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Design of big data technology prototype for classification of village status based on village development index involves k-means algorithm to support village ministry Pdtt work programs 2

Design of big data technology prototype for classification o...

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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 technology is the overall technology that can handle the processing associated with analyzing the data to explore the potential that is in it. Some of the uses of big data are based on the biggest data traffic sources, such as social media, financial transactions, public data, censorship data, and company data. The problem found in the accumulation of village status data that has not been utilized in the decision-making process to determine the status of the next village and the absence of an application to process the data stored in the data database so that a tool is developed to analyze the buildup. The results of this study are to produce a prototype design that is Unified Modeling Language (UML) design, Form Design, and Database Design that will be used to develop Big Data Technology in determining the classification of village status based on the Village Build index. © Published under licence by IOP Publishing Ltd.

关键词： Decision making

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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

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fast data processing, diversity of data structures, and data values so that it is not possible to be processed with outdated methods.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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Finding the Best Techniques for Predicting Term Deposit Subscriptions (Case study UCI Machine Learning Dataset)

Finding the Best Techniques for Predicting Term Deposit Subs...

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International Conference on Sustainable Engineering and Creative Computing (ICSECC)

作者： Lila Setiyani Ayu Indahsari Rosalina Tjong Wansen Master of Science Information Technology study program President University Bekasi Indonesia Informatics Study Program President University Bekasi Indonesia

Knowing a lot about attributes, such as bank client data, marketing campaigns, social and economic context, and so on, is necessary to predict which bank customers are likely to sign up for time deposits. The direct marketing campaigns dataset for the bank institution was made available by the UCI machine learning repository. This dataset had previously been used in studies to forecast customers who would sign up for time deposits, but the outcomes of the two studies were different. The purpose of this study is to determine which machine learning methods are most effective for predicting customers who will sign up for time deposits. In this study, researchers used machine learning methods like random forests, K-nearest neighbors, decision trees, naive bayes, logistic regression, SVM, and XGBoost to uncover the truth. Results showed that XGBoost had the highest accuracy (91.73%), followed by the DT classifier (88.79%), LR classifier (91.2%), NB classifier (84.78%), KNN classifier (90.6%), SVM (89.6%), and XGBoost (91.44%).

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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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IoT: Monitoring Temperature, Water pH, and Automatic Water Drainage Systems for Gurami Cultivation

IoT: Monitoring Temperature, Water pH, and Automatic Water D...

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Networking, Electrical Engineering, Computer Science, and Technology (IConNECT), International Conference on

作者： Heni Sulistiani Wijaya Saputra Dedi Darwis Auliya Rahman Isnain Ardy Rimanda Putra Yosi Khairunisa Study Program of Accounting Information System Universitas Teknokrat Indonesia Lampung Indonesia Study Program of Computer Engineering Universitas Teknokrat Indonesia Lampung Indonesia Study Program of Informatics Universitas Teknokrat Indonesia Lampung Indonesia Regional Research and Development Agency Lampung Province (Balitbangda) Lampung Indonesia

Gurami is a native fish from Indonesian waters that is much-loved by Indonesian people for daily food consumption. The gurami inhabits still waters such as swamps, lakes, and ponds. Besides that, carp cannot live in a water content that is too alkaline or acidic, the oxygen content in the water must be stable. Water quality is a very important factor and can affect the survival of cultivated fish. Several parameters must be considered in improving the development of carp, one of which is the temperature and pH of the water and automatic drainage of water. In this paper, we conduct IoT-based research that focuses on controlling water temperature and pH and automatically draining pool water. Water temperature and pH control such as a pH sensor temperature sensor and a water turbidity sensor will later be connected to the ESP 32 microcontroller which already has a wi-fi module. A system that is linked to electrical power and the internet then the sensor will read the water quality including the pH temperature value and water turbidity from inside the fish pond, after getting the data, the data will go to ESP 32. This research can help gurami cultivating farmers to make it easy to control the pH temperature and perform automatic pool water draining. The results of sensor testing with actual data are pretty accurate with the average error value of the ds18b20 sensor being 0.05% while the value of the pH sensor itself is 0.07%.

