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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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Analysis of the effect of charge and discharge LiFePO4 batteries using BMS with and without Active balancer

Analysis of the effect of charge and discharge LiFePO4 batte...

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2022 International electrical engineering Congress, iEECON 2022

作者： Muangjai, Worrajak Aroonchai, Thanakit Somsak, Teerasak Ngaodet, Montri Oranpiroj, Kosol Thongpron, Jutturit Rajamangala University of Technology Lanna Electrical Engineering Program Faculty of Engineering Chiang Mai Thailand Rajamangala University of Technology Lanna Collage of integrated science and technology Chiang Mai Thailand

ISBN: (纸本)9781665402064

The purpose of this research was to study the behavior of battery management systems (BMS) and to study the effect of charge and discharge of batteries using BMS with and without Active balancer. 1) Comparison of BMS case behavior and 2) Battery performance when BMS is connected to Active balancer. The experiments were divided into two methods, charge and discharge in the BMS only, and compared with systems with Active balancer, by determining current. Fixed in the experiment at a battery charge of 0.2-1C (1-5A), then the results of the two experiments were compared and analyzed on the advantages and disadvantages of the system. Research has shown that systems with Active balancer have a more significant effect on a battery charge than systems without Active balancer and the most efficient in use at 0.4C (2A). © 2022 IEEE.

关键词： Lithium compounds

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NFT-Based Hydroponic Automated Control Using Adaptive Network-Based Fuzzy Inference System 2

NFT-Based Hydroponic Automated Control Using Adaptive Networ...

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2nd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2022

作者： Surantha, Nico Vincentdo, Vito Bina Nusantara University Binus Graduate Program - Computer Science Jakarta11480 Indonesia Tokyo City University Faculty of Scienc and Engineering Department of Electrical Electronics and Communication Engineering Japan

ISBN: (纸本)9781665459440

The rapid population growth and industrial development in developing countries harm the agricultural sector because many agricultural lands are converted into residential or industrial areas. Applying modern agriculture technologies such as hydroponic could help to overcome the problem. However, hydroponics requires special attention in adjusting the pH and nutrient levels to maximize plant growth, so an automated system is needed to manage the process. In this research, a smart hydroponic system is proposed by applying Adaptive Networkbased Fuzzy Inference System (ANFIS) and Internet-of-Things. The IoT system consists of sensor, actuator, and data processing layer is designed to monitor and control the condition of pH and nutrition of the observed plants. Then, the ANFIS algorithm is designed to control the level of pH and nutrition. The experiment results show that the system can automatically adjust the pH and nutrient levels to the expected range for growing plants, and the fuzzy controller made using ANFIS are more accurate and stable than the fuzzy controller made using Sugeno. This study shows that ANFIS has excellent performance when controlling multiple actuators, as long as the data set has great granularity and well defined. © 2022 IEEE.

关键词： Hydroponics

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Investigation of Microplastics in Raw and Processed Water for Unbranded Refilled Drinking Water in Karawang, Indonesia

SSRN

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SSRN 2025年

作者： Sari, Gina Lova Utami, Marsah Rahmawati Kasasiah, Ahsanal Rohmana, Andini Siti Amethysia, Nur Ridha Cahyaningrum, Putri Sekti Nainggolan, Adinda Melianda Kurniawan, Setyo Budi Study Program of Environmental Engineering Faculty of Engineering Universitas Singaperbangsa Karawang H.S Ronggowaluyo Karawang41361 Indonesia Study Program of Pharmacy Faculty of Health Science Universitas Singaperbangsa Karawang H.S Ronggowaluyo Karawang41361 Indonesia Department of Chemical and Process Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Selangor UKM Bangi 43600 Malaysia

