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Empirical mode decomposition of near-infrared spectroscopy signals for predicting oil content in palm fruits

Information Processing in Agriculture 2023年第3期10卷 289-300页

作者： Inna Novianty Ringga Gilang Baskoro Muhammad Iqbal Nurulhaq Muhammad Achirul Nanda Computer Engineering Study Program College of Vocational StudiesIPB UniversityBogor 16680Indonesia Informatics Management Study Program College of Vocational StudiesIPB UniversityBogor 16680Indonesia Technology and Plantation Production Management Study Program College of Vocational StudiesIPB UniversityBogor 16680Indonesia Department of Agricultural and Biosystem Engineering Faculty of Agro-Industrial TechnologyUniversitas PadjadjaranJatinangor 45363Indonesia

Oil content estimation in palm fruits is a precious property that significantly impacts oil palm production,starting from the upstream and *** content can be used to monitor the progress of the oil palm fresh fruit bunch(FFB)and be applied to identify product *** on the near-infrared(NIR)signals,this study proposes an empirical mode decomposition(EMD)technique to decompose signals and predict the oil content of palm ***,350 palm fruits with Tenera varieties(Elaeis guineensis ***),at various ages of maturity,were harvested from the Cikabayan Oil Palm Plantation(IPB University,Indonesia).Second,each sample was sent directly to the laboratory for NIR signal measurements and oil content ***,the EMD analysis and arti-ficial neural network(ANN)were employed to correlate the NIR signals and oil ***,a robust EMD-ANN model is generated by optimizing the lowest possible *** on performance evaluation,the proposed technique can predict oil content with a coefficient of determination(R2)of 0.933±0.015 and a root mean squared error(RMSE)of 1.446±*** results demonstrate that the model has a good predictive capacity and has the potential to predict the oil content of palm fruits directly,without neither solvents nor reagents,which makes it environmentally ***,the proposed technique has a promising potential to be applied in the oil palm *** like this will lead to the effective and efficient management of oil palm production.

关键词： Artificial neural network Empirical mode decomposition Oil palm Oil content prediction

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Unraveling Game Addiction Behavior Among Digital Native Students: Leveraging Machine Learning for Insights 13

Unraveling Game Addiction Behavior Among Digital Native Stud...

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13th IEEE International Conference on Communication, Networks and Satellite, COMNETSAT 2024

作者： Amriza, Rona Nisa Sofia Fadhilla, Cut Alna Telkom University Department of Information System Purwokerto Indonesia Universitas Samudra Informatics Study Program Faculty of Engineering Aceh Indonesia

ISBN: (纸本)9798350368086

The allure of gaming often leads to excessive engagement, which can result in addictive and problematic behaviors, negatively impacting academic performance and school achievements. While gaming becomes increasingly prevalent, concerns about game addiction have grown, particularly among students. The excessive and obsessive usage of video games that characterizes game addiction can have detrimental effects like academic deterioration, social isolation, and mental health problems. This study seeks to elucidate the complex patterns of game addiction among digital-native students by utilizing advanced machine learning techniques. We employed Random Forest, SVM, Decision Tree, and Naïve Bayes algorithms to classify game addiction data from students. To address the class imbalance, we applied Borderline-SMOTE. Our results demonstrate that decision tree and random forest outperformed other machine learning approaches, achieving an accuracy of 95% in classifying game addiction. These findings contribute to the expanding body of knowledge on game addiction. Furthermore, in order to provide real-time monitoring and intervention for students who are at risk of developing a game addiction, future research may investigate incorporating these findings into educational platforms or applications. © 2024 IEEE.

关键词： Adversarial machine learning

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IoT-Integrated Machine Learning for Real-Time Soil Nutrient Monitoring and Horticultural Crop Recommendations 10

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

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10th IEEE Information Technology International Seminar, ITIS 2024

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

ISBN: (纸本)9798331521295

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. © 2024 IEEE.

关键词： pH sensors

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Aircraft Flight Schedule Announcement at Pionir Indonesian Airport Based on SMS Broadcast 1

Aircraft Flight Schedule Announcement at Pionir Indonesian A...