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Real Market Basket Analysis using Apriori and Frequent Pattern Tree Algorithm

Real Market Basket Analysis using Apriori and Frequent Patte...

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2021 International Conference on Computer, Control, informatics and Its Applications - Learning Experience: Raising and Leveraging the Digital Technologies During the COVID-19 Pandemic, IC3INA

作者： Christian, Michael Albert Nathanael, Nathanael Mauliani, Annisa Indrawati, Ariani Manik, Lindung Parningotan Akbar, Zaenal Informatics Engineering Program Study Kwik Kian Gie School of Business Jakarta Indonesia Research Center for Informatics National Research and Innovation Agency Bandung Indonesia

ISBN: (纸本)9781450385244

Recently, data mining has been implemented in various fields, including business and telecommunications. Data mining is a technique for extracting and detecting patterns in massive data sets that combines machine learning, statistics, and database systems. One of the most important use-cases in data mining is finding the high-frequency patterns between the set of itemset called association rules. Association rule mining is a well-researched technique for finding some relations between variables in large databases. This paper aims to measure the performance of the Apriori and Frequent Pattern Tree algorithms by comparing them using several points of comparison. Then we compared the outputs, whether they produce the same or different rules, to find out whether the way the two algorithms work is similar or not. After that, we looked for the itemsets that best match the reality in the market by giving them to a user who had transaction data from his spare parts shop. © 2021 ACM.

关键词： Association rules

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Internet of Medical Things: A Bibliometric Analysis of Research Publications from 2018–2022 4th

Internet of Medical Things: A Bibliometric Analysis of Resea...

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4th International Conference on Electronics, Biomedical Engineering, and Health informatics, ICEBEHI 2023

作者： Maulana, Fairuz Iqbal Lestari, Dian Adi, Puput Dani Prasetyo Arifin, Mohammad Nazir Purnomo, Agung Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Faculty of Medicine Universitas Airlangga Surabaya60132 Indonesia Telecommunication Research Center National Research and Innovation Agency Jakarta11480 Indonesia Informatics Engineering Study Program University of Madura Pamekasan Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9789819714629

The field of the Internet of Medical Things (IoMT) is experiencing significant growth as it involves the integration of medical devices and systems with the internet and various digital technologies. This study provides a bibliometric analysis of scholarly articles pertaining to the Internet of Medical Things (IoMT) during the time frame of 2018 to 2022. The analysis is conducted using data sourced from the Scopus database. A total of 1165 documents were identified and analyzed to gain insights into the current state of research in this field. The analysis includes trends in publication output, top authors and institutions, and key research topics. The results of the analysis indicate a steady increase in publication output on IoMT over the past five years, with the highest number of publications in 2022. The top authors in this field were Mohanty, S.P., Kougianos, E., and Pirbhulal, S., while the top institutions were King Saud University, Chinese Academy of Sciences, and University of North Texas. Co-citation analysis revealed that wearable devices, telemedicine, and data analytics were among the key research topics in IoMT. This bibliometric analysis offers useful insights into the present research landscape of the Internet of Medical Things (IoMT) spanning the years 2018 to 2022. The findings can be beneficial for researchers, practitioners, policymakers, and funding agencies in understanding the trends and priorities in this field. The top authors and institutions identified in this analysis can serve as valuable resources for collaboration and staying updated on the latest developments in IoMT. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Digital devices

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New Media as a Tools to Improve Creative Thinking: A Systematic Literature Review 7

New Media as a Tools to Improve Creative Thinking: A Systema...

