion is based on the fact that the ideal power (desired) will be achieved when all phases of the different signals received by the antenna element are the same. By comparing the Sequential Quadratic Programming (SQP) and Simulated Annealing (SA) methods, the better optimization method can be found to determine the maximum power value of Optical Ring Resonator.
Optimisasi Pengunaan Vissible Light Communication Dengan Melakukan Perubahan Posisi Receiver Redha Arby Mauluddien Nuriman; Herminarto Nugroho; William Fransean Nangka
JURNAL TEKNOLOGIA Vol 2 No 2 (2020): Jurnal Teknologia
Publisher : Aliansi Perguruan Tinggi Badan Usaha Milik Negara (APERTI BUMN)

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Abstract

Abstract— Vissible Light Communication (VLC) is a method of sending and receiving data that has a way of working similar to the light that shines on an object. There are two main components in VLC, namely the transmitter and receiver. The transmitter will emit electromagnetic light which is then received by the receiver. In the application of VLC, the coming angle of the beam emitted by the transmitter will greatly determine the performance performance of the receiver. Therefore it is necessary to optimize the distance position (D) of the receiver in receiving the incoming light. In this optimization process two algorithms will be used, namely genetic algorithm (GA) and particle swarm optimization (PSO). The research method is carried out by simulating the two algorithms using MATLAB. Then the results of the two algorithms are compared to find the most optimal distance value and also with a fast iteration process. In this study, the results obtained by the two algorithms show the same distance and optimization angle values. However, in terms of speed to iterate they have differences. Genetic algorithm requires longer time and iteration compared to particle swarm optimization algorithm. Keywords— VLC, GA, PSO, Optimization. Abstrak— Vissible Light Communication (VLC) adalah sebuah metode pengirimian dan penerimaan data yang memiliki cara kerja mirip seperti cahaya lampu yang menyinari suatu objek. Terdapat dua komponen utama dalam VLC, yaitu transmitter dan receiver. Transmitter akan memancarkan sinar elektromagnetik yang kemudian diterima receiver. Pada aplikasinya sudut datang dari sinar yang dipancarkan transmitter akan sangat menentukan kinerja kinerja receiver. Oleh karena itu perlu dilakukan optimisasi posisi jarak (D) receiver dalam menerima sinar yang datang. Dalam proses optimisasi ini akan digunakan dua algoritma, yaitu genetic algorithm (GA) dan particle swarm optimisation (PSO). Metode penelitian dilakukan dengan melalui proses simulasi kedua algoritma tersebut menggunakan MATLAB. Kemudian hasil kedua algoritma tersebut dibandingkan untuk mencari nilai jarak yang paling optimal dan juga dengan proses iterasi yang cepat. Pada penelitian ini, hasil yang didapatkan oleh kedua algoritma menunjukkan nilai jarak dan sudut optimasi yang sama. Namun, dalam hal kecepatan untuk melakukan iterasi keduanya memiliki perbedaan. Genetic algorithm memerlukan waktu dan iterasi yang lebih lama dibandingkan dengan algoritma particle swarm optimization. Kata kunci— VLC, GA, PSO, Optimisasi.
Penggunaan Metode Particle Swarm Optimization (PSO) Pada Posisi Robot Dalam Sistem Visible Light Communication (VLC) Agung Rachmanto; Annida Sakinah Ramadhani; Herminarto Nugroho
JURNAL TEKNOLOGIA Vol 2 No 2 (2020): Jurnal Teknologia
Publisher : Aliansi Perguruan Tinggi Badan Usaha Milik Negara (APERTI BUMN)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Visible Light Communication (VLC) merupakan suatu sistem komunikasi yang menggunakan cahaya yang dihasilkan oleh LED dan photo-electronic untuk mengirim dan menerima informasi antarperangkat yang terkoneksi sebelumnya. Pada paper ini akan mengoptimalkan VLC sebagai media untuk mengetahui posisi pada robot. Robot tersebut mempunyai photodetector dibagian atas robot tersebut,yang berfungsi untuk menghitung kekuatan sinyal electromagnetic yang diterima. Pengoptimasian dilakukan terhadap radius dari robot, yang bertujuan untuk pendekatan nilai penerimaan sinyal elektromagnetik secara perhitungan dengan menggunakan metode PSO (Particle Swarm Optimization). Visible Light Communication (VLC) merupakan suatu sistem komunikasi yang menggunakan cahaya yang dihasilkan oleh LED dan photo-electronic untuk mengirim dan menerima informasi antarperangkat yang terkoneksi sebelumnya. Pada paper ini akan mengoptimalkan VLC sebagai media untuk mengetahui posisi pada robot. Robot tersebut mempunyai photodetector dibagian atas robot tersebut,yang berfungsi untuk menghitung kekuatan sinyal electromagnetic yang diterima. Pengoptimasian dilakukan terhadap radius dari robot, yang bertujuan untuk pendekatan nilai penerimaan sinyal elektromagnetik secara perhitungan dengan menggunakan metode PSO (Particle Swarm Optimization).
Perbandingan Metode Optimasi Non-Linear Partical Swarm Optimization (PSO) Dengan Metode Interior Point Untuk Optimasi Daya Pada Turbin Angin Dengan Menentukan Nilai Optimum Pitch Angle Alfian Abdi Prasetyo; Fikri Aufa Rafinda; Herminarto Nugroho
KILAT Vol 11 No 1 (2022): KILAT
Publisher : Sekolah Tinggi Teknik - PLN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33322/kilat.v11i1.1324

