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Review the Utilization of Big Data and K-Means Algorithm in Supporting the Determination of Village Status As Support to the Ministry of Village PDTT 2

Review the Utilization of Big Data and K-Means Algorithm in ...

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2nd International Conference on Sciences and Technology Applications, ICOSTA 2020

作者： Hasugian, Paska Marto Hutahaean, Harvei Desmon Sinaga, Bosker Sriadhi Silaban, Saronom Informatics Engineering Study Program STMIK Pelita Nusantara Medan Indonesia Computer Science and Informatics Education Study Program Faculty of Engineering Universitas Negeri Medan Medan20221 Indonesia Departement of Chemistry Universitas Negeri Medan Medan20221 Indonesia

Big data refers to big data, fast data processing, diversity of data structures, and data values so that it is not possible to be processed with outdated methods. Big data technology is used in various industrial sectors. Big data technology is the whole technology that can handle Big Data. Some of the uses of big data are based on the largest significant data traffic sources such as social media, financial transactions, public data, sensor data, and corporate data. The same is the case with the status of so many villages in Indonesia, so it is better to use big data for the classification of village status based on the village index build by involving an algorithm process. This research aims to produce a description of the role of big data in supporting activities in a grouping. The method used is a qualitative approach related to data collection based on scientific work with the source of data information needed to study literature techniques from various studies that have been published in national and international journals. A decision is made that big data has been widely used in different circles to facilitate performance and speed up the decision-making process. © Published under licence by IOP Publishing Ltd.

关键词： Data mining

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Observing Generator Performance by Finite Element Analysis Considering Coil Numbers 5

Observing Generator Performance by Finite Element Analysis C...

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5th International Conference on Technology and Policy in Energy and Electric Power, ICT-PEP 2023

作者： Habibi, Muhammad Afnan Ali Irfani, Mochamad Farhan Gumilar, Langlang Kusumawardana, Arya Aripriharta Baskoro, Angger Universitas Negeri Malang Study Program of Power Plant Engineering Technology Malang Indonesia Universitas Negeri Malang Department of Electrical Engineering and Informatics Malang Indonesia National Yang Ming Chiao Tung University Dept. Electrical Engineering and Computer Sciences Hsinchu Taiwan

ISBN: (纸本)9798350369717

This paper conducts a comprehensive analysis of electrical generator performance using Finite Element Analysis (FEA), with a specific emphasis on the role of coil numbers in influencing generator efficiency and functionality. In the context of modern energy systems, where efficient power generation is paramount, this research aims to elucidate the relationship between the number of coils within a generator and its overall performance, including power output and electromagnetic behavior. Through systematic FEA simulations that vary coil numbers while keeping other parameters constant, this study provides valuable insights into the trade-offs associated with increased coil numbers and enhanced efficiency. These findings have significant implications for optimizing generator designs across various applications, from renewable energy systems to industrial power generation, ultimately advancing our understanding of generator dynamics and contributing to more sustainable and efficient power generation technologies. © 2023 IEEE.

关键词： Finite element method

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Artificial Intelligence-Based System ‘SiMoniK’ for MSMEs

Artificial Intelligence-Based System ‘SiMoniK’ for MSMEs

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Information Technology International Seminar (ITIS)

作者： Sri Lestari Yulmaini Aswin Sulyono Ruki Rizal Nul Fikri Faculty of Computer Science Informatics Engineering Study Program Bandar Lampung Indonesia Faculty of Economics Business Management Study Program Bandar Lampung Indonesia

Artificial intelligence was recently implemented in various fields. One of these applied artificial intelligence systems was the Performance Monitoring System “SiMoniK” for MSMEs. This system was designed through the C4.5 algorithm and the Porat-Rank method. The C4.5 algorithm was applied to classify the MSMEs into three classifications, e.g. the micro enterprise classification, the small enterprise classification, and the medium enterprise classification. Moreover, the Porat-Rank method was also applied to distribute the solving-problem recommendations and to improve the independence of MSMEs. The result of this study was that the C4.5 algorithm could classify the MSME data correctly in the form of an accuracy value of 99.2%. Besides, the Porat-Rank method could also provide recommendations in the form of outstanding quality with an NDCG mean value of 0.87.