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1st International Conference of Adisutjipto on Aerospace Electrical engineering and informatics, ICAAEEI 2024

作者： Kusumaningrum, Anggraini Wahyu, Septian Sahal, Ahmad Pujiastuti, Asih Ayuningtyas, Astika Pratiwi, Elizabeth Anna Adisutjipto Institute of Aerospace Technology Informatics Study Program Yogyakarta Indonesia Adisutjipto College of Technology Informatic Engineering Department Yogyakarta Indonesia Respati University D3 Information Technology Study Program Faculty of Science and Technology Yogyakarta Indonesia Adisutjipto Institute of Aerospace Technology Aerospace Engineering Study Program Yogyakarta Indonesia

ISBN: (纸本)9798331507930

The design and construction of delivering announcements using a web-based SMS gateway aims to help overcome problems that often occur at pioneer airports;this is because when passengers want to travel, many passengers still arrive late to check-in, even though the passenger ticket has a notification for checking. -in 1 hour before Departure. If a flight's Departure is delayed or accelerated, passengers will only receive this information when they arrive at the airport, whereas if at the time the departure notification is delayed or accelerated, the passenger is still outside the airport or still on their way to the airport, as a result, they will definitely not receive the information. Testing voice announcements on parking, arrival, departure, delay, check-in, and waiting room services, as well as testing SMS broadcasts (30 user numbers and one airline), shows that the announcement application provides information through voice data recording and broadcasts SMS to passengers and families. Testing was carried out at Indonesian Pioner airport for 30 passengers for a week. The percentage of Ease of obtaining test voice information was 81.98%, and the percentage of Ease of obtaining broadcast SMS information was 83.1%. Implementing the announcement is feasible at pioneer airports with a percentage of 82.54%. © 2024 IEEE.

关键词： Text messaging

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Design of an Infusion Capacity Monitoring System for Patients Based on the Internet of Things in Hospitals 9

Design of an Infusion Capacity Monitoring System for Patient...

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9th International Conference on Business and Industrial Research, ICBIR 2024

作者： Windyasari, Vina Septiana Murad, Silvia Ayunda Syam, Syahriani Mahardika, Maulia Budiman, Johan Rahmawati, Diah Islamic Syekh-Yusuf University Information Systems Study Program Tangerang Indonesia Binus University Binus Online Learning Information System Department Jakarta Indonesia Islamic Syekh-Yusuf University Informatics Engineering Study Program Tangerang Indonesia Islamic Syekh-Yusuf University Civil Engineering Study Program Tangerang Indonesia

ISBN: (纸本)9798350383010

The patient's infusion fluid will only be changed if the nurse changes it or based on information from the patient's family. The research method used in terms of fluid volume utilizes the function of the Arduino microcontroller as the brain, the load cell sensor as an infusion fluid weight detector connected to the IoT, fuzzy logic calculations on the infusion volume weight measuring device in line with real-time decision-making when reading gram weight changes with sensors, and the system development method using a prototype model. The test results of three infusion bottles containing mineral water with a liquid volume of 500 ml and a load cell sensor as an infusion weight detector can be accepted by the Arduino Wemos D1 as a load cell sensor processing component. The infusion liquid weight data is uploaded to the MySQL database, and a notification is sent and displayed on the smartphone when the infusion volume reaches 12% of its weight. The results of this study indicate that the design of tools connected to applications on smartphones can work well and facilitate the process of monitoring infusions for patients in real-time © 2024 IEEE.

