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All Journal Jurnal Ilmiah Aplikasi Isotop Radiasi WAPFI (Wahana Pendidikan Fisika) Spektra: Jurnal Fisika dan Aplikasinya Jurnal ULTIMA Computing Indonesian Journal of Biomedicine and Clinical Sciences Indonesian Journal of Aerospace
Adhi Harmoko Saputro
Department Of Geography, Faculty Of Mathematics And Natural Sciences, University Of Indonesia, UI Depok Campus, Depok, 16424, Indonesia
Aerospace Engineering Astronomy Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Materials Science & Nanotechnology Medicine & Pharmacology Neuroscience Physics Social Sciences Other

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Pengukuran Scaling pada Pipa menggunakan Tomografi Gamma Parallel Beam Bayu Azmi; Wibisono Wibisono; Adhi Harmoko Saputro
Jurnal Ilmiah Aplikasi Isotop dan Radiasi Vol 13, No 1 (2017): Juni 2017
Publisher : BATAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17146/jair.2017.13.1.3914

Abstract

Pembentukan scale pada pipa maupun unit proses lainnya dapat terjadi di dalam proses produksi. Scaling pada pipa dapat mengurangi diameter pipa sehingga mengurangi laju alir dan bahkan mengakibatkan pipa tersumbat. Pengukuran diperlukan untuk mengetahui keberadaan dan persentase scaling pada pipa. Tomografi merupakan teknik yang digunakan untuk menginvestigasi struktur dalam suatu obyek secara non-intrusive dan non-invasive. Dalam penelitian ini sistem tomografi digunakan untuk pemindaian translasi dan rotasi secara otomatis. Sumber radiasi gamma 137Cs yang terkolimasi mentransmisikan foton gamma menembus obyek uji yang kemudian dideteksi dengan detektor sintilasi NaI(Tl). Kumpulan data proyeksi dibangun menjadi citra menggunakan perekonstruksi citra dengan metode filtered back projection (FBP). Citra hasil rekonstruksi dapat membedakan material dengan nilai densitas yang berdekatan seperti air (1 g/cm3), parafin (0,9 g/cm3), dan pertalite (0,72-0,77 g/cm3). Citra pipa dengan scale dianalisis untuk menghitung persentase area aliran setelah terjadi scaling terhadap pipa normal (pipa tanpa scale). Hasil analisis citra area aliran yang tersisa pada pipa geothermal plant adalah 10,06% dengan 16 proyeksi, 9,86% dengan 32 proyeksi, 9,75% dengan 64 proyeksi, dan 9,76% dengan 128 proyeksi, sedangkan 26,08% pada pipa furnace dengan 32 proyeksi. Sistem yang telah dibangun berhasil memindai obyek, mengakuisisi dan mengumpulkan data, serta membangun dan menganalisis citra untuk menginvestigasi scale di dalam pipa.
The development and use of artificial intelligence (AI) in dermatology: a narrative review Irene Darmawan; Shannaz Nadia Yusharyahya; Sampurna, Adhimukti T.; Saputro, Adhi Harmoko
Indonesian Journal of Biomedicine and Clinical Sciences Vol 56 No 3 (2024)
Publisher : Published by Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/inajbcs.v56i3.15970

Abstract

Artificial intelligence (AI) is defined as a computer science involving program development aiming to reproduce human cognition to analyze complex data. Artificial intelligence has rapidly developed in the medical field. In dermatology, its development is relatively new and is generally used in the diagnostic, especially for skin imaging analysis and classification, and also for risk assessment. The greatest advances have been primarily in the diagnosis of melanoma, followed by the assessment of psoriasis, ulcers, and various other skin diseases. The use of AI has shown good accuracy and is comparable to dermatologists in various studies, especially related to melanoma and skin tumors. However, several obstacles exist in the application of AI to daily clinical practice, including generalizability, image standardization, the need for large data quantities, and legal and privacy aspects. In current developments, AI should be aimed at helping enhance the decision-making of clinicians.
Seismometer Health Diagnosis Based on Cross Spectral Density Coherence Method in Indonesia Seismic Networks Jannah, Miftahul; Annisa, Risa; Saputro, Adhi Harmoko; Lestari, Titik
Spektra: Jurnal Fisika dan Aplikasinya Vol. 9 No. 3 (2024): SPEKTRA: Jurnal Fisika dan Aplikasinya, Volume 9 Issue 3, December 2024
Publisher : Program Studi Fisika Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/SPEKTRA.093.05

