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Analysis of extreme weather used C-band radar and rain gauge for floods and landslides in Lombok

AIP Conference Proceedings 2023年第1期2609卷

作者： Made Sutha Yadnya Yudist I. Wayan Sudiarta 1Electrical Engineering Communication Laboratory Engineering Faculty University of Mataram Mataram Indonesia 2BMKG Lombok Mataram Indonesia 3Physic Study Program Faculty of Mathematics and Natural Science University of Mataram Mataram Indonesia

This paper is collaboration between BMKG and the University of Mataram to mitigate landslides by utilizing C-band radar data and rain gauges in measuring rainfall as the main factor triggering disasters. In heavy and prolonged rains, there is a chance for disasters to occur. Based on the observations of the Lombok International Airport Meteorological Station (-8°76'59"LS and 116°27’'91"E), the 24-hour cumulative rain on January 30, 2021, the analysis results of 64 mm/h can be included in the category of extrime rainfall.

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Simulation of model landslides observation in laboratory used by IoT

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AIP Conference Proceedings 2023年第1期2609卷

作者： Made Sutha Yadnya I. G. P. Wedashwara Wedarama I. Wayan Sudiarta 1Electrical Engineering Communication Laboratory Engineering Faculty University of Mataram Mataram Indonesia 2Informatics Engineering Faculty of EngineeringUniversity of Mataram Mataram Indonesia 3Physic Study Program Faculty of Mathematics and Natural Science University of Mataram Mataram Indonesia

This paper is collaboration between BMKG and the University of Mataram to mitigate land slide. For this study using light intensity sensors, air temperature sensors, voltage sensors, current sensors, humidity sensors. This research is on a laboratory scale with a soil slope of 10 degrees, dry soil with a tendency to split (clay) from brittle volcanic rocks. The initial conditions were without rain, then the soil was burdened with rain in low (drizzle), medium (25mm/h) and high (55mm/h) capacities. The second condition of the stage is given a vibration which is a model of the earthquake evenly on that stage. Soil Moisture soil, soil temperature, 3 pieces of vibration sensor switch, piezo electric vibration sensor. The initial height of the soil is 36.78 cm with a width of 79.35cm after being rained for 90 minutes, the final height is 29.93 and 60.25 cm, widening receding to the right and left sides.

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Digital filter effect of the ventilator tester parameters to identify inflation phases

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AIP Conference Proceedings 2022年第1期2537卷

作者： Tomy Abuzairi Ahli Irfan Basari 1Electrical Engineering Study Program Department of Electrical Engineering Faculty of Engineering Universitas Indonesia Kampus UI Depok West Java 16424 Indonesia 3Research Center for Biomedical Engineering Faculty of Engineering Universitas Indonesia Kampus UI Depok West Java 16424 Indonesia 2Biomedical Engineering Study Program Department of Electrical Engineering Faculty of Engineering Universitas Indonesia Kampus UI Depok West Java 16424 Indonesia

A ventilator is a breathing support device that serves as a therapeutic tool or treatment tool for patients with respiratory system failure caused by various health problems or diseases. On ventilators, there are crucial parameters that need to be monitored in advance, such as inspiration–expiration (I:E) ratio, respiration rate, tidal volume, peak inspiration pressure (PIP), positive end-expiratory pressure (PEEP), and oxygen concentration. To monitor those parameters, a ventilator tester is needed. In this paper, we analyzed the effect of a digital filter in the ventilator tester, COVENT-Tester, to identify the inflation phase in the ventilator parameters. The results show that the digital filter is not effective in measuring I:E ratio and respiration rate because of the delay in inspiration and expiration time. However, the digital filter is effective in measuring tidal volume, PIP, PEEP, and oxygen concentration.

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A comparison on the use of Perlin-noise and Gaussian noise based augmentation on X-ray classification of lung cancer patient 1

A comparison on the use of Perlin-noise and Gaussian noise b...