It is undeniable that microplastics are found in many types of water, including drinking water. This study aims to investigate the presence of microplastics in one of the drinking waters widely used by communities in Indonesia, known as unbranded refilled drinking water. The investigation was conducted at eight unbranded refilled drinking water depots in Karawang, West Java. A total of 2.00 L of raw air and processed water samples were taken from each depot, then prepared by the National Oceanic and Atmospheric Administration, analyzed using an Olympus BX - 41 microscope with a magnification of ten times, and then counted manually. The results showed that raw and processed water in all unbranded refilled drinking water depots contained microplastics with details of 15.50-42.00 particles/L and 6.50-17.50 particles/L, respectively. The dominant microplastics found were fibers and fragments with sizes of 1.00-3.00 mm and less than 1.00 mm. Furthermore, the dominant color of the microplastics was black, indicating that the polymers of microplastics were polyethylene, polypropylene, or polystyrene. This finding has confirmed that refilled drinking water consumed by the community in Indonesia has potentially become one of the main pathways for the entry and accumulation of microplastics into the human body, posing significant health risks. Based on current research, further research is needed to improve water treatment performance to protect public health. © 2025, The Authors. All rights reserved.

关键词： Microplastic

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Monitoring System for Elderly Health Care Using Smart Band, Raspberry Pi, and Node-Red 2

Monitoring System for Elderly Health Care Using Smart Band, ...

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

作者： Ardiyanto, Yudhi Adi, Kusworo Kurnianingsih Putra, Karisma Trinanda Utomo, Pradityo System School of Postgraduate Studies Universitas Diponegoro Doctoral Program of Information Semarang Indonesia Universitas Muhammadiyah Yogyakarta Faculty of Engineering Department of Electrical Engineering Yogyakarta Indonesia Universitas Diponegoro Faculty of Science and Mathematics Department of Physics Semarang Indonesia Politeknik Negeri Semarang Faculty of Engineering Department of Electrical Engineering Semarang Indonesia Universitas Merdeka Madiun Faculty of Engineering Department of Informatics Management Madiun Indonesia

ISBN: (纸本)9781665465410

The decline in physical, cognitive, and sensory functions for most elderly people leads to the development of several health issues such as memory loss, a tendency to fall, dizziness, and reduced ability to care for oneself independently. These can be mitigated using devices designed to monitor vital signs and human activity such as a smart band. However, the application of a smart band is characterized by a disadvantage which involves storing user data in the vendor's cloud and only one device can access the client applications. Therefore, nurses, doctors, and family members cannot simultaneously analyze data and receive alerts when abnormal conditions occur in elderly patients. This study aims to develop a system capable of monitoring the health conditions of multiple elderly individuals and sending alerts during abnormal conditions based on the heart rate value read by the smart band sensor. The process involved installing a database on the Raspberry Pi to store data while a monitoring system was built on the Node-RED platform to display elderly health data and made it accessible locally. The detection of an abnormal heart rate condition in the elderly patient leads the system to send notifications via telegram to multiple receivers registered in the system using their telegram identity. © 2022 IEEE.

关键词： Heart

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Towards the Improvement of the Cognitive Process of the Synthesized Speech of Mathematical Expression in MathML: An Eye-Tracking 2

Towards the Improvement of the Cognitive Process of the Synt...

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2nd International Conference on Interactive Media, Smart Systems and Emerging Technologies, IMET 2022

作者： Souza, Adriana Freitas, Diamantino Bahia Federal Institute of Education Science and Technology Bahia Brazil Doctoral Program in Digital Media Faculty of Engineering of the University of Porto Porto Portugal Faculty of Engineering of the University of Porto Speech Processing Laboratory Electrical and Computer Engineering Department Porto Portugal

ISBN: (数字)9781665470162

ISBN: (纸本)9781665470162

Being one essential part of the solutions we are developing to provide accessibility for blind persons, synthesized speech of mathematical content, although having evolved in naturalness in recent years, still keeps a characteristic of generating very long outputs, which makes it difficult for a person who uses a screen reader to memorize. Eye-gaze tracking has been useful for studying cognitive processes and student's effort in performing tasks therefore it seems attractive as a means to understand how people analyze, process, and break down extensive math expressions into smaller ones. This understanding can help to build a similar model of auditory rendering of MathML capable of avoiding cognitive overload. Therefore, we carried out an experiment to do a gaze-based analysis of reading and memorizing mathematical expressions. Our sample consisted of fourteen participants, and seven mathematical expressions were used in the experiment. The results showed that the computed complexity of the expressions and the average duration of eye-gaze fixations have a strong and significant relationship. Therefore, we conclude that the complexity variable must always be considered in the speech synthesis process of mathematical expressions. However, when considering why participants requested the repetition of an expression with not larger complexity during the memorization process, a tentative interpretation based on the number of MathML tree nodes and the computed complexity of the expressions was not enough to explain it, indicating that other factors need to be investigated. Although some answers to the research questions were not yet conclusive, we consider this research relevant because it points to directions for the work in order to minimize the cognitive processing and mental load of the synthesized speech rendering of mathematical expressions. © 2022 IEEE.

