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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) Al-Fiziya: Journal of Materials Science, Geophysics, Instrumentation and Theoretical Physics Jurnal Ilmiah Aplikasi Isotop Radiasi Journal of Degraded and Mining Lands Management Jurnal Keteknikan Pertanian Tropis dan Biosistem Journal of Engineering and Technological Sciences ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Jurnal Penelitian Pendidikan IPA (JPPIPA) Spektra: Jurnal Fisika dan Aplikasinya FaST : Jurnal Sains dan Teknologi International Journal of Remote Sensing and Earth Sciences (IJReSES) Jurnal Instrumentasi Formosa Journal of Sustainable Research (FJSR) PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) Journal of Sciencce Technology and Visual Culture Indonesian Journal of Aerospace
Sastra Kusuma Wijaya
Departemen Fisika Universitas Indonesia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Physics Social Sciences Other

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Design Virtual Instrumentation System of a Cigarette Smoke Detector Sabar; Joni; Kisna Pertiwi; Ratih Rundri Utami; Sastra Kusuma Wijaya
Formosa Journal of Sustainable Research Vol. 2 No. 3 (2022): March 2023
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/fjsr.v2i3.3502

Abstract

The contributor to air pollution today is cigarette smoke because almost every public facility is provided with a special room for smokers and a non-smoking room. However, the level of awareness of active smokers is not only harmful to themselves but also to secondhand smoke, especially in smoke-free environments. Along with the development of technology, we can take advantage of the development of a cigarette smoke detector based on the Arduino with the MQ-2 gas sensor. Therefore, this tool will make it easier to monitor a crowded room for cigarette smoke. The system uses the MQ-2 gas sensor to detect cigarette smoke in a room. By using a buzzer alarm as a sign that there is cigarette smoke inside a room. The ppm value obtained from the sensor is 550 ppm on the cigarette sensor to detect cigarette smoke
Rapid Flood Mapping Using Statistical Sampling Threshold Based on Sentinel-1 Imagery in the Barito Watershed, South Kalimantan Province, Indonesia Muhammad Priyatna; Muhammad Rokhis Khomarudin; Sastra Kusuma Wijaya; Fajar Yulianto; Gatot Nugroho; Pingkan Mayestika Afgatiani; Anisa Rarasati; Muhammad Arfin Hussein
Journal of Engineering and Technological Sciences Vol. 55 No. 1 (2023)
Publisher : Directorate for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.eng.technol.sci.2023.55.1.10

Abstract

Flood disasters occur frequently in Indonesia and can cause property damage and even death. This research aimed to provide rapid flood mapping based on remote sensing data by using a cloud platform. In this study, the Google Earth Engine cloud platform was used to quickly detect major floods in the Barito watershed in South Kalimantan province, Indonesia. The data used in this study were Sentinel-1 images before and after the flood event, and surface reflectance of Sentinel-2 images available on the Google Earth Engine platform. Flooding is detected using the threshold method. In this study, we determined the threshold using the Otsu method and statistical sampling thresholds (SST). Four SST scenarios were used in this study, combining the mean and standard deviation of the difference backscatter of Sentinel-1 images. The results of this study showed that the second SST scenario could classify floods with the highest accuracy of 73.2%. The inundation area determined by this method was 4,504.33 km2. The first, third and fourth SST scenarios and the Otsu method could reduce the flood load with an overall accuracy of 48.37%, 43.79%, 55.5% and 68.63%, respectively. The SST scenario is considered to be a reasonably good method for rapid flood detection using Sentinel-1 satellite imagery. This rapid detection method can be applied to other areas to detect flooding. This information can be quickly produced to help stakeholders determine appropriate flood management strategies.
SPECTRAL CHARACTERISTICS OF FLASH FLOOD AREAS FROM MEDIUM SPATIAL OPTICAL IMAGERY Priyatna, Muhammad; Khomarudin, Muhammad Rokhis; Chulafak, Galdita Aruba; Wijaya, Sastra Kusuma
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 18, No 2 (2021)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2021.v18.a3666