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1st International Symposium on Physics and Applications, ISPA 2020

作者： Haekal, M. Septiawan, R.R. Haryanto, F. Arif, I. Department of Physics Faculty of Sciences and Data Analytics Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo-Surabaya Jawa Timur60111 Indonesia Computer Engineering Study Program School of Electrical Engineering Telkom University Jl. Telekomunikasi No.1 Jawa Barat Bandung40257 Indonesia Faculty of Mathematics and Natural Sciences Institut Teknologi Bandung Jl. Ganeca 10 Jawa Barat Bandung40132 Indonesia

The use of deep learning in medical image classification has become an important study in the past few years. The proper use of this method, however, is still hindered by many problems, one of it being the imbalance of dataset available for training which resulted in small-set database. In this study, the effect of noise-based augmentation on the performance of deep learning based classification will be studied. The noises which were used for the augmentation method were Perlin-noise and Gaussian noise. The modality of medical image used in this study is X-ray. 174 X-ray images (87 cancer, 87 normal) were used in this study and will be classified by using transfer learning from previously trained deep learning architecture. The deep learning architecture used was vgg-19. The images were divided into two groups, 138 (69 cancer, 69 normal) images were used for training phase and 36 (18 cancer, 18 normal) were images used for testing phase. Three deep learning models were used for the classification tasks, the first one was retrained to classify the original images, the second one was retrained by using mix of original images and images with Perlin-noise, and the third one was retrained by using mix of original images and images with Gaussian noise. The results showed that the three models returned similar accuracy of 0.8 which indicate that the use of noise-based augmentation can increase the performance of deep learning in classifying medical images with small set training database. © Published under licence by IOP Publishing Ltd.

关键词： Classification (of information)

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Development of measuring quality to Buffalo’s meat in Toraja

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AIP Conference Proceedings 2022年第1期2542卷

作者： Wilson Jefriyanto Benyamin Salu Ishak Pawarangan Welsiliana 1Physics Education Study Program Universitas Kristen Indonesia Toraja Makale Indonesia 2Elementary School Teacher Education Study Program Universitas Kristen Indonesia Toraja Makale Indonesia 3Electrical Engineering Study Program Universitas Kristen Indonesia Toraja Makale Indonesia 4Biology Study Program Universitas Timor Kefamenanu Indonesia

Toraja has long been known as an area that is very thick with customs and culture. Rambu Solo’ is a traditional death ceremony which in the process of its activities there is a buffalo slaughter. The number of buffalo is determined by the strata of the family who died or the ability of the family and relatives. Because the consumption of buffalo meat is quite high in Toraja, and knowledge about the quality of meat such as buffalo meat has still lacked in the community, it is necessary to test the quality of the meat. In measuring the quality of meat usually use laboratory tests, the results of which are quite long. In addition, the testing has not been carried out by the Health Service in Toraja due to limited tools and other facilities. With the development of science, now there are several sensors to detect variables of the maturity of a meat such as the color, moisture and pH. This research is a continue research that has previously been carried out, namely a prototype measuring tool for measuring meat maturity based on *** this study, a prototype measuring instrument for the quality of buffalo meat has been made using the parameters of color, moisture and pH. The results of this study is show that prototype is able to identify several parameters of meat quality. The higher the RGB data, the better the meat. As for the good moisture, the meat has a high water holding capacity or humidity, while the pH of the meat measured is still in normal conditions for all types of meat.