Abstract

Along with the increasing development of technology, demand for electricity is also increasing. To overcome the problem of reducing electricity raw materials originating from fossil energy, new renewable energi is the solution. One of the new renewable energi sources that have high efficiency values is wind. Wind power plants require wind speed to produce efficiency and output power in the wind turbine. The optimization problem of a wind turbine is to determine the angle of placement of the wind turbine in order to produce the desired optimum power. This journal is determining the wind turbine pitch angle to determine the optimum power by comparing two optimization methods, namely Partical Swarm Optimization (PSO) and the Interior Point optimization method. The data to be obtained is the optimal distance between the turbines and the comparison of the efficiency between the two optimization methods in producing the optimal solution for the problem of placing wind turbines in the wind turbine field. Seiring dengan meningkatnya perkembangan teknologi, kebutuhan listrik juga semakin meningkat. Untuk mengatasi permasalahan berkurangnya bahan baku listrik yang berasal dari energi fosil, maka energi baru terbarukan adalah solusinya. Sumber energi baru terbarukan yang memiliki nilai efisiensi yang tinggi salah satunya adalah angin. Pembangkit listrik tenaga angin membutuhkan kecepatan angin untuk menghasilkan efisiensi dan daya keluaran pada turbin angin tersebut. Permasalahan optimisasi dari suatu turbin angin adalah menentukan sudut peletakan turbin angin agar menghasilkan daya optimum yang diinginkan. Pada jurnal ini bertujuan menentukan pitch angle wind turbine unutk menentukan daya optimum dengan membandingkan dua metode optimasi yaitu Partical Swarm Optimization (PSO) dan metode optimasi Interior Point. Data yang akan diperoleh adalah jarak optimal antar turbin dan perbandingan efisiensi antara kedua metode optimasi tersebut dalam menghasilkan solusi optimal untuk masalah penempatan turbin angin di lapangan turbin angin.
Co-Authors Ade Irawan Ade Irawan Agung Rachmanto Alfian Abdi Prasetyo Anggerdini Wahyudi Anggita Permatasari Annida Sakinah Ramadhani Ariana Yunita Aulia Rahma Annisa Carolus Aditya Daffi Insan Alif Erwin Setiawan Erwin Setiawan Fikri Aufa Rafinda Hanny Megawati Rosalinda Jonathansori Panuturan Marza Ikhsan Marzuki Masayu Setty Rahmadani Muhamad Koyimatu Muhamad Koyimatu Muhammad Muhammad Abdillah Nabilla Ananda Yusva Nita Indriani Pertiwi Ortega Incon Marama Pandiangan Panji Rendika Prayogi, Soni Redha Arby Mauluddien Nuriman Rozan Haqi Pratama Septiyan Nungsizu Susanty, Meredita Tamarindanara Prillyastraya Astarine Tasmi Tasmi Teguh Aryo Nugroho Teuku Muhammad Roffi Wahyu Agung Pramudito Wahyu Kunto Wibowo William Fransean Nangka