Abstract

This study aims to investigate surface reflectance changes over flash flood areas in Nusa Tenggara Timur, Indonesia. Fifteen sample points from Sentinel-2 satellite imagery were used to analyse the differences in reflectance of areas before and after flash flood events. The method used involved analysis of the significant differences in the dreflectance values of each Sentinel-2 channel. The analysis results show that channels 6, 7, and 8A displayed significant differences compared to the others with regard to reflectance before and after flooding, for both settlements and shrubs. The results could be used for further research in building a reflectance index for the rapid detection of affected areas, with a focus on these channels.
Runner profile optimisation of gravitational vortex water turbine Ridwan Arief Subekti; Sastra Kusuma Wijaya; Arief Sudarmaji; Tinton Dwi Atmaja; Budi Prawara; Anjar Susatyo; Ahmad Fudholi
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i5.pp4777-4788

Abstract

This study discusses the numerical optimisation and performance testing of the turbine runner profile for the designed gravitational water vortex turbine. The initial design of the turbine runner is optimised using a surface vorticity algorithm coded in MATLAB to obtain the optimal stagger angle. Design validation is carried out using computational fluid dynamics (CFD) Ansys CFX to determine the performance of the turbine runner with the turbulent shear stress transport model. The CFD analysis shows that by optimising the design, the water turbine efficiency increases by about 2.6%. The prototype of the vortex turbine runner is made using a 3D printing machine with resin material. It is later tested in a laboratory-scale experiment that measures the shaft power, shaft torque and turbine efficiency in correspondence with rotational speeds varying from 150 to 650 rpm. Experiment results validate that the optimised runner has an efficiency of 45.3% or about 14% greater than the initial design runner, which has an efficiency of 39.7%.
Water Level Detection System based on Arduino and LabVIEW for Flood Monitors using Virtual Instrumentation Sabar Sabar; Dewi Maulidah Nur Anjani; Sastra Kusuma Wijaya
Al-Fiziya: Journal of Materials Science, Geophysics, Instrumentation and Theoretical Physics Al-Fiziya: Journal of Materials Science, Geophysics, Instrumentation and Theoretical Physics | Vol.4
Publisher : Physics Study Programme, Faculty of Science and Technology UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/fiziya.v4i1.19808

Abstract

This virtual instrumentation system based on Arduino and LabVIEW aims to detect the water level using a water level sensor. The water level sensor used to measure the water level is the Funduino type. This sensor and the buzzer module are connected to the Arduino Uno to transmit data to LabVIEW. When the water has reached a certain height, this sensor will detect the water level. When the water has reached the set point, this sensor will sound a buzzer as a sign that the water is full. Based on the experimental results, it is found that the tension value affects the volume of the experiment site. Where the greater the volume used will produce a large voltage, and vice versa. Furthermore, the graph results obtained that are still away from the linearity of a regression function with a value of y = 0.0079x + 1.8561 and R² = 0.4298.
Convolutional Neural Network for Earthquake Ground Motion Prediction Model in Earthquake Early Warning System in West Java Melki Adi Kurniawan; Sastra Kusuma Wijaya; Nuraini Rahma Hanifa
Jurnal Penelitian Pendidikan IPA Vol. 9 No. 11 (2023): November
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v9i11.3514

Abstract

As urbanization continues, more people and infrastructure are concentrated in areas that are at risk from earthquakes. This can increase the potential damage and loss of life when earthquakes occur. Indonesia is a region that is near the boundary of three major tectonic plates which has a very high frequency of earthquake occurrences. Over the past two decades, a new approach to earthquake disaster risk mitigation has emerged. It is based on the advent of digital seismology and advances in data transmission and automatic processing that make it possible to send warnings before the largest ground motion that called the Earthquake Early Warning System (EEW). On-site EEW is a type of EEW that consists of limited seismic stations located at a specific destination/infrastructure (for early detection systems). On-site EEW estimates ground motion parameters directly from the characteristics of seismograms recorded by the system. An artificial intelligence approach to EEW is necessary to increase the speed and accuracy of information, which increases processing time, especially in areas very close to the epicenter
Convolutional Neural Network for Earthquake Ground Motion Prediction Model in Earthquake Early Warning System in West Java Melki Adi Kurniawan; Sastra Kusuma Wijaya; Nuraini Rahma Hanifa
Jurnal Penelitian Pendidikan IPA Vol 9 No 11 (2023): November
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v9i11.3514