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study on the waste valve's stroke to water hammer pressure and flow patterns in a hydraulic ram pump

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AIP Conference Proceedings 2023年第1期2568卷

作者： I. P. Widiarta M. Suarda I. G. K. Sukadana M. Sucipta N. M. Suantini I. N. Suweden 1Student at Master Study Program of Mechanical Engineering Faculty of Engineering Udayana University Denpasar Bali Indonesia 2Mechanical Engineering Department Faculty of Engineering Udayana University Denpasar Bali Indonesia 3Chemistry Department Faculty of Mathematics and Natural Science Udayana University Denpasar Bali Indonesia 4Electrical Engineering Department Faculty of Engineering Udayana University Denpasar Bali Indonesia

The pressure in the hydraulic ram pump increases due to a sudden cessation of flow out through the waste valve when the waste valve is closing. The increasing of water hammer pressure is strongly influenced by velocity of the water flow in the drive pipe. Therefore, the waste valve has an important role in mechanism of the occurrence of water hammer pressure, performance, and flow patterns in the hydraulic ram pump. This study investigated the water hammer pressure and the flow patterns in the hydraulic ram pump that has been installed at Bon sub-village, as well as its performance at various strokes of the waste valve. In addition, CFD simulation using Ansys Fluent was conducted. The result show that increasing stroke of the waste valve increase the water velocity in the drive pipe and the water hammer pressure, and the optimum of the waste valve stroke has been predicted subject to volumetric and total efficiency using the equation of their trendlines. Furthermore, the flow patterns such as vortex, split flow, and blockage mass in the hydraulic ram pump have been identified.

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Sweat sensing in wearable sensor: A review of the future non-invasive technology for real-time health monitoring system

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AIP Conference Proceedings 2022年第1期2537卷

作者： Elly Septia Yulianti Nurul Intan Siti Fauziyah Rahman Basari 1Biomedical Engineering Study Program Department of Electrical Engineering Faculty of Engineering Universitas Indonesia Kampus UI Depok West Java 16424 Indonesia 2Research Center for Biomedical Engineering Faculty of Engineering Universitas Indonesia Kampus UI Depok West Java 16424 Indonesia

Wearable sensors are devices used in the diagnostic process for real-time health monitoring systems. Types of sensors are generally based on physical sensors and chemical sensors. However, the types of wearable sensors that are largely commercialized are limited to physical sensors. Some diagnostic processes generally use the blood collecting method to determine a patient’s condition. However, this method can cause adverse effects such as infection, pain, and bruising for some patients. Chemical-based wearable sensors are capable of detecting metabolic conditions in the body and can be an alternative to the existing method. Based on an approach using alternative analytes, sweat is the most frequently used because it is highly accessible and proceeds good parameters compared to the blood. Several studies related to wearable sensors using sweat have been done to increase convenience during the sampling process. Electrochemical, biosensor, and hybrid with several sampling methods, including microfluidic system, absorbent material, superhydrophobic-super hydrophilic surface, and iontophoresis, can be used for wearable sensor analysis method. Over the past decade, the characteristics of wearable sensors (i.e., selectivity, sensitivity, stability, and response time), textile materials, and biofuel cell technology for self-powered sensor development have also increased. From these classifications, it can be concluded that the method which is highly feasible to be developed is electrochemical wearable sensors that combine microfluidic and iontophoresis systems. The system is also expected to have stretchable material and is equipped with an integrated biofuel cell system that has the potential to be developed in our upcoming research topic.

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Design of BCI motor imagery classification using WPT-CSP and CNN

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AIP Conference Proceedings 2022年第1期2537卷

作者： Dio Alif Pradana Basari 1Biomedical Engineering Study Program Department of Electrical Engineering Faculty of Engineering Universitas Indonesia Kampus UI Depok West Java 16424 Indonesia 2Research Center for Biomedical Engineering Faculty of Engineering Universitas Indonesia Kampus UI Depok West Java 16424 Indonesia

