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The Online Test application uses Telegram Bots Version 1.0 3

The Online Test application uses Telegram Bots Version 1.0

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3rd International Conference on Science and Technology 2019, ICST 2019

作者： Parlika, Rizky Pratama, Arista Informatics Engineering Study Program Faculty of Computer Science Indonesia Information Systems Study Program Faculty of Computer Science National Development University Veteran East Java Raya Rungkut Madya Road Gunung Anyar Surabaya Indonesia

The development of the smartphones that rapidly increasing, and high smartphone Users as a tool to make a lot of information, make emergence of instant messaging applications with a variety of options for use. Telegram, as one of the instant messaging application that is fairly new, offering in its various features compared to other instant messaging applications, so it can grow rapidly and much in demand in only 2 years. One of the interesting features is the Bot telegram, a special account without number that can handle Command from the User and gives answers appropriate to Command functionality. The account serves as the interface of the running system that communicate via Telegram Bot API. This study seeks to build a Bot telegram with database to built The Online Test application uses Telegram Bots Version 1.0. In each lecture meeting, a Lecturer can make a short test in the form of multiple choices to review the material at the previous meeting and get information about what percentage of students understand the material that has been taught before. We can use the application to send realtime messages to facilitate the test. Of course, which supports the creation of bots easily to add features that did not yet exist. Of the many we chose Telegram to be an online test environment by utilizing the Bot creation facilities provided by Telegram. This article will be a guide that makes it easier for lecturers to give a simple test at the beginning of the meeting, so that they can attract students' daily grades. And in order to be more interactive there are features of student value progress reports that can also be accessed individually so that students can know the progress of their learning outcomes. © Published under licence by IOP Publishing Ltd.

关键词： Students

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Optimization of Certainty Factor Algorithm to Overcome Uncertainty in Expert System Identification of Pests and Diseases of Cocoa 2

Optimization of Certainty Factor Algorithm to Overcome Uncer...

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

作者： Gunawan, Rakhmat Dedi Ahmad, Imam Parjito Anggono, Harry Vernando, Ego Hengki Jaya, Firman Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Bandarlampung Indonesia Stkip Pgri Information Technology Education Study Program Situbondo Indonesia

ISBN: (纸本)9781665465410

Lampung Province is one of the regions with the highest cocoa production, but many factors can interfere with cocoa production. One of them is the factor of pests and diseases of cocoa that cannot be identified and prevented beforehand. An expert system is a system that adopts expert knowledge or experts in a particular field. However, the diagnosis usually contains uncertainty in the form of answers and statements used. Certainty Factor (CF) algorithm, is one of the algorithms that is able to overcome uncertainty by providing a value for the level of trust from experts and users. However, because the CF value is based on the level of confidence in the symptoms experienced by the user, it creates a problem, namely the consistency of the user's answers. So, it is necessary to make improvements to the CF algorithm, to overcome the inconsistency of user answers through the use of Consistency Ratio (CR). Through the use of CR, inconsistencies are overcome through comparisons between the consistency index and the random index. Based on the results of the accuracy test, the proposed model is able to produce an accuracy rate of 86.67% in the diagnosis of pests and diseases on cocoa plants. © 2022 IEEE.

关键词： Cocoa

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Biomedical Image Quality Improvement with Spatial Domains 2

Biomedical Image Quality Improvement with Spatial Domains

引用

2nd International Conference on Innovative and Creative information Technology, ICITech 2021

作者： Fernando, Erick Siagian, Pandapotan School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Computer Engineering Study Program Del Institute of Technology Faculty of Informatics and Electrical Engineering North Sumatera22381 Indonesia

ISBN: (纸本)9781728197463

Digital image processing aims to improve the quality of an original image so that it can display an image that is relatively better than the original image, so as to obtain the detailed information needed for an analysis need. Quality degradation Biomedical images in computerization usually experience changes in brightness, blur, and contrast stretching. Because of the deterioration in the image quality, doctors and patients cannot obtain the information needed for analysis, therefore the need for biomedical image processing techniques with spatial domain methods to improve the quality and details of information in the image so that it helps doctors in diagnosing. Data analysis is biomedical images like X-ray images, CT-Scan (Computer Tomographic Scan) images, and USG (Ultrasound Graphic) images. A focused study on improving image quality can be done with digital spatial domain image processing techniques. Digital domain image processing is digital image processing based on the manipulation of pixel values in the image directly, in the form of point processing and mask processing. Process testing for each image for Blur level is CT-scan images with a value of 0.98436, ultrasound images with a value of 0.9875, X-ray images with a value of 0.9836. This value is blur level value get near to 1 which means the image becomes clearer. The analysis results prove that the spatial domain method can clarify the object image in this study. The biomedical image quality processing model is proven to be able to improve the quality of the image that is declining due to the digitization process and assist the user in analyzing the biomedical image. © 2021 IEEE.

