{"title":"Color Feature Extraction of Fingernail Image based on HSV Color Space as Early Detection Risk of Diabetes Mellitus","authors":"I. Kurniastuti, T. D. Wulan, Ary Andini","doi":"10.1109/ICOMITEE53461.2021.9650161","DOIUrl":"https://doi.org/10.1109/ICOMITEE53461.2021.9650161","url":null,"abstract":"Fingernail image color could be used for health diagnosis, such as detecting pancreatic condition as an indicator presence of diabetes mellitus risk. This paper focused on fingernail images as an early detection risk of diabetes mellitus. Therefore. the study aimed to analyze color features of fingernail images based on HSV (Hue, Saturation, Value) color space. The research data used fingernail images which were divided into three categories including normal, prediabetes, and diabetes data that according to blood glucose level. The data was cropped and extracted to each component of HSV color space. Analysis data was applied by grouping frequency distribution. The results revealed that among components of HSV, hue and value were overlapped between prediabetes and diabetes data. Component saturation had different range numbers in normal, prediabetes, and diabetes data. Therefore, it could be concluded that the HSV channel was considered as early detection of Diabetes Mellitus risk with fingernails image color as an object assay.","PeriodicalId":250516,"journal":{"name":"2021 International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122250339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Herlambang, D. Rahmalia, D. Karya, Fajar Annas Susanto, F. Yudianto, O. S. Suharyo
{"title":"Optimal Control Model of Two Dimensional Missile Using Forward Backward Sweep Method (FBSM)","authors":"T. Herlambang, D. Rahmalia, D. Karya, Fajar Annas Susanto, F. Yudianto, O. S. Suharyo","doi":"10.1109/ICOMITEE53461.2021.9650094","DOIUrl":"https://doi.org/10.1109/ICOMITEE53461.2021.9650094","url":null,"abstract":"Indonesia is an archipelagic and maritime country, so it is imperative to improve the country's aerospace technology, that is, the main equipment of defence system to defend the state sovereignty. One example is a missile that can be remotely controlled. Missiles are military rocket weapons with automatic control system to trace targets or follow direction. One of the missile technologies currently being developed is the optimal control of missile. The application of optimal control by Forward Backward Sweep Method (FBSM) method can be used for missile model consisting of flight angle, speed, horizontal position, and altitude with thrust force as control. FBSM uses state variable and adjoint variable in its computation. Then, FBSM updates the control by current control and new control. Based on the simulation results, the comparison between the missile model with thrust force control and without thrust force control are obtained. The flight angle with control produces smaller deviation than the flight angle without control. The altitude with control produces increasing trajectory while the altitude without control produces decreasing trajectory.","PeriodicalId":250516,"journal":{"name":"2021 International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128287534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"ICOMITEE 2021 Other Reviewers","authors":"","doi":"10.1109/icomitee53461.2021.9650085","DOIUrl":"https://doi.org/10.1109/icomitee53461.2021.9650085","url":null,"abstract":"","PeriodicalId":250516,"journal":{"name":"2021 International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121290482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Implementation of PCA and KNN Algorithms in the Classification of Indonesian Medicinal Plants","authors":"Rohmat Indra Borman, Riduwan Napianto, N. Nugroho, Donaya Pasha, Yuri Rahmanto, Yohanes Egi Pratama Yudoutomo","doi":"10.1109/ICOMITEE53461.2021.9650176","DOIUrl":"https://doi.org/10.1109/ICOMITEE53461.2021.9650176","url":null,"abstract":"Maintaining and increasing body immunity in the midst of the Covid-19 pandemic needs to be done so that the risk of contracting this disease can be reduced. One way to increase immunity is to consume herbs or medicinal plants. Since ancient times, plants have been used as medicine and are still used today. Medicinal plants are a wide range of plants that are known to have great properties in assisting with keeping up with wellbeing and treat an infection. But many people do not know the characteristics and forms of these plants. This study performs image classification of Indonesian medicinal plants using a combination of PCA and CNN. PCA is used as a feature extraction based on the characteristics formed from each spatial property and is utilized for grouping of items dependent on learning information that has the nearest distance to the object. This investigation obtained the results that the image classification of the application of PCA and KNN on Indonesian medicinal plants with an accuracy of 88.67%.","PeriodicalId":250516,"journal":{"name":"2021 International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE)","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115789546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Application The Method Direct Effect Piezoelectric (DEP) Using Vibrator Engine Diesel","authors":"B. S. Kaloko, Widjonarko, Zulfikar Febrian","doi":"10.1109/ICOMITEE53461.2021.9650118","DOIUrl":"https://doi.org/10.1109/ICOMITEE53461.2021.9650118","url":null,"abstract":"In this study using the piezoelectric direct effect (DEP) method. The existence of this method can be used to generate voltages and currents from the piezoelectric. From these data, it can be divided between series and parallel circuits to carry out the battery charging process using a diesel engine vibration. The results of this experiment, namely by using a series arrangement will get a good voltage up to a value of 10.5 volts with a voltage drop of about 3 volts so that the resulting current is about 30 mA. When using a parallel circuit the resulting voltage is less than 0.8 volts so that the battery is not filled. The estimated time taken for the research process is 50 minutes with an average power output of around 90.91 mW so that the value of the mAh is about 19.38 mAh.","PeriodicalId":250516,"journal":{"name":"2021 International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133523450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Evi Febrion Rahayuningtyas, Galih Wasis Wicaksono, Didih Rizki Chandranegara
