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1st International Conference on Computer Science and Applied Mathematic, ICCSAM 2018

作者： Syahputa, Zulfahmi Zarlis, M. Nasution, Beny B. Informatics Engineering Study Program Magister Faculty of Computer Science Information Technology Universitas Sumatera Utara Medan Indonesia

Raspberry Pi is a mini-computer that is provided to carry out activities quickly and precisely, but Raspberry Pi was created to not be able to do the real-time system with the support of Windows 10 IoT operating system, so the real-time system can be done on Raspberry Pi. The real-time applied in the application needs to be tested with the Nyquist theory. The purpose of this study was to get real-time system measurements available on Windows 10 IoT. This test is done using the Nyquist theory by calculating the results of measurements on mp3 streaming performed on Windows 10 IoT. © Published under licence by IOP Publishing Ltd.

关键词： Real time systems

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Analysis of Decision Tree and Smooth Support Vector Machine Methods on Data Mining 1

Analysis of Decision Tree and Smooth Support Vector Machine ...

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1st International Conference on Computer Science and Applied Mathematic, ICCSAM 2018

作者： Sitepu, Natalina Br Sawaluddin Zarlis, M. Efendi, Syahril Dhany, Hanna Willa Informatic Engineering Study Program Magister Faculty of Computer Science and Information Technology Universitas Sumatra Utara Medan Indonesia

This research is about smooth support vector machine (SSVM) and Decision Tree in data mining. Many researchers conduct and develop methods to improve the accuracy and classification of data on good results. This research was conducted by conducting an experiment on STMIK Neumann Medan student data. In this study, it was concluded that Decision Tree performance is better than SSVM, Decision Tree gets very good results that promise to help find the best students to get scholarships. This study is better than SSVM. The training process has a difference of 11.04% and the testing process is 10.08% with each Accuracy. © Published under licence by IOP Publishing Ltd.

关键词： Decision trees

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Techno-Economic Analysis of Bioethanol Production from Sugarcane Bagasse in Indonesia

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SSRN 2023年

作者： Aditiya, H.B. Riayatsyah, Teuku Meurah Indra Chitra, I.S.N. Ong, Hwai Chyuan Silitonga, A.S. Mahlia, T.M. Indra Department of Mechanical Engineering Faculty of Engineering Sampoerna University Jakarta Indonesia Sampoerna University Energy Research Center Pancoran Jakarta Selatan12780 Indonesia School of Civil & Environmental Engineering University of Technology Sydney 81 Broadway UltimoNSW2007 Australia Department of Mechanical Engineering National Yunlin University of Science and Technology Touliu Yunlin64002 Taiwan Program Study of Mechanical Engineering Department of Production and Industrial Technology Institut Teknologi Sumatera South Lampung 3536 Indonesia Future Technology Research Center College of Engineering National Yunlin University of Science and Technology Douliou Yunlin64002 Taiwan Centre for Technology in Water and Wastewater School of Civil and Environmental Engineering Faculty of Engineering and Information Technology University of Technology SydneyNSW2007 Australia Center of Renewable Energy Department of Mechanical Engineering Politeknik Negeri Medan Medan20155 Indonesia

The studies of bioethanol production are being intensively explored over the past years in the provision of biofuel. This has been long recognized as the best alternative for a renewable energy resource to overcome the problem of the depletion of fossil resources. Indonesia's main agricultural sector, sugarcane industry, has shown promise in supplying sugarcane bagasse (SCB) as a feedstock for the second generation of bioethanol production. In this study, the techno-economic analysis of the sugarcane bagasse from the bioethanol production plant was explored, and the viability of bioethanol production based on the biomass generated from a local sugarcane factory was evaluated. All the costs that will be incurred during a 20-year operating period for a 203 ktons bioethanol production plant from SCB is $231 million, with a payback period of 6.19 years. The potential amount of bioethanol produced from SCB of this plant is 30.19 ML/year with the production cost (levelized cost of bioethanol, LCOB) of $0.59 per liter of ethanol produced. Overall, SCB bioethanol still carries better competitiveness at lower selling price in comparison with the latest price regulation by the Indonesian government ($0.85/L). © 2023, The Authors. All rights reserved.