关键词： Smartphones

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Fine-Tuned Attribute Weighted Naïve Bayes with Modified Partial Instances Reduction for Gaming Disorder Classification

HighTech and Innovation Journal

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HighTech and Innovation Journal 2025年第1期6卷 67-80页

作者： Latubessy, Anastasya Wardoyo, Retantyo Musdholifah, Aina Kusrohmaniah, Sri Doctoral Program Department of Computer Science and Electronics Faculty of Mathematics and Natural Science Universitas Gadjah Mada Yogyakarta55281 Indonesia Department of Informatics Engineering Faculty of Engineering Universitas Muria Kudus Indonesia Department of Computer Science and Electronics Faculty of Mathematics and Natural Science Universitas Gadjah Mada Yogyakarta55281 Indonesia Department of Psychology Faculty of Psychology Universitas Gadjah Mada Yogyakarta55281 Indonesia

Fine Tuning Attribute Weighted Naïve Bayes (FTAWNB) is a reliable modified Naïve Bayes model. Even though it is able to provide high accuracy on ordinal data, this model is sensitive to outliers. To improve the performance of FTAWNB, this research modified the Partial Instances Reduction (PIR) technique to make the FTAWNB more adaptive to outliers. Nevertheless, in contrast to the original PIR technique, which substitutes missing values for data values deemed outliers, the PIR technique suggested in this study replaces data values deemed outliers using a Naïve Bayes weighting approach. The attribute values from the outlier data are replaced with the highest probability values for the attributes in the actual class. This PIR technique is referred to as modified PIR. The FTAWNB model with modified PIR has been evaluated using the Gaming Disorder dataset. Replacing the four attributes with the least amount of information resulted in accuracy gains of 99.74%, an increase of 1.53% over the FTAWNB model. The experimental result shows that adding the modified PIR technique to the FTAWNB model can handle the outlier in the data, proving it by increasing the performance in terms of accuracy, precision, and recall without pruning the dataset used. © 2025, Ital Publication. All rights reserved.

关键词： Attribute Weighted Classification Fine-Tune Gaming Disorder Instances Reduction Naïve Bayes

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Javanese Script Single Letters Classification using GoogLeNet Architecture and Adam Optimizer Based on Convolutional Neural Networks (CNN)

Javanese Script Single Letters Classification using GoogLeNe...

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2023 International Seminar on Application for Technology of Information and Communication, iSemantic 2023

作者： Susanto, Ajib Sari, Christy Atika Mulyono, Ibnu Utomo Wahyu Rachmawanto, Eko Hari Setiadi, De Rosal Ignatius Moses Ali, Rabei Raad University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia Northern Technical University Department of Computer Engineering Technology Mosul Iraq

ISBN: (纸本)9798350339215

This study examines the decline in the usage of the Javanese language, which has experienced a decrease in the number of speakers from approximately 82 million in 2007 to 68.2 million in 2015. The convergence of the Javanese script and Optical Character Recognition (OCR) technology is proposed as a solution, allowing for the preservation and accessibility of the Javanese script in the digital age. The integration of Convolutional Neural Networks (CNNs) in Javanese script classification achieved a high accuracy rate of 92.95% in identifying positive and negative cases. The dataset used for training consisted of 8440 sample images, which were divided into 20 subfolders for training and testing. The results presented in Table IV demonstrate the successful implementation of the classification model, achieving a 98.87% sensitivity, 100% precision, and 98.88% specificity. This research contributes to the preservation and understanding of the culturally significant Javanese script while addressing the decline in its usage. © 2023 IEEE.

关键词： Convolutional neural networks

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White Bread Mold Detection using K-Means Clustering Based on Grey Level Co-Occurrence Matrix and Region of Interest

White Bread Mold Detection using K-Means Clustering Based on...

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2023 International Seminar on Application for Technology of Information and Communication, iSemantic 2023

作者： Putra, Qori Alfatah Sari, Christy Atika Rachmawanto, Eko Hari Cahyo, Nur Ryan Dwi Mulyanto, Edy Alkhafaji, Mohamed Ayad University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia University of Dian Nuswantoro Department of Informatics Engineering Semarang Indonesia National University of Science and Technology Department of Computer Science DhiQar Iraq