{"title":"Prediction of Yuan to IDR Exchange Rate using General Regression Neural Network","authors":"Evi Febrion Rahayuningtyas, Galih Wasis Wicaksono, Didih Rizki Chandranegara","doi":"10.1109/ICOMITEE53461.2021.9650304","DOIUrl":"https://doi.org/10.1109/ICOMITEE53461.2021.9650304","url":null,"abstract":"The exchange rate is the value or price of a currency in front of other currencies divided into selling rates and buying rates. The differences and alteration of exchange rates are caused by interest rates, inflation, and many other factors. The General Regression Neural Network method is applied to build a prediction system for the Yuan to IDR exchange rate, using the input to determine the output. The dataset is taken from the Bank Indonesia website with 191 records after pre-processing. Based on the resulting test, we found that the MSE score is 106.13, the RMSE score is 10.30, and the MAE score is 8.73. The model can find and recognize training data patterns to provide excellent data output with the results given.","PeriodicalId":250516,"journal":{"name":"2021 International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117258284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"ICOMITEE 2021 Author Index","authors":"","doi":"10.1109/icomitee53461.2021.9650287","DOIUrl":"https://doi.org/10.1109/icomitee53461.2021.9650287","url":null,"abstract":"","PeriodicalId":250516,"journal":{"name":"2021 International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124525905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Detection Hand Tremor Through Each Finger Movement Based On Arduino For Parkinson’s Patients","authors":"Eka Mistiko Rini, Endi Sailul Haq","doi":"10.1109/ICOMITEE53461.2021.9650157","DOIUrl":"https://doi.org/10.1109/ICOMITEE53461.2021.9650157","url":null,"abstract":"Parkinson’s disease, which is often characterized by tremors in a person’s body, indicates that there has been a decline in brain function. However, not all the appearance of tremor symptoms can be classified as someone suffering from Parkinson’s disease. The characteristics of Parkinson’s disease vary widely, one of which is resting tremor, rhythmic vibration of 4 to 6 Hz in the fingers, arms, and even in the legs. This study proved that a smart glove could measure and monitor resting tremors in the fingers. Five IMU MPU6050 sensors are placed on each fingertip. An Arduino microcontroller processes raw data into frequency values and sends it to a mobile application via Bluetooth communication. The device was tested on the right hands of several healthy people and patients with Parkinson’s disease. The results showed that the built device could identify tremors in each finger and convert the tremor value into frequency. Based on tremor reading data from several patients, it was found that the index finger always has a significantly higher frequency value which theoretically means the index finger has a more significant relationship with the brain than the other fingers. However, further research is needed to prove it.","PeriodicalId":250516,"journal":{"name":"2021 International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128821271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Raihan Natigor Tarigan, Reny Nadlifatin, A. P. Subriadi
{"title":"Academic Dishonesty (Cheating) In Online Examination: A Literature Review","authors":"Raihan Natigor Tarigan, Reny Nadlifatin, A. P. Subriadi","doi":"10.1109/ICOMITEE53461.2021.9650082","DOIUrl":"https://doi.org/10.1109/ICOMITEE53461.2021.9650082","url":null,"abstract":"Currently, it is an era that is closely related to information and communication technology. The existence of information and communication technology also has a significant impact on human life today. Many studies have shown a good effect on the use of information and communication technology currently widely applied in Education. Still, it is unfortunate that the perceived benefits are not in line with the gaps that can be a weakness in Education. One of the uses of Information and Communication Technology in Education is implementing academic evaluations conducted online. Still, this is a gap for some people to commit fraudulent actions such as Cheating when running an online assessment. This paper aims to find out what factors can influence someone to cheat during an online exam. To find out what factors can influence someone to cheat during an online exam, the researcher conducted a Literature Review from various sources that discussed Cheating in the world of Education. What factors can influence someone to cheat during an online exam that is collected from some of the literature found.","PeriodicalId":250516,"journal":{"name":"2021 International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133128255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Sentiment Analysis Of Online Lecture Opinions On Twitter Social Media Using Naive Bayes Classifier","authors":"Devi Ajeng Damaratih","doi":"10.1109/ICOMITEE53461.2021.9650135","DOIUrl":"https://doi.org/10.1109/ICOMITEE53461.2021.9650135","url":null,"abstract":"Sentiment analysis is a depiction of polarity in a text or word. Sentiment analysis is a form of expression of an individual or group in a particular problem. Sentiment analysis basically works to group the text in a sentence or document into positive and negative forms. The Naïve Bayes Classifier is a simple probabilistic classification method that calculates a set of probabilities by adding up the frequencies and combination of values from a given dataset. In this study, the classification process is divided into two classes, namely positive and negative. From a dataset of 1004, the results obtained accuracy of 62% with 2 scenarios, namely 70:30 and 80:20.","PeriodicalId":250516,"journal":{"name":"2021 International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130588354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}