关键词： Image quality

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Smartphone Application As An Air Quality Monitor Using Raspberry Pi for Reducing Air Pollution 2

Smartphone Application As An Air Quality Monitor Using Raspb...

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2nd International Conference on Innovative and Creative information Technology, ICITech 2021

作者： Siagian, Pandapotan Fernando, Erick Computer Engineering Study Program Del Institute of Technology Faculty of Informatics and Electrical Engineering North Sumatera22381 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia

ISBN: (纸本)9781728197463

Good air quality is very important in human health. However, air pollution has been polluted everywhere, whether in the house, in cities. This is caused by a growing industry that produces air pollution. Room air pollution and various cities will contribute to air pollution, which will cause problems for human health. This work measures the carbon monoxide level using the MQ-7 sensor and measures the air's carbon dioxide level with the CCS811 sensor and MH-Z19 sensor. All three sensors are connected to the NodeMCU ESPS266, and we call it a NodeMCU module. Tests are carried out in three rooms in the house, and then three NodeMCU modules are used so that the three modules will send data alternately. Raspberry Pi3 (RPi3) functions as a server that collects data and acquires information data from sensors. Data from the CCS811 (TCOV) sensor, MH-Z19 (co2), will be processed first with fuzzy logic rules to make decisions about CO2, which are right, moderate, nasty conditions. The process is carried out on the Raspberry Pi 3 server with MQTT using publication, customer, fuzzy logic, and broker services. The value of the sensor's measurement results can be accessed via a smartphone and provides good air control values. © 2021 IEEE.

关键词： Air quality

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Long Short Term Memory Networks for Stroke Activity Recognition base on Smartphone 5

Long Short Term Memory Networks for Stroke Activity Recognit...

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5th IEEE International Conference on information Technology, information Systems and Electrical engineering, ICITISEE 2021

作者： Siagian, Pandapotan Fernando, Erick Del Institute Of Technology Faculty Of Informatics And Electrical Engineering Computer Engineering Study Program North Sumatera 22381 Indonesia Bina Nusantara University School Of Information Systems Information Systems Department Jakarta11480 Indonesia

ISBN: (纸本)9781665401968

Aims this study to analyze rehabilitation exercises using sensor data embedded in smartphones is widely used to recognize human activities regularly to gain a better understanding of human behavior. However, it is rarely used to measure accelerators of patient movement in hospital wards. This paper proposes an optimized neural network-based feature extraction approach based on the Long Short Term Memory technique to recognize human activity using data from a tri-axial accelerometer. The activity to be measured is the Range of Motion for patient rehabilitation, and rehabilitation exercises are one of the most important steps for recovery. The results of the softmax regression trained on the dataset set have 1, 076, 105 records and 12 class attributes (class distribution). The experimental results on the SAR dataset show that our Long Short Term Memory-based approach is practical and successful, with an accuracy of 89.74%. © 2021 IEEE.

关键词： Smartphones

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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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Android Based Heart-rate Monitoring System using ECG Sensor 2

Android Based Heart-rate Monitoring System using ECG Sensor

引用

2nd International Conference on Sustainable engineering and Creative Computing, ICSECC 2020

作者： Rosalina Selina, Grace Mandala, Rila Faculty of Computing Information Technology Study Program President University Bekasi Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia

ISBN: (纸本)9781728175881

This research aims to help the user monitor their heart’s condition and notify other people in case of an emergency due to an abnormal heartbeat (normal heartbeat around 60-100 beats per minute). From the heart rate graph, the user could do a consultation with an expert in the nearest hospital using a map feature that will show the nearest hospital with a 1 KM radius from the user’s current location. The heart is undeniably an essential part of the human body system. The heart's missions are to pump blood to the lungs to expel the waste carbon dioxide that resulted from the respiration and pump blood that will deliver oxygen throughout the human body's circulation system. While the blood that carries oxygen being pumped throughout the human body, the heart will provide the oxygen to all cells. Body cells need to use oxygen to get the energy from food through a process called cellular respiration. Monitoring our heartbeat and pulse rate can increase people’s awareness about their heart’s health, motivating, and encouraging people to maintain a healthy eating plan and exercise. This research will be implemented ECG Sensor. The sensor will then send the data to the android application via HC-06 Bluetooth module. Monitoring the heart rate and analyzing the user’s heartbeat will be done in the android with a microcontroller device's help. © 2020 IEEE.