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Innovative web-based microteaching model: To improve the teaching skills of prospective informatics teachers in vocational high schools

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Social Sciences and Humanities Open 2025年 11卷

作者： Sugihartini, Nyoman Elmunsyah, Hakkun Nurhadi, Didik Rahmawati, Yuni Vocational Education Doctoral Program Post Graduate School Universitas Negeri Malang Malang Indonesia Informatics Education Study Program Department of Informatics Faculty of Engineering and Vocational Universitas Pendidikan Ganesha Bali Indonesia

Prospective informatics teachers in vocational schools (VS) must master content knowledge, pedagogical skills, and technology integration to achieve learning goals. Therefore, informatics teachers in VS need to innovate to increase students' creativity. However, many prospective informatics teachers experience difficulties in this regard. This research aims to develop and implement the Web-Based Microteaching (WBM) model to improve the teaching skills of prospective informatics teachers at VS. This study uses research and development methods with the ADDIE model approach. The research results show that the WBM model effectively improves prospective informatics teachers' teaching skills, especially in planning lessons and practising basic teaching skills. This innovation is a relevant learning solution in the digital era and positively contributes to the professional development of informatics teachers. The WBM model is an innovation to provide a more intensive and structured practical experience by utilizing web technology as the main media. Through web-based learning, prospective teachers can access material, exercises and feedback independently, which is expected to accelerate pedagogical mastery. © 2025 The Authors

关键词： Microteaching model Prospective informatics teacher Teaching skills Vocational high schools Web-based

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Identification of Beef Freshness Using Linear Discriminant Analysis (LDA) Algorithm and Extraction of HSV Values 2

Identification of Beef Freshness Using Linear Discriminant A...

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2nd International Conference on Electronic and Electrical engineering and Intelligent System, ICE3IS 2022

作者： Napianto, Riduwan Tri Prastowo, Agung Deni Wahyudi, Agung Wajiran Yudoutomo, Yohanes Egi Pratama Suparto, Arico Ayani Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Bandarlampung Indonesia Information Technology Education Study Program Stkip Pgri Situbondo Situbondo Indonesia

ISBN: (纸本)9781665465410

To determine the quality of beef, it is usually seen using a flashlight and matching it with a predetermined color standard. However, this method is time consuming and the results are inconsistent due to human visual limitations. This study aims to identify the freshness of beef based on its color characteristics using feature extraction method with HSV and LDA method for identification. The identification process begins with the transformation process from RGB images to L∗a∗b, then image segmentation serves to separate one object from another and image identification uses the LDA method with feature extraction using HSV. The use of color feature extraction with the HSV algorithm to assist in obtaining information from the colors contained in the image for easy identification. Furthermore, the LDA algorithm has a function to obtain the maximum projection to obtain a smaller dimensional space so that the desired patterns can be separated through the boundary line of a linear equation so as to form a certain class or group. Based on the test results using the confusion matrix, it produces a precision value of 80%, recall of 84%, and accuracy of 82%. © 2022 IEEE.

关键词： Beef

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IoT-Integrated Machine Learning for Real-Time Soil Nutrient Monitoring and Horticultural Crop Recommendations

IoT-Integrated Machine Learning for Real-Time Soil Nutrient ...