This study proposes a new method in an electroencephalograph (EEG)-based Brain-Computer Interface (BCI) that can directly utilize brain signals to control external devices. The motor Imagery (MI) signal, which contains an image of a certain limb movement, is generally used in BCI. It does not need direct movements. The implementation of MI-EEG signal into BCI still experiences major issues because the patterns obtained for each recording can vary from one another even though they have the same type of motion. In this study, we utilized the Wavelet Packet Transform (WPT) method to decompose the EEG signal into specific sub-band frequencies and Common Spatial Pattern (CSP) as a spatial filter to increase the spatial resolution of the EEG signal. The Convolutional Neural Network (CNN) was subsequently selected for training from the classifier. Next, the results of the training were used to classify the movements of the given MI-EEG. We evaluated the model using dataset 2a from Brain-Computer Interface Competition (BCIC) IV. The results of this method showed the increase in the accuracy of 32% and in Kappa up to 0.42 and the decrease in Root Mean Square Error (RMSE) up to 1.21, compared with only using CNN as the classifier. These results showed fairly good performance compared to other methods used previously in dataset 2a from BCIC IV.

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Correlation between digital literacy and environmental literacy of 11th-grade students

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AIP Conference Proceedings 2024年第1期3106卷

作者： Mimien Henie Irawati Al Muhdhar Shinta Amrul Khoirina Muhamad Arjuna Salim Racy Rizky Abdillah Diana Hernawati Diki Muhamad Chaidir Muhammad Iqbal Akbar Lely Mardiyanti Mohammad Qodri Department of Biology Faculty of Mathematics and Sciences Universitas Negeri Malang Malang East Java Indonesia Department of Biologi Education Universitas Siliwangi Tasikmalaya Wesst Java Indonesia Department of Electrical and Informatics Engineering Faculty of Engineering Universitas Negeri Malang Malang East Java Indonesia Study Program of Biological Education Universitas Jambi Jambi Indonesia SMA Negeri 1 Batu Batu East Java Indonesia

The rapid development of technology, information, and communication requires students to master digital literacy. In addition, the rapid development of technology also affects environmental conditions, so it is necessary to master environmental literacy to understand and interpret environmental conditions, as well as build students’ awareness of environmental issues. This study aims to determine the correlation between digital literacy and student environmental literacy. The population in this research includes 11th-grade students of SMAN 1 Batu. The research sample amounted to 102 students, and the sampling technique used was purposive random sampling. Data were collected through digital literacy questionnaires, environmental literacy questionnaires, and environmental literacy tests. The data were tested for normality and homogeneity prerequisites and then analyzed using the Pearson Correlation statistical test. The results obtained show that the average digital literacy score of students is 105.1, including the high category, and the average student environmental literacy score is 279.7, included in the medium category. The high level of digital literacy will make students more critical in accessing technology and digital media. Digital literacy includes the process of finding, using multiple sources, evaluating, and using information to produce original products, with the maximum application of digital literacy, which is expected to support students’ environmental literacy in providing knowledge, understanding, and building an attitude of caring for the environment. The data obtained shows that there is a positive relationship between digital literacy and environmental literacy.

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Classification of Civet and Canephora coffee using Support-Vector Machines (SVM) algorithm based on order-1 feature extraction

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IOP Conference Series: Materials Science and engineering 2021年第1期1173卷

作者： R Z H Suyoto M Komarudin G F Nama T Yulianti Informatics Engineering Study Program Department of Electrical Engineering Faculty of Engineering Universitas Lampung Jl. Prof. Sumantri Brojonegoro No.1 Bandar Lampung 35145 Indonesia

Identification of coffee beans types is a process carried out in determining the category of civet and robusta coffee. The selection of civet coffee manually by the community in determining the variety of coffee beans. Manual selection makes the process slow. There is no certainty whether the selected coffee stated original civet coffee or a mixture with Robusta coffee. It needs to be built a system in identifying the types of coffee beans. In this study, the classification technology used for the selection process of Civet and Robusta coffee beans. This research uses first-order feature extraction with the Support-Vector Machines (SVM) algorithm, which aims to recognize civet and robusta coffee beans' patterns using texture analysis on grayscale images and feature extraction. In the study, the authors used the Rapid Application Development approach to build the selection system. The data used in this study were 120 images, consisting of 110 training data and 10 test data. The accuracy in identifying the types of coffee beans by using this method is 87.27%.

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