关键词： Eye tracking

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Deep Learning Model for Classifying Public Opinions on Energy Sector IHSG Stocks on the Twitter Social Media Platform

Deep Learning Model for Classifying Public Opinions on Energ...

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2023 International Conference on Artificial Intelligence Robotics, Signal and Image Processing, AIRoSIP 2023

作者： Sulistio, Bambang Heryadi, Yaya Lukas Suparta, Wayan Sonata, Ilvico Binus Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia Universitas Katolik Indonesia Atma Jaya Cognitive Engineering Research Group Jakarta Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta Indonesia

ISBN: (纸本)9798350327472

Capital market transactions provide an opportunity for investors to acquire ownership of company shares and capital gains, as well as dividends. However, alongside the benefits, there are risks of capital loss and liquidation, leading to stress and depression due to profit targets and decision-making errors. To mitigate the risk of decision-making errors in investment, data analysis is needed, including sentiment analysis, which influences stock prices. This study aims to develop a new deep learning model to classify Indonesian public opinion on JCI stocks, especially the Energy sector, obtained from the Twitter social media platform. The model will perform sentiment analysis and categorize opinions as negative, neutral, or positive. We created a dataset that was trained using Bidirectional Encoder Representations from Transformers (BERT) to summarize the analysis of public sentiment above so that it can assist investors in studying public sentiment as a reference for investing with a yield precision of 76%, Recall of 77%, and F1-score on 76%. © 2023 IEEE.

关键词： Tweets

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An Optimal Framework for SDN Based on Deep Neural Network

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Computers, Materials & Continua 2022年第10期73卷 1125-1140页

作者： Abdallah Abdallah Mohamad Khairi Ishak Nor Samsiah Sani Imran Khan Fahad RAlbogamy Hirofumi Amano Samih M.Mostafa Department of Industrial Engineering School of Applied Technical Sciences German Jordanian UniversityAmman35247Jordan School of Electrical and Electronic Engineering Universiti Sains MalaysiaNibong Tebal14300Malaysia Center for Artificial Intelligence Technology Faculty of Information Science and TechnologyThe National University of Malaysia(UKM)Bangi43600SelangorMalaysia Department of Electrical Engineering University of Engineering and TechnologyPeshawar814Pakistan Turabah University College Computer Sciences ProgramTaif UniversityTaif21944Saudi Arabia Research Institute for Information Technology Kyushu UniversityFukuoka819-0395Japan Computer Science-Mathematics Department Faculty of ScienceSouth Valley UniversityQena83523Egypt

Software-defined networking(SDN)is a new paradigm that promises to change by breaking vertical integration,decoupling network control logic from the underlying routers and switches,promoting(logical)network control centralization,and introducing network ***,the controller is similarly vulnerable to a“single point of failure”,an attacker can execute a distributed denial of service(DDoS)attack that invalidates the controller and compromises the network security in *** address the problem of DDoS traffic detection in SDN,a novel detection approach based on information entropy and deep neural network(DNN)is *** approach contains a DNN-based DDoS traffic detection module and an information-based entropy initial inspection *** initial inspection module detects the suspicious network traffic by computing the information entropy value of the data packet’s source and destination Internet Protocol(IP)addresses,and then identifies it using the DDoS detection module based on *** assaults were found when suspected irregular traffic was *** reveal that the algorithm recognizes DDoS activity at a rate of more than 99%,with a much better accuracy *** false alarm rate(FAR)is much lower than that of the information entropy-based detection ***,the proposed framework can shorten the detection time and improve the resource utilization efficiency.