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Information Technology International Seminar (ITIS)

作者： Abdul Wahid Jumadi Mabe Parenreng Aswandi Ananta Dwi Prayoga Alwi Satria Gunawan Zain Wirawan Setialeksana Informatics and Computer Engineering Department Universitas Negeri Makassar Makassar Indonesia Network Engineering Technology Study Program Politeknik Negeri Lhokseumawe Lhokseumawe Indonesia

ISBN: (数字)9798331521295

ISBN: (纸本)9798331521301

Farmers and agricultural newcomers often rely on intuition for plant nutrient management, leading to inaccuracies. This study presents a real-time soil nutrient monitoring and plant recommendation system using IoT and machine learning. The prototype integrates an ESP32 microcontroller, NPK sensor, soil pH sensor, and DHT11 with an application and a machine learning model. The model employs a hard voting method combining random forest, LightGBM, and support vector machine algorithms, deployed via Flask API and hosted on Vercel. Testing showed the system effectively monitors soil nutrients in real-time, with a pH sensor error margin of ±0.51 and NPK sensor readings displaying a non-linear increase in levels. The hard voting method achieved 98.5% accuracy, with recommendation processing taking less than one second (371.17ms) and CPU usage at 7%. System performance depends on internet speed, while recommendation accuracy is influenced by temperature and humidity. This system offers a practical solution for precision agriculture by optimizing nutrient application and plant recommendations.

关键词： Temperature measurement Temperature sensors Support vector machines Accuracy Prototypes Soil Nutrients Real-time systems Monitoring Random forests

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Decision Support System in Determining the Achievement of Widyaiswara Value Using WASPAS and TOPSIS Algorithm 1

Decision Support System in Determining the Achievement of Wi...

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1st International Conference on Technology Innovation and Its Applications, ICTIIA 2022

作者： Pratama, Yudhistira Adhitya Iswara, Bagus Ajie Nababan, Adli Abdillah Information System Studies Program Pelita Harapan University Medan Campus Faculty Of Computer Science Medan Indonesia Master's Study Program Informatics Engineering Universitas Sumatera Utara Faculty Of Computer Science And Information Technology Medan Indonesia Digital Business Study Program Stmik Pelita Nusantara Medan Indonesia

ISBN: (数字)9781665488266

ISBN: (纸本)9781665488266

Widyaiswara is required to show the best performance to fulfill his duties and obligations. Therefore, it is very important to measure the performance of the Widyaiswara, so that it can be used as evaluation material by the BPSDM PROVSU. However, the assessment process that occurs is still not precise and time-consuming. Therefore, to minimize this, a decision support system is needed that can minimize time errors and data processing in decision-making so that the assessment runs well and accurately. This system was built by applying the WASPAS method and the TOPSIS method. Based on the results of tests carried out five times, the results of the WASPAS method processing time resulted in an average processing time of 0.00029791 ms and an average memory usage value of 2.836.44 kb, while the results of the TOPSIS method processing time test resulted in an average processing time - an average of 0.000296428 ms and an average memory usage value of 2.862.34 kb. © 2022 IEEE.

关键词： Decision support systems

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Mini Prototype of the Futuristic Bin with an Automatic Waste Sortation System for Managing the Garbage Problems in Society

Mini Prototype of the Futuristic Bin with an Automatic Waste...

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International Conference on Wireless and Telematics (ICWT)

作者： Muhammad Taufik Dwi Putra Anugrah Adiwilaga Jezzy Putra Munggaran Muhammad Azka Adhitama Raihan Anwar As'Ad Ahmad Ali Alhafidz Rin Rin Nurmalasari Agus Juhana Computer Engineering Study Program Universitas Pendidikan Indonesia Bandung Indonesia Department of Electrical Engineering UIN Sunan Gunung Djati Bandung Indonesia Multimedia Education Study Program Universitas Pendidikan Indonesia Bandung Indonesia

ISBN: (数字)9798350377057

ISBN: (纸本)9798350377064

This article explores the development and implementation of futuristic bins with automated waste sortation systems to address improper and mixed waste disposal challenges. Despite the existence of categorized waste bins, individuals often dispose of waste improperly, hindering the sorting and decomposition processes. Integrating advanced technologies, such as Artificial Intelligence (AI), futuristic bins offer innovative solutions. Futuristic bins with automated sorting systems facilitate accurate waste sorting, reduce mixing, and optimize waste disposal. These bins increase efficiency, reduce costs, and optimize collection routes while promoting environmental cleanliness and awareness of waste management. The article describes the research methodology, including preliminary study, specification requirements analysis, prototype development, and testing. The results demonstrate the implemented system's accuracy and real-time object detection capabilities. The study also acknowledges limitations and suggests future research directions, including improving communication between object detection algorithms and microcontrollers. Overall, the development of futuristic bins with automated waste sortation systems represents a significant advancement in waste management, with the potential to revolutionize waste management systems and create sustainable cities and communities.