Abstract

As urbanization continues, more people and infrastructure are concentrated in areas that are at risk from earthquakes. This can increase the potential damage and loss of life when earthquakes occur. Indonesia is a region that is near the boundary of three major tectonic plates which has a very high frequency of earthquake occurrences. Over the past two decades, a new approach to earthquake disaster risk mitigation has emerged. It is based on the advent of digital seismology and advances in data transmission and automatic processing that make it possible to send warnings before the largest ground motion that called the Earthquake Early Warning System (EEW). On-site EEW is a type of EEW that consists of limited seismic stations located at a specific destination/infrastructure (for early detection systems). On-site EEW estimates ground motion parameters directly from the characteristics of seismograms recorded by the system. An artificial intelligence approach to EEW is necessary to increase the speed and accuracy of information, which increases processing time, especially in areas very close to the epicenter
Pengaruh Suhu Pada Pengukuran Jarak Menggunakan Sensor Ultrasonik SR04/05 Berbasis Instrumentasi Maya Sabar Sabar; Duwi Hariyanto; Kisna Pertiwi; Handoyo Handoyo; Sastra Kusuma Wijaya; Zunanik Mufidah; Fajar Paundra; Muhammad Syaukani
Journal of Science, Technology, and Visual Culture Vol 1 No 1 (2021): Juli 2021
Publisher : Jurusan Teknologi Produksi dan Industri, Institut Teknologi Sumatera

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

Abstract

Penelitian ini menjelaskan tentang bagaimana pengaruh suhu pada perambatan gelombang ultrasonik di udara. Hal ini berkaitan dengan verifikasi keakuratan jarak pengukuran sensor ultrasonic sebagai alat ukur. Sensor yang digunakan dalam instrumentasi maya berupa sensor ultrasonik SR 05/04 sebagai sensor pengukur jarak dan sensor suhu LM35 digunakan sebagai acuan untuk mengukur suhu lingkungan. Tujuan penelitian ini adalah memverifikasi apakah kecepatan gelombang utrasonik di udara berpengaruh terhadap perubahan suhu serta mempengaruhi pengukuran jarak. Pada penelitian ini didapatkan hasil rata-rata nilai simpangan standar deviasi pengukuran jarak terkoreksi suhu adalah 0,114 sedangkan pengukuran jarak tanpa terkoreksi suhu adalah 0,1075. Hal ini menunjukan bahwa kenaikan perubahan suhu walaupun 1°C dapat mempengaruhi sensor ultrasonik dalam mengukur jarak. Secara umum instrumentasi maya mampu bekerja dan membaca besaran sensor-sensor serta melakukan perhitungan dan menampilkan data dengan sangat baik.
Prediksi Banjir menggunakan ANFIS-PCA sebagai Peringatan Dini Bencana Banjir RACHMAWARDANI, AGUSTINA; WIJAYA, SASTRA KUSUMA; PRAWITO, PRAWITO; SOPAHELUWAKAN, ARSHASENA
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 12, No 2: Published April 2024
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v12i2.335

Abstract

ABSTRAKDi antara kejadian bencana yang terjadi di Indonesia, 76 persen terdiri dari bencana hidrometeorologi seperti banjir, badai, longsor, dan kebakaran hutan. Provinsi DKI Jakarta sebagai daerah perkotaan sangat rentan terhadap banjir. Persamaan matematis yang kompleks dapat digunakan untuk memodelkan kejadian banjir secara fisik. Sistem pembelajar (machine learning) adalah sistem yang merancang dan mengembangkan algoritma yang menggunakan data historis untuk melakukan prediksi banjir. Dengan menggunakan data ini, sistem pembelajar dapat menghasilkan nilai probabilitas dasar, yang sangat membantu sistem prediksi, memberikan solusi yang lebih hemat biaya dan kinerja yang lebih baik. Prediksi yang akurat dan tepat dapat membantu strategi pengelolaan sumber daya air, analisis kebijakan dan rekomendasi serta pemodelan evakuasi lebih lanjut. Penelitian ini akan dibahas tentang Perancangan Sistem Peringatan Dini Banjir berbasis Ensemble Machine Learning sebagai mitigasi bencana banjir. Hasil dari penelitian menunjukkan nilai RMSE dari algoritma ANFIS – PCA adalah sebesar 0.12 dan koefisen korelasi (R2) sebesar 0.856.Kata kunci: Prediksi Banjir, Machine Learning, ANFIS, ANFIS – PCA ABSTRACTThe nation of Indonesia is prone to disaster, with 76% of natural disasters being hydrometeorological, such as floods, landslides, tropical cyclones, and droughts. Flood occurrences can be physically modeled using complex mathematical equations. Machine Learning serves as a system for designing and developing algorithms that can predict flood events using historical data. Machine learning systems can leverage existing data to produce underlying probability values, making significant contributions to prediction systems that offer better performance and cost-effective solutions. Accurate predictions contribute to water resource management strategies, policy recommendations, and further evacuation modeling. This research will discuss an Early Warning Flood System design based on Ensemble Machine Learning as a flood disaster mitigation measure. The research results show that the RMSE value and coefficient correlation (R2) for the ANFIS - PCA algorithm are 0.12 and 0.856, respectively. Keywords: Flood Early Warning, Machine Learning, ANFIS, ANFIS – PCA
POWERED LANDING GUIDANCE ALGORITHMS USING REINFORCEMENT LEARNING METHODS FOR LUNAR LANDER CASE Nugroho, Larasmoyo; Zani, Novanna Rahma; Qomariyah, Nurul; Akmeliawati, Rini; Andiarti, Rika; Wijaya, Sastra Kusuma
Indonesian Journal of Aerospace Vol. 19 No. 1 (2021)
Publisher : BRIN Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.jtd.2021.v19.a3573

