IJCONSIST JOURNALS最新文献_第2页

Digital Image Segmentation Resulting from X-Rays of Covid Patients using K-Means and Extraction Features Method 基于k均值和提取特征的新冠肺炎患者x射线数字图像分割

IJCONSIST JOURNALS Pub Date : 2021-12-28 DOI: 10.33005/ijconsist.v3i1.55

Dhian Satria Yudha Kartika, Anita Wulansari, Hendra Maulana, Eristya Maya Safitri, Faisal Muttaqin

{"title":"Digital Image Segmentation Resulting from X-Rays of Covid Patients using K-Means and Extraction Features Method","authors":"Dhian Satria Yudha Kartika, Anita Wulansari, Hendra Maulana, Eristya Maya Safitri, Faisal Muttaqin","doi":"10.33005/ijconsist.v3i1.55","DOIUrl":"https://doi.org/10.33005/ijconsist.v3i1.55","url":null,"abstract":"The COVID-19 pandemic has significant impact on people's lives such as economic, social, psychological and health conditions. The health sector, which is spearheading the handling of the outbreak, has conducted a lot of research and trials related to COVID-19. Coughing is a common symptoms among humans affected by COVID-19 in earlier stage. The first step when a patient shows symptoms of COVID-19 was to conduct a chest x-ray imaging. The chest x-rayss can be used as a digital image dataset for analysing the spread of the virus that enters the lungs or respiratory tract. In this study, 864 x-rays were used as datasets. The images were still raw, taken directly from Covid-19 patients, so there were still a lot of noise. The process to remove unnecessary images would be carried out in the pre-processing stage. The images used as datasets were not mixed with the background which can reduce the value at the next stage. All datasets were made to have a uniform size and pixels to obtain a standard quality and size in order to support the next stage, namely segmentation. The segmentation stage of the x-ray datasets of Covid-19 patients was carried out using the k-means method and feature extraction. The Confusion Matrix method used as testing process. The accuracy value was 78.5%. The results of this testing process were 78.5% of precision value, 78% of recall and 79% for f-measure","PeriodicalId":163873,"journal":{"name":"IJCONSIST JOURNALS","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124691747","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}

引用次数: 0

Evaluation of the Hospital Information System (HIS ) using EUCS and PIECES Methods on the Medical Record Section of RSUD dr. Haryoto Lumajang 利用EUCS和PIECES方法评价RSUD病案科Haryoto Lumajang医生的医院信息系统(HIS)

IJCONSIST JOURNALS Pub Date : 2021-12-28 DOI: 10.33005/ijconsist.v3i1.57

Arini Farihatul Hanesya, Ancah Caesarina Novi Marchianti, S. Bukhori

{"title":"Evaluation of the Hospital Information System (HIS ) using EUCS and PIECES Methods on the Medical Record Section of RSUD dr. Haryoto Lumajang","authors":"Arini Farihatul Hanesya, Ancah Caesarina Novi Marchianti, S. Bukhori","doi":"10.33005/ijconsist.v3i1.57","DOIUrl":"https://doi.org/10.33005/ijconsist.v3i1.57","url":null,"abstract":"The use of HIS itself in Indonesia is 82.21% of hospitals have adopted HIS and only 15.79% have not adopted HIS. However, the use of SIMRS still uses paperless medical records because there are still several aspects of SIMRS that need to be developed according to user needs. The purpose of this study was to evaluate HIS using the PIECES and EUSC methods. The PIECES method is used to evaluate based on system performance consisting of performance, information, economy, control, efficiency and service variables. The EUSC method is used to evaluate user satisfaction using content, format, acurancy, timeliness and easy of use variables. This type of research is quantitative descriptive and analytic with a sample of 45 people. Descriptive data processing using scoring and analytical using chi square test. Descriptive data processing using scoring and analytical using chi square test. The results of descriptive research using the PIECES method: the performance variable is 69.0%, the information variable is 70.18%, the economy variable is 67.3%, the control variable is 71.4%, the efficiency variable is 72.3%, the service variable is 73. ,2% and all variables included in the good category. The results of analytical research using the End User Computing Satisfaction method found that there are 4 variables that affect user satisfaction, namely content, format, timeliness and easy of use, while the acurancy variable does not affect HIS user satisfaction.","PeriodicalId":163873,"journal":{"name":"IJCONSIST JOURNALS","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123164542","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}

引用次数: 3

Battery Power Control and Monitoring System with Internet of Things Technology 基于物联网技术的电池电量控制与监测系统