关键词： Life cycle

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High Level Learning Approach for High Level Collision Avoidance Using Sensors

High Level Learning Approach for High Level Collision Avoida...

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Interdisciplinary Humanitarian Conference for Sustainability (IIHC), International

作者： Lamhot Naibaho Razauddin L. Vertivendan V. Karunakaran Ashish Oberoi N.C. Ajay Vishwath English Language Education Study Program Faculty of Letters and Languages Christian University of Indonesia Department of computer and information sciences Gulf Colleges Saudia Arabia Department of CSE Galgotias University Greater Noida Uttar Pradesh India Department of CSE Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bangalore INDIA Department of CSE RIMT University Mandi Godindgarh India Aeronautical Department Parul Institute of Engineering and Technology Parul University

Motion planning for many unmanned aircraft is challenging because they have a larger configuration space than self-driving automobile development (Automated guided vehicles). Additionally, there are more significant uncertainties and disruptions in UAV environments, which makes inter automatic navigation more difficult. In this letter, I proposed a 2 recurrent neural networks (RL) oriented multi-UAV collision avoidance technique by modeling the unpredictability or noise in the environment. Our objective is to create a strategy that can construct a path without clashing with anything using local noisy data. But unlike supervised algorithms, RL lacks a steady training data set with floor labels, thus its collision avoidance strategies often show significant fluctuation and are difficult to reproduce. To solve these issues, we created a two-stage training method for RL-based collision avoidance. We first optimize the policy, and then we utilize a supervised learning methodology with a loss function that encourages the agents to adopt the well-known reciprocity obstacle detection mechanism. In the second step, we use transmission to fine-tune the policy. The complete computer simulation findings demonstrate that this approach can handle noisy local views with erratic sound levels and can design moment & accident paths under inadequate sensing. We review the impact of our policies in a variety of ways.

关键词： Training Uncertainty Supervised learning Training data Aircraft navigation Sensors Noise measurement

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Performance LoRa Technology for Autonomous Vehicles

Performance LoRa Technology for Autonomous Vehicles

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International Seminar on Intelligent Technology and Its Applications (ISITIA)

作者： Puput Dani Prasetyo Adi Iwan Purnama Arfanda Anugrah Siregar Angga Putra Juledi Firman Edi Abdul Karim Yuyu Wahyu Fairuz Iqbal Maulana Suhardi Atmoko Budi Susilo Toni Ilham Maliki Harahap Lintang Patria National Research and Innovation Agency (BRIN) Bandung Indonesia Faculty of Science and Technology Labuhanbatu University Labuhanbatu North Sumatra Indonesia Telecommunication Engineering Study Program Politeknik Negeri Medan Medan City North Sumatra Indonesia Department of Engineering Management Faculty of Industrial Technology Batam Institute of Technology Batam City Riau Islands Indonesia Department of Information Technology Budi Darma University Medan North Sumatra Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Teacher Training and Education Labuhanbatu University Labuhanbatu North Sumatra Indonesia Faculty of Engineering Universitas Terbuka Jakarta Indonesia

This research is an approach to intelligent vehicles with a LoRa communication system, LoRaWAN compatible for Long-Range and Outdoor Communication, but in this paper, we will test the ability of LoRa to handle autonomous vehicles, a Blind-Adaptive Data method will be tried on vehicles systems. The system offered is when the vehicle is running, the sensor will send position data in real-time, the number of vehicles is four, and GPS data is sent alternately using the Blind Adaptive Data Rate principle to avoid data collisions, and when the GPS shows a certain position, the value of SF is ascertained, which affects the data rate and ToA, and the output given is RSSI on each car, speed of a car, power consumption of sensor nodes, signal power, SNR, Bit rate or data rate, and sensitivity. With the Blind ADR principle, it is ensured that there is no data collision between car position data that causes packet loss.