Abstract

Evaluation of seismometer health is crucial in accurately detecting earthquake and tsunami events. Currently, seismometer health evaluation is based solely on data quality unrelated to seismometer sensor performance. While seismometers are essential for tracking seismic activity, environmental factors, aging components, and external interference can cause seismometers to function worse over time. This study presents a seismometer health diagnosis technique based on seismic signal analysis, including signal truncation, signal resampling, filtering, and deconvolution of instrument response. Then the proposed method of cross-spectral density coherence to extract seismometer sensor health indicators performed on two adjacent broadband seismic stations by analyzing the frequency domain with a maximum inter-station distance of 100 km. The data used are seismic signals recorded on three-component seismometers (North-South, East-West, Z-Vertical). The coherence value of cross-spectral density is used as an indicator to diagnose seismometer health. The proposed method was evaluated on a seismic network in Indonesia consisting of 88 stations and a teleseismic earthquake event in Honshu, Japan. The coherence values of almost all tested stations are above 0.8, which means good performance. The proposed method is suitable for analyzing the health of seismometers, especially in Indonesia.
Stem-base Rot Disease Detection in Oil Palm using RGB (Red, Green, Blue) and OCN (Orange, Cyan, NIR) Image Fusion Method Based on ResNet50 Panggabean, Prima Ria Rumata; Rista, Rista; Saputro, Adhi Harmoko; Handayani, Windri
Spektra: Jurnal Fisika dan Aplikasinya Vol. 10 No. 1 (2025): SPEKTRA: Jurnal Fisika dan Aplikasinya, Volume 10 Issue 1, April 2025
Publisher : Program Studi Fisika Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/SPEKTRA.101.02

Abstract

Current image acquisition and processing methods still need to be improved to effectively detect oil palm diseases. A precise and fast method to detect stem base rot disease in oil palm trees can be developed using drone technology and image processing approaches. An OCN (Orange, Cyan, NIR) camera is added to a standard drone and equipped with an RGB (Red, Green, Blue) camera. Combining the two cameras is proposed to generate multispectral imagery using an image fusion method called early fusion. A Multispectral Convolution Neural Network (MCNN) is also introduced to detect stem base rot disease by analysing the leaf patterns of oil palms. Healthy and unhealthy leaf samples were collected from oil palm plantations in Bogor. The images that have passed the image processing stage with the fusion method become inputs for modelling to identify stem base rot disease in oil palm. The results of the research using the multispectral image fusion method (RGB and OCN) based on the ResNet50 architecture can be used to identify stem base rot disease in oil palm effectively, as evidenced by the training and validation accuracy of 97.75% and 96.48%.
Implementation of Vibration and Wave Puzzles to Increase Students’ Interest and Motivation in Learning Physics Class Pramesti, Hari Agusasi; Saputro, Adhi Harmoko
WaPFi (Wahana Pendidikan Fisika) Vol 10, No 1 (2025): WaPFi (Wahana Pendidikan Fisika) February 2025
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/wapfi.v10i1.79371