关键词： Electrocardiograms

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Mammogram Breast Cancer Classification Based on Deep-Convolutional Neural Network

Mammogram Breast Cancer Classification Based on Deep-Convolu...

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

作者： Amadea, Avissa Aurellia Sari, Christy Atika Rachmawanto, Eko Hari Sari, Wellia Shinta Noori, Mohammed S. Alkhafaji, Mohamed Ayad University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia University of Dian Nuswantoro Study Program in Information Systems Semarang Indonesia Northern Technical University Department of Computer Engineering Technology Mosul Iraq National University of Science and Technology Department of Computer Science DhiQar Iraq

ISBN: (纸本)9798350339215

Based on WHO's data, breast cancer is one of the most deadly diseases that has claimed many victims, especially women. This disease begins with the presence of an undetected and eventually turns into malignant (cancer). This happens due to ignorance of the importance of having a medical check-up even though in good health. Doctors and researchers can prevent the development of tumor cells through treatment that begins with radiological examinations to identify the possibility of a person being affected by this disease. One of the most frequently used techniques is Mammography. This technique can detect the presence of tumor cells using advanced technology and several methods in displaying the patient's diagnostic results on low-dose X-rays in the form of mammogram images. The technology is inseparable from the methods used to identify the presence of tumor cells. In this study, we have proposed the CNN method based on the deep-CNN model to identify mammogram images in the detection of breast cancer cells with average evaluation results in terms of accuracy, precision, recall, specificity, and f-measure on mammogram image datasets of 99.52%, 99.72%, 99.31%, 99.72%, and 99.5%. These results showed that this method has a good performance in breast cancer detection. © 2023 IEEE.

关键词： Diseases

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Weed Detection Based on Fine-Tuned YOLOv5 16

Weed Detection Based on Fine-Tuned YOLOv5

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16th International Conference on information Technology and Electrical engineering, ICITEE 2024

作者： Agustian, Indra Wibirama, Sunu Ardiyanto, Igi Anggraini, Ika Novia Noviansyah, Pariyanto Universitas Gadjah Mada Department of Electrical and Information Engineering Yogyakarta Indonesia Universitas Bengkulu Study Program of Electrical Engineering Bengkulu Indonesia Universitas Gadjah Mada Department of Electrical and Information Engineering Yogyakarta55281 Indonesia Universitas Gadjah Mada Department of Electrical and Information Engineerig Yogyakarta Indonesia

ISBN: (纸本)9798350375817

Conventional weed control often ignores weed locations, potentially causing land damage. AI-based weed detection offers a modern solution. Unfortunately, little attention has been paid to how an augmentation technique improves performance of AI-based weed detection. To address this research gap, we proposed a weed detection model based on fine-tuned YOLOv5 to detect weeds in corn fields aged 1 to 3 weeks. YOLOv5 offers computational benefits, includes auto-augmentation capabilities, and presents a more organized visualization of the outcomes from the training data. The primary dataset used in this study comprised 3,437 images with a total of 18,267 annotated objects, including corn plants and weeds. We observed the effect of mosaic augmentation on the dataset images based on auto-augmentation in YOLOv5. We found that mosaic augmentation with a 0.75 probability outperformed 0.5 and 1.0. The best mAP performance was at the level @0.5 with score of 0.776 for all classes. Meanwhile, the mAP@0.5:0.95 was 0.573 for all classes, indicating that the model's performance requires further improvement. Our study is promising as a guidance for future development of AI-based weed detection. © 2024 IEEE.

关键词： weed deep learning Weed detection weed-yolo yolov5

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Parallel Construction of information Technology Value Model: Design-Science Research Methodology

Parallel Construction of Information Technology Value Model:...

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International Conference of information and Communication Technology (ICoICT)

作者： Lukman Abdurrahman Tatang Mulyana Information Systems Study Program Industrial Engineering Study Program School of Industrial Engineering Telkom University Bandung Indonesia

ISBN: (数字)9781728161426

ISBN: (纸本)9781728161433

To date, the study model of IT value usually takes the form of a serial construction relating its components. This paper tries to offer a parallel construction in modeling the IT value study. The applied methodology is the design-science research approach to create the construction relating its components. To perfect the construct, the paper applies the partial adjustment valuation that functions as an estimating technique to approximate and evaluate the mathematical magnitude of the performing returns of a component compared to the real figures. The developed pattern undertakes a case study with Mandiri's data, an Indonesian state-owned banking industry, shows that the estimated revenue of the parallel configuration has a deviation of only 0.28% when compared with the bank's real revenue during the period 2004-2014. Thus, the parallel configuration may appear as the alternative configuration in the study of IT value as a result of its authenticity academically as well as pragmatically.

关键词： Modeling Resource management FCC Correlation Technological innovation

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