关键词： Deep neural network computer networks data security optimization

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Interpretable Machine Learning for Multi-Class Crop Yield Prediction 3

Interpretable Machine Learning for Multi-Class Crop Yield Pr...

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3rd International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2023

作者： Nurcahyo, Aldian Heryadi, Yaya Lukas Suparta, Wayan Sonata, Ilvico Bina Nusantara University Compuer Science Binus Graduate Program Jakarta Indonesia Jakarta Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta Indonesia Doctor of Computer Science Bina Nusantara University Binus Graduate Program Compuer Science Departement Jakarta Indonesia

ISBN: (纸本)9798350394559

Crop Yield Analysis and Prediction is a fast-expanding discipline that is critical for optimizing agricultural methods. A lack of trustworthy data is one of the challenges in estimating crop yields. We develop predictive models for 22 different fruits and vegetables data. The goals of this study are to create accurate and interpretable crop recommendation models. We used multiple machine learning (ML) models for multi-class crop production prediction to fulfill our research goal. We thoroughly examined the influence of climate and nutrient factors on crop yield, considering their complex interactions. To improve the dataset, augmented data techniques were applied. Configuring the parameters and fine-tuning the hyperparameters is our technique to increase the model performance. Furthermore, we employ explainable artificial intelligence (XAI) techniques and interpretability tools like Shapley Additive exPlanations (SHAP) to improve the interpretability of our prediction model. Our findings reveal that the XGBoost model has the best performance model with 99.86% accuracy, followed by SVM Poly Kernel with 99.32% and Random Forest with 98.82%. Feature selection and analysis are emphasized, particularly in regional agricultural contexts. This study contributes to the creation of accurate and interpretable crop recommendation models while also addressing the issue of untrustworthy data, providing useful insights for optimizing agricultural practices. © 2023 IEEE.

关键词： Forecasting

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Effect of Community-Based Total sanitation program with diarrhea Incidents in toddler at communities near rivers

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Materials Today: Proceedings 2022年 63卷 S349-S353页

作者： Purnama Sari Indah, Fenita Cardiah, Tita Rahmat, Azwar Sulandjari, Kuswarini Andiyan, Andiyan Hendayani, Nenden Departement of Public Health STIKes Widya Dharma HusadaTangerang Banten 15417 Indonesia Interior Design School of Creative Industries Telkom University West Java Bandung 40257 Indonesia Madrasah Ibtidaiyah Teacher Education Study Program Faculty of Tarbiyah State Islamic University of Fatmawati Sukarno Bengkulu Bengkulu Bengkulu 38211 Indonesia Agribusiness Study Program Faculty of Agriculture Universitas Singaperbangsa Karawang West Java Karawang 41361 Indonesia Architecture Study Program Faculty of Science and Engineering Universitas Faletehan West Java Bandung 40266 Indonesia Digital Business Study Program Universitas Sali Al-Aitaam West Java Bandung 40287 Indonesia

The objective of this study was to determine the determinants between Community-Based Total Sanitation and the incidence of diarrhea in toddler at communities near rivers. This study used a quantitative approach with cross sectional design. The sample consisted of 76 mothers who have toddler with the sampling technique by accidental sampling. Primary data obtained directly from interviews using questionnaires and direct observation to respondents. The independent variable was Community-Based Total Sanitation which includes the behavior of open defecation, drinking water and food management, household waste management, and household waste water management. The results showed that only household wastewater management was significant with the incidence of diarrhea in toddlers (p value 0,0000;OR 5,2), while, open defecation (p value 0.118), drinking water and household food management (p value 1,000), household waste management (p value 0,979) was not related to the incidence of diarrhea in toddlers. Toddlers in households with poor wastewater treatment were 5,2 times more likely to have diarrhea. The conclusion is household wastewater management was significant with the incidence of diarrhea in toddlers, so that innovative efforts are needed so that the community improves their waste management. This is useful for preventing the occurrence of diarrhea in toddlers. © 2022

关键词： Sanitation

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