Abstract

For students to develop interest and motivation in learning physics, teachers need to create active and enjoyable learning experiences. A suitable model is crucial to provide students with new ways to engage with physics, making them more active in class and improving their learning outcomes. This study aims to assess the effect of students’ interest and motivation on their learning outcomes, as well as their response to the applied learning model. Using a pretest and posttest experimental design, the study involved seventy 11th-grade students. Data were collected through tests and questionnaires. The learning outcomes (tests) were analyzed using paired t-test, while questionnaire data were examined using multiple linear regression with SPSS 25. The paired t-test results show a 2-tailed value of 0.000 indicating a significant increase in students’ motivation and interest due to the use of vibration and wave puzzles. Meanwhile, based on the analysis of the questionnaire results, the Adjusted R-Square value from the regression analysis is 0.456, which means that 45.6% of the variation in learning outcomes is explained by students’ interest and motivation. These findings shows that the developed learning model is effective in increasing students’ interest and motivation to learn towards students’ achievement or learning outcomes. Student engagement and performance from the application of this puzzle-based learning method makes learning active and learner-centered engagement in a fun and innovative way, offering an alternative approach to teaching physics and a foundation for further research on other physics topics.
Long Term Prediction of Extreme Weather with Long Short Term Memory (LSTM) Model: Effect of Climate Change Putri, Nurulita Purnama; Harmoko Saputro, Adhi
ULTIMA Computing Vol 17 No 1 (2025): Ultima Computing: Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v17i1.4022

Abstract

Increasingly intense climate change has increased the frequency and intensity of extreme weather, making weather prediction critical for mitigation and adaptation. This research focuses on long-term prediction of extreme weather using the Long ShortTerm Memory (LSTM) model, as well as evaluating the influence of climate change on prediction accuracy. In this study, historical weather data is used to train and test an LSTM model combined with a RandomForestClassifier. Analysis was carried out using the Mean Squared Error (MSE) evaluation technique for 50 epochs and 8 trials at various threshold values (26, 29, 32, 35, 38, 41, 44, 47). The research results show that the LSTM model is able to predict extreme weather with an accuracy of up to 100%. Apart from that, this research also predicts daily rainfall in Bandung City through the process of data collection, preprocessing, normalization and evaluation using Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). This model produces an RMSE of 4.24 and MAE value of 2.72%, indicating quite good predictions. It is hoped that this research can make a significant contribution to the field of meteorology and can be developed further by adding parameters or other methods to improve the quality of predictions. Suggestions are given to increase the amount of data used to obtain better prediction results in the future.
A Review of Absolute Radiometry Calibration Method for Satellite Multispectral Camera while in Orbit Sartika Salaswati; Saputro, Adhi Harmoko; Hasbi, Wahyudi
Indonesian Journal of Aerospace Vol. 22 No. 2 (2024): Indonesian Journal Of Aerospace
Publisher : BRIN Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/ijoa.2024.3090

Abstract

Multispectral cameras on satellites are a type of camera that is widely used in satellite remote sensing and has wide applications. Therefore, it is necessary to carry out absolute radiometric calibration to maintain the accuracy of radiometric information in satellite camera images. There are several types of absolute radiometric calibration, including onboard, Rayleigh, vicarious, and cross-calibration. These methods have strengths and weaknesses. Therefore, it is necessary to conduct a literature review to find out which calibration method is appropriate for certain conditions. Based on a literature review, all methods can be used and adapted to the conditions of the satellite. The onboard calibration method is suitable for satellites equipped with calibration instruments. The Rayleigh calibration method is suitable for large FOV cameras with visual wavelengths. The vicarious calibration method is suitable for satellites from countries close to standardized calibration sites. Meanwhile, the cross-calibration method is suitable for satellites cameras that have specifications and conditions close to the reference camera. Therefore, these calibration methods can be carried out together to complement each method.
Co-Authors Annisa, Risa Bayu Azmi Dimyati, Ratih Dewanti Dony Kushardono Handayani, Windri Irene Darmawan Kustiyo Kustiyo, Kustiyo LILIK BUDIPRASETYO Miftahul Jannah Panggabean, Prima Ria Rumata Pramesti, Hari Agusasi Putri, Nurulita Purnama Rista, Rista Rokhmatuloh, Rokhmatuloh Sampurna, Adhimukti T. Sartika Salaswati Shannaz Nadia Yusharyahya Titik Lestari Wahyudi Hasbi Wibisono Wibisono