ISBN: (纸本)9798350339215

This research paper presents a bread mold identification system that utilizes digital image processing techniques, specifically K-means clustering and thresholding, to accurately detect and classify mold-infected areas on bread. The system aims to provide valuable information regarding the safety of consuming mold-contaminated bread, enabling consumers to make informed decisions and reduce the risk of health issues associated with consuming mold-infested bread. the K-means clustering algorithm for mold classification, considering factors such as the number of iterations and the distance metric within the feature space to determine its accuracy. The GLCM feature extraction technique is employed to extract texture information from bread images, encompassing features such as standard deviation (110.62), contrast (1.46), energy, and homogeneity (0.96 and 0.77, respectively). Experimental results demonstrate that the Euclidean Distance yielded the highest result of 72.73, the Cosine Distance obtained the highest result of 8.25, and the City Block Distance obtained the highest result of 92.11. These findings showcase the effectiveness of the system in accurately detecting and classifying mold-infected areas on bread, thereby aiding in ensuring food safety and reducing health risks for consumers. © 2023 IEEE.

关键词： Image segmentation

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Smart Electrical Devices Control with Intrusion Detection Alert

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2022年第5期16卷 139-152页

作者： Achmad, Andani Muliadi Areni, Intan Sari Palantei, Elyas Hadis, Muhammad Sabirin Department of Electrical Engineering Faculty of Engineering Universitas Hasanuddin Gowa Indonesia Department of Electrical Engineering Education Faculty of Engineering Universitas Negeri Makassar Indonesia Study Program of Informatics STMIK AKBA Makassar Indonesia

The consumption profile of electrical energy always increases every year due to the highly consumptive and inappropriate lifestyles of modern society. A bad lifestyle such as forgetting to turn off the unused electronic devices when they are leaving home is one of the factors influenced the increasing consumption of electrical energy. This is off course contributing in wasting energy. In the paper, an IoT-based electronic device control system has been successfully constructed. Monitoring and control tasks could be performed remotely and in real time mode using an interface application installed on a smartphone. The system built is equipped with a device operational condition monitoring featured by placing light, temperature, thermal and current sensors, respectively. Through the utilization of the implemented system, users can monitor and control electronic devices easily and can figure out the condition of the device remotely in a real time mode. The control test on the system was successful with an average response time of approximately 3.32 seconds and the accuracy of sensor readings above 89%. With the implementation of this system, users can easily monitor and control electronic devices anywhere and anytime so that the opportunities for efficient and effective use of electrical energy could be further optimized. © 2022. All Rights Reserved.

关键词： Energy efficiency

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The use of Carica papaya seeds as bio coagulant for laundry wastewater treatment

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Journal of engineering and Applied Science 2024年第1期71卷 99页

作者： Vezar, Siti Alfinna Naulita Belinda, Zeriyatina Tri Rendana, Muhammad Agustina, Tuty Emilia Nasir, Subriyer Hanum, Laila Andarini, Desheila Undergraduate Student of Chemical Engineering Program Faculty of Engineering Universitas Sriwijaya Sumatra Selatan Indralaya30662 Indonesia Chemical Engineering Program Faculty of Engineering Universitas Sriwijaya Sumatra Selatan Indralaya30662 Indonesia Biology Department Faculty of Mathematics and Natural Sciences Universitas Sriwijaya Sumatra Selatan Indralaya30662 Indonesia Public Health Program Study Faculty of Public Health Universitas Sriwijaya Sumatra Selatan Indralaya30662 Indonesia

The study aims to analyze the effectiveness of wastewater treatment by using Carica papaya seeds as bio coagulants to diminish total suspended solids (TSS) and excess phosphate. This method has some advantages because it does not use chemical materials, is simple to apply, and is safe for the environment and human health. The wastewater samples were taken from an active laundry site in Palembang City, South Sumatra Province of Indonesia. The study found that the best dosage of coagulant was 3 g for the wastewater samples. The pH and BOD parameters showed slight changes after treatment, with pH 7.63–7.19 and 33–27 mg/L values, respectively. The TSS removal efficiency ranged from 9.3 to 15.6%, while the COD and phosphate removals were obtained from 11.7 to 39.3% and 56.3 to 68.4%, respectively. The treated TSS, COD, and phosphate concentrations have met the Indonesian domestic wastewater quality standard and environmental protection organization (EPO) guidelines. In addition, the statistical analysis and t-test showed significant differences (p © The Author(s) 2024.

关键词： Wastewater treatment

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