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Developing vocabulary card base on Augmented Reality (AR) for learning English

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IOP Conference Series: Materials Science and engineering 2021年第1期1073卷

作者： I F Rozi E Larasati V A Lestari Informatics Engineering Study Program Information Technology Politeknik Negeri Malang

The application of technology in the world of education can affect the quality of students in understanding learning material because technology is one of the important elements to assist in the teaching and learning process. One educational application that can be developed is Augmented Reality (AR) technology. AR is one of the learning media that can be used to combine virtual objects or objects into a real environment with the virtual world to be able to interact in realtime. English is a foreign language that must be mastered. In learning English, students need to be given adequate vocabulary learning that can be provided through reading or listening activities. The importance of adequate vocabulary in English to support the smoothness of oral communication, where there are 2 things that inhibit the ineffectiveness of oral communication namely students do not have adequate vocabulary mastery and do not know how to use vocabulary in their spoken language. Effective and interactive learning media will facilitate students in learning vocabulary. This research an instructional media based on augmented reality vocabulary cards will be made for learning English vocabulary. Learning English vocabulary developed is a basic vocabulary consisting of object recognition and greeting. The learning media will display real objects and sounds, so that the object looks real and the ease of pronunciation of English consonants correctly.

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Advanced Blb Disease Assessment in Paddy Fields Using Multispectral Uav Data and Patch Fragmentation Metrics

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SSRN 2024年

作者： Wijayanto, Arif Kurnia Prasetyo, Lilik Budi Hudjimartsu, Sahid Agustian Sigit, Gunardi Hongo, Chiharu Department of Forest Resource Conservation and Ecotourism Faculty of Forestry and Environment IPB University Bogor16680 Indonesia Ronpaku Fellow Tokyo102-0083 Japan Environmental Research Center IPB University Bogor16680 Indonesia Study Program of Information Technology Faculty of Science and Engineering Ibn Khaldun University Bogor16129 Indonesia Department Agriculture Forestry and Bioresources Seoul National University Seoul08826 Korea Republic of Regional Office of Food Crops Service West Java Province Cianjur43283 Indonesia Chiba University Chiba263-8522 Japan

This study presents a new method for assessing bacterial leaf blight (BLB) in paddy fields using multispectral UAV (Unmanned Aerial Vehicle) data through patch fragmentation analysis. Unlike traditional pixel-based methods, which often fail to capture the spatial context, our approach treats pixels as objects and analyzes their spatial relationships to evaluate BLB severity. We used six patch fragmentation metrics derived from binarized vegetation indices to classify BLB damage scores using a random forest algorithm. This method achieves high accuracy (AUC of 0.938) with a 0.5-meter sampling window, offering a more detailed assessment than conventional pixel-based analysis. This study highlights the benefits of incorporating the spatial context and improving BLB monitoring and management. This innovative approach allows agricultural stakeholders to gain valuable insights into the extent and severity of BLB disease infestation, enabling targeted intervention strategies for disease management and mitigation. © 2024, The Authors. All rights reserved.

关键词： Pixels

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Method for modelling the number of HIV and AIDS cases using least square spline Biresponse nonparametric negative binomial regression

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MethodsX 2025年 14卷 103336页

作者： Ramadan, Arip Chamidah, Nur Budiantara, I Nyoman Lestari, Budi Aydin, Dursun Doctoral Study Program of Mathematics and Natural Sciences Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia Information System Study Program Department of Industrial and System Engineering Telkom University Surabaya Campus Surabaya 60231 Indonesia Department of Mathematics Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia Research Group of Statistical Modeling in Life Science Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia Statistics Department Faculty of Science and Data Analytics Sepuluh Nopember Institute of Technology Surabaya 60111 Indonesia Department of Mathematics Faculty of Mathematics and Natural Sciences The University of Jember Jember 68121 Indonesia Department of Statistics Faculty of Science Muğla Sıtkı Koçman University Muğla 48000 Turkey Research Scholar at Department of Mathematics University of Wisconsin Oshkosh Algoma Blvd Oshkosh 54901 WI United States

We propose a new statistical modeling method to analyze functional relationship between predictor variables and correlated response variables, and apply it for modeling the number of HIV and AIDS cases influenced by early-age marriages and contraceptive users. The proposed method is LS-Spline BNNBR that is a Biresponse Nonparametric Negative Binomial Regression (BNNBR) based on least squares spline (LS-Spline). To validate the proposed method, we compare it with classical method, namely Ordinary Least Square Biresponse Parametric Negative Binomial Regression (OLS-BPNBR). The results show that the LS-Spline BNNBR method provided deviance value of 7.542334 which is smaller than that of OLS-BPNBR method, namely 7.993935. Thus, the proposed method has better prediction fit than the classical method. • This study discusses new statistical modeling method for the number of HIV and AIDS cases influenced by early-age marriages and contraceptive users where the response variables are correlated with each other. • The model estimation results show that the number of HIV and AIDS cases in Indonesia will decrease if the early-age marriages percentage increases and the contraceptive users percentage decreases. • The results are useful to provide a scientific basis for making policies to control the number of HIV and AIDS cases in Indonesia. © 2025 The Authors