关键词： Accuracy Costs Urban areas Prototypes Object detection Real-time systems Waste disposal

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The Recommendation System for Increasing the Independence of Micro, Small and Medium Enterprises (MSMEs) Using the Normalized Rating Frequency (NRF) Method 4

The Recommendation System for Increasing the Independence of...

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4th International Conference on Information and Communications Technology, ICOIACT 2021

作者： Lestari, Sri Yulmaini Aswin Kurniawan, Rio Sulyono Pratama, Yan Aditiya Faculty of Computer Science Informatics Engineering Study Program Bandar Lampung Indonesia Faculty of Business Economics Management Study Program Bandar Lampung Indonesia

ISBN: (纸本)9781665433945

Micro, Small, and Medium Enterprises (MSMEs) have an important role in improving the economy of small communities and the stability of the Indonesian economy. However, they still face various problems such as capital, raw materials, distribution, licensing, and others. This study developed a special treatment recommendation system to increase the independence of MSMEs by adopting a ranking-based method to produce recommendations related to problem-solving steps from MSMEs. The ranking method used Normalized Rating Frequency (NRF). This method performed an aggregation process of the ratings given by MSMEs in looking at the priority level of problem-solving based on previous experience. The result of the experiment showed that an average NDCG value was 0.7916. This explained that the quality of the ranking was good so that it was feasible to be recommended in solving problems in the form of special treatment to acquire to the independence of MSMEs. © 2021 IEEE

关键词： Recommender systems

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Selection of education Assistance Recipients Based on AHP and SAW 23

Selection of Education Assistance Recipients Based on AHP an...

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23rd International Seminar on Intelligent Technology and Its Applications, ISITIA 2022

作者： Pranoto, Gatot Tri Pebrianti, Dwi Darwis, Muhammad Yaddarabullah Krishnasari, Erneza Dewi Pelita Bangsa University Informatics Engineering Study Program Bekasi Indonesia Budi Luhur University Computer Science Jakarta Indonesia Universitas Trilogi Department of Informatics Engineering Jakarta Indonesia Universitas Trilogi Department of Visual Communication Design Jakarta Indonesia

ISBN: (数字)9781665460811

ISBN: (纸本)9781665460811

The final decision of the educational assistance recipient in GNOTA Foundation, Jakarta is still processed manually. They usually only look at the father's occupation criteria without looking at other criteria such as the age of the child, the child's orphan status, the occupation of mother, the age of father, the age of mother and other scholarships received. GNOTA Foundation needs to implement a Decision Support System (DSS) for the selection process, so the results are fast and on target. This research applies the Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods for the selection of education assistance recipients so the criteria can be weighted and the prospective recipient students can be ranked. This research determines the priority weight and importance of each criterion, namely the age of child age (0.18), the status of child (0.22), the occupation of father (0.08), the occupation of mother (0.06), the age of father (0.05), the age of mother (0.04) and other scholarship assistance (0.36). The results of the weighting of these criteria have been tested and declared consistent through the Consistency Ratio (CR) value of 0.070. This study also produces a list of the best ranking students who are prospective recipients of educational assistance. The ranking results have been tested based on compliance with the provisions of the GNOTA Foundation of 92.91%. The system in this study was developed using a prototyping system development model and utilizing the Unified Modeling Language (UML) tool. The prototype functionality in this study works well by using the Blackbox Testing (BBT) model based on Equivalence Partitioning. In addition, the level of user acceptance of the prototype in this study was 81.2% using the Technology Acceptance Method (TAM). © 2022 IEEE.

关键词： Decision support systems

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