Abstract

Any future planetary landing missions, just as demonstrated by Perseverance in 2021 Mars landing mission require advanced guidance, navigation, and control algorithms for the powered landing phase of the spacecraft to touch down a designated target with pinpoint accuracy (circular error precision < 5 m radius). This requires a landing system capable to estimate the craft’s states and map them to certain thrust commands for each craft’s engine. Reinforcement learning theory is used as an approach to manage the mapping guidance algorithm and translate it to engine thrust control commands. This work compares several reinforcement learning based approaches for a powered landing problem of a spacecraft in a two-dimensional (2-D) environment, and identify the advantages/disadvantages of them. Five methods in reinforcement learning, namely Q-Learning, and its extension such as DQN, DDQN, and policy optimization-based such as DDPG and PPO are utilized and benchmarked in terms of rewards and training time needed to land the Lunar Lander. It is found that Q-Learning method produced the highest efficiency. Another contribution of this paper is the use of different discount rates for terminal and shaping rewards, which significantly enhances optimization performance. We present simulation results demonstrating the guidance and control system’s performance in a 2-D simulation environment and demonstrate robustness to noise and system parameter uncertainty.
Co-Authors AA Sudharmawan, AA Adbizar Asmon Rizal Adindra Vickar Ega Ahmad Fudholi Andiarti, Rika Anisa Rarasati Anisa Rarasati Anjar Susatyo Anjar Susatyo Anwar Soefi Ibrahim Arief Sudarmaji Bernadus H. S Budi Prawara Budi Prawara Chulafak, Galdita Aruba Dewi Maulidah Nur Anjani Duwi Hariyanto Ester Fatmawati Fajar Paundra Fajar Yulianto Fajar Yulianto Firliyani Rahmatia Ningsih Gatot Nugroho Gatot Nugroho Ghufron Zaid Handono, Juli Handoyo Handoyo Ibrahim, Anwar Soefi Joni Juli Handono Khomarudin, Muhammad Rokhis Kisna Pertiwi Kisna Pertiwi Larasmoyo Nugroho Melki Adi Kurniawan Mohamad Nur Yahya Mufidah, Zunanik Muhammad Arfin Hussein Muhammad Arfin Hussein Muhammad Priyatna Muhammad Priyatna Muhammad Priyatna, Muhammad Muhammad Rokhis Khomarudin Muhammad Rokhis Khomarudin Muhammad Syaukani Nuraini Rahma Hanifa Nurul Qomariyah Ocka Hedrony Paston Sidauruk Pingkan Mayestika Afgatiani Pingkan Mayestika Afgatiani Prawito Prawito Rachmawardani, Agustina Ratih Rundri Utami Ridwan Arief Subekti Ridwan Arief Subekti Rini Akmeliawati Sabar Sabar SOPAHELUWAKAN, ARSHASENA Tesa Apriyanti Tinton Dwi Atmaja Umiatin, Umiatin Wibisono Wibisono Zani, Novanna Rahma