关键词： AIDS BLSSNNBR model Contraceptive user Early-age marriage HIV Least square spline

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Linearization of two-state thruster models 5

Linearization of two-state thruster models

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5th International Conference on Mathematics: Pure, Applied and Computation, ICoMPAC 2019

作者： Adzkiya, Dieky Nurhadi, Hendro Herlambang, Teguh Department of Mathematics Institut Teknologi Sepuluh Nopember Indonesia Department of Industrial Mechanical Engineering Institut Teknologi Sepuluh Nopember Indonesia Center of Excellence for Mechatronics and Industrial Automation Research Center Institut Teknologi Sepuluh Nopember Indonesia Study Program of Information Systems Universitas Nahdlatul Ulama Surabaya Indonesia

A thruster is a device used for station keeping, attitude control, in the reaction control system, or long-duration, low-thrust acceleration. Thruster is one of the main components in autonomous surface vehicle. In this paper, we discuss the linearization of two-state thruster model by using the Jacobian method. © Published under licence by IOP Publishing Ltd.

关键词： Linearization

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Rapid and non-destructive determination of vitamin C and antioxidant activity of intact red chilies using visible near-infrared spectroscopy and machine learning tools

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Case Studies in Chemical and Environmental engineering 2023年 8卷

作者： Devianti Sufardi Hafsah, Siti Sariadi Ahmad, Fachraniah Arianti, Nunik Destria Saputra, Edo Hartuti, Sri Department of Agricultural Engineering Faculty of Agriculture Syiah Kuala University Banda Aceh 23111 Indonesia Department of Soil Science Faculty of Agriculture Universitas Syiah Kuala Banda Aceh 23111 Indonesia Department of Agrotechnology Faculty of Agriculture Universitas Syiah Kuala Banda Aceh 23111 Indonesia Department of Chemical Engineering Politeknik Negeri Lhokseumawe Lhokseumawe 24301 Indonesia Department of Information System Nusa Putra University Sukabumi 43155 Indonesia Department of Agricultural Technology Faculty of Agriculture Universitas Riau Pekanbaru 28293 Indonesia Agricultural Engineering Study Program IPB University Bogor 16680 Indonesia

Red chili peppers are extensively used in the culinary industry due to their high vitamin C, antioxidant content, spice, and natural colorant properties. Traditional methods for determining these parameters are time-consuming and unstable. This study investigates the viability of visible near-infrared spectroscopy as a rapid and nondestructive method for determining vitamin C content and antioxidant activity in intact red chilies. Visible near-infrared spectroscopy measures the sample's light absorption, proportional to its chemical composition. Collecting intact red chili samples from various sources and determining their vitamin C content and antioxidant activity using conventional methods were required for the study. The visible near-infrared spectra of the pieces were collected using a spectrometer, and chemometric models were devised to correlate the spectra with the vitamin C content and antioxidant activity. Traditional methods were compared to visible near-infrared spectroscopy regarding their performance of prediction. In conjunction with chemometric models and machine learning algorithms, visible near-infrared spectroscopy could accurately predict red chilies' vitamin C content and antioxidant activity. The developed models exhibited high calibration and prediction coefficients, low root mean square errors, and high prediction-to-deviation ratios. The identified absorption peaks in the visible near-infrared spectra were related to the samples' color pigments and water content. This study demonstrates the feasibility of visible near-infrared spectroscopy as a rapid and nondestructive method for determining the vitamin C content and antioxidant activity of intact red chilies. The findings may have significant ramifications for the food industry, providing a more efficient and secure quality control and nutritional labeling method. It is recommended that additional research and validation be conducted to ensure the applicability of the developed models to var

关键词： Chemometrics tools Machine learning Red chilies Spectroscopy

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