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7th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2023

作者： Hermawan, Hellik Mahardika, Fajar Darmayanti, Irma Sumantri, R. Bagus Bambang Saputra, Dhanar Intan Surya Aminuddin, Afrig Universitas Amikom Purwokerto Faculty of Computer Science Department of Informatics Jawa Tengah Banyumas Indonesia Institut Teknologi Dan Sains Nahdlatul Computer Technology Study Program Faculty of Science and Technology Ulama Pekalongan Indonesia Universitas Amikom Purwokerto Faculty of Computer Science Department of Information Technology Jawa Tengah Banyumas Indonesia Universitas Harapan Information Systems Study Program Faculty of Science and Technology Bangsa Indonesia Universitas Amikom Yogyakarta Faculty of Computer Science Sleman Indonesia

ISBN: (纸本)9798350382266

This systematic literature review (SLR) study aims to analyze the role of New Media as a Tool to Improve Creative Thinking, with relevant articles from 2018 to 2023 taken from reputable international journals. It uses three research questions (RQ) to explore New Media's relevance in stimulating creativity. The results indicate that interactive platforms such as social media and online collaboration tools positively influence creative thinking skills. Interaction through New Media allows individuals to share ideas, discuss, and be exposed to various points of view, all of which stimulate creative thinking. In addition, New Media also facilitates the creative process of solving problems and generating original ideas. The immersive experiences offered by this technology can enhance the exploration of ideas and increase the ability to think out-of-the-box. While New Media offers great potential to enhance creativity, there are also potential risks, such as false information, media addiction, and privacy concerns. Therefore, awareness of the wise use of New Media needs to be increased, especially in education and everyday life. Overall, this literature review provides in-depth insight into the role of New Media in enhancing creative thinking skills and driving innovation. With the right approach, New Media can be an effective tool in stimulating creative thinking and encouraging the creation of original ideas beneficial for future social and technological developments. © 2023 IEEE.

关键词： Creative Thinking New Media Original Ideas Systematic Literature Review The Effect of Using New Media

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Development Of Scholarship Sustainability Analysis Application Every Semester On STMIK Pelita Nusantara Students

Development Of Scholarship Sustainability Analysis Applicati...

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International Conference of Computer Science and Information Technology

作者： Nera Mayana Br Tarigan Bosker Sinaga Erwin Panggabean Jijon Raphita Sagala Informatics Engineering Study Program STMIK Pelita Nusantara Medan Indonesia Software Engineering Study Program STMIK Pelita Nusantara Medan Indonesia

ISBN: (纸本)9798350399080

Decision making in an organization is needed a system. Decision support system is a system that helps company management and education in decision making that provides information, modeling and analyzing data with the application of a method. The management, especially higher education, must maximize sophisticated technology. For example, to analyze scholarship data. Problems are found in manual data analysis so that human errors often occur in addition to using more time than the target, losing old data, resulting in inaccurate analysis of scholarship sustainability every semester. The research was conducted to overcome the problems that have been found by analyzing the existing data with the simple additive weighting method, building a system by applying the method and testing the system. The result of this research is to produce an application for the development of a decision support system in managing student data to determine the sustainability of the scholarship every semester. Applications that are built can help the management in managing scholarships.

关键词： Decision support systems Additives Scholarships Education Decision making Surface acoustic waves Data models

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Online Handwritten Recognition For Alphabet Writing Practice

Online Handwritten Recognition For Alphabet Writing Practice

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Ni Putu Linda Santiari I Gede Surya Rahayuda Information System Study Program Faculty of Informatics and Computer Institute of Technology and Business STIKOM Bali Denpasar Indonesia Informatics Study Program Faculty of Math and Natural Sciences Udayana University Mangupura Indonesia

ISBN: (纸本)9781665453967

Learning to write in children requires the child's habit of using a pencil to write on paper. The manual method has drawbacks such as the use of a lot of paper when children have to study harder to keep repeating the exercises and also cannot be done online remotely. In addition to this, writing exercises on the touchscreen can also train children to be more skilled at using the touchscreen. To overcome these problems, the author will discuss the use of handwriting recognition technology to practice writing capital letters (A-H), where the technology will be built on a web-based basis. The recognition algorithm used is K-NN. Testing the use of the website was carried out at Tunas Mekar Sari Kindergarten, Denpasar. The identification number and result will be stored on the web server. Based on the experiment, it was found that from 80 image data, the K-NN algorithm succeeded in providing accurate recognition results on 60 image data, and obtained an accuracy of 78.75%.

关键词： Handwriting recognition Image recognition Manuals Writing Touch sensitive screens Animation Web servers

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