IJCONSIST JOURNALS Pub Date : 2021-12-28 DOI: 10.33005/ijconsist.v3i1.56

Slamet Winardi, Didik Dwi Suharso, Hendra Purnomo, Arief Budijanto

{"title":"Battery Power Control and Monitoring System with Internet of Things Technology","authors":"Slamet Winardi, Didik Dwi Suharso, Hendra Purnomo, Arief Budijanto","doi":"10.33005/ijconsist.v3i1.56","DOIUrl":"https://doi.org/10.33005/ijconsist.v3i1.56","url":null,"abstract":"Along with the development of battery/ACCU technology, the ACCU charging and loading system has also developed manually or automatically. In this paper, the results of research on the manufacture of tools that function to monitor and control the charging and loading of electrical power will be explained from batteries that are burdened with lights and DC motors through a control panel or android smart phone with IoT technology. This tool is designed to monitor 2 ACCUs, namely ACCU1 and ACCU2. ACCU1 is loaded with lamp and parallel with DC motor load while ACCU2 is loaded with DC motor and parallel with lamp load. If ACCU1 and ACCU2 are full, ACCU1 is loaded with only one lamp and ACCU2 is only loaded with DC motor. For example, ACCU1's electrical power is still within the limits that can be loaded with lights and DC motors while ACCU2 can't be loaded because electric power is not capable of being loaded with DC motors, the DC motor's load will be transferred to ACCU1. So that ACCU1 is loaded with DC lamps and motors and ACCU2 is charging the electricity, as well as for the opposite condition. The design of this tool uses the main component of the ESP32 microcontroller, where this component has been integrated with the wifi module and other supporting circuit modules, namely the current sensor circuit, voltage sensor and OLED display. The software design consists of a program code designer for hardware using C++ and an android smart phone application design using MIT App Inventor. The results of this study are in accordance with the design specifications, namely the device can be used to control charging and loading as well as monitor ACCU1 and ACCU2 electrical power on OLED screens and on Android smart phones screens","PeriodicalId":163873,"journal":{"name":"IJCONSIST JOURNALS","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121568611","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}

引用次数: 0

Edmodo E-Learning Analysis using End-User Computing Satisfaction Method (Case Study: Senior High School 1 Sampang) 基于终端用户计算满意度法的Edmodo E-Learning分析(以高三三邦为例)

IJCONSIST JOURNALS Pub Date : 2021-12-28 DOI: 10.33005/ijconsist.v3i1.58

Khusnia Nur Rachmah, Ahmad Nashirul Haq, Nur Hasan Assobarry, Fariza Nanda Sabila, Tri Lathif Mardi Suryanto

{"title":"Edmodo E-Learning Analysis using End-User Computing Satisfaction Method (Case Study: Senior High School 1 Sampang)","authors":"Khusnia Nur Rachmah, Ahmad Nashirul Haq, Nur Hasan Assobarry, Fariza Nanda Sabila, Tri Lathif Mardi Suryanto","doi":"10.33005/ijconsist.v3i1.58","DOIUrl":"https://doi.org/10.33005/ijconsist.v3i1.58","url":null,"abstract":"The development of information technology that continues to grow in all aspects of life which makes human work more efficient and effective. The current COVID-19 pandemic is one of the conditions in which people's activities are hindered and limited in their daily activities. The application of Information Technology is a solution that can be applied for the sustainability of community activities in the midst of this pandemic, one of which is the education sector. Edmodo's E-Learning system is one of the most widely used e-learning systems for the teaching and learning process. The application of e-learning certainly changes the way students learn from offline to online. EUCS (end-user computing satisfaction) is one of the methods used to analyze user satisfaction of an information system, where this method has 5 variables, namely content, accuracy, format, ease of use, and timeliness. The case study of Senior High School 1 Sampang will be the object of this research, where the EUCS method is used to measure the satisfaction of end users of the Edmodo E-Learning system. Data was collected by distributing questionnaires to active students at Senior High School 1 Sampang by obtaining a sample of 80 respondents. From the results of the research conducted, it was found that the EUCS method can be applied to the Edmodo E-Learning system at Senior High School 1 Sampang because the data obtained from the respondents was declared valid and reliable so that it can be relied upon in measuring end user satisfaction with the Edmodo E-learning system, while the factors - the factors of the EUCS method that affect the satisfaction of the end user of the Edmodo E-Learning system at Srnior High School 1 Sampang are the content and accuracy factors.","PeriodicalId":163873,"journal":{"name":"IJCONSIST JOURNALS","volume":"187 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128117322","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}

引用次数: 2

Classification of color features in butterflies using the Support Vector Machine (SVM) 基于支持向量机的蝴蝶颜色特征分类

IJCONSIST JOURNALS Pub Date : 2021-06-01 DOI: 10.33005/ijconsist.v2i02.50

Dhian Satria Yudha Kartika, Hendra Maulana

{"title":"Classification of color features in butterflies using the Support Vector Machine (SVM)","authors":"Dhian Satria Yudha Kartika, Hendra Maulana","doi":"10.33005/ijconsist.v2i02.50","DOIUrl":"https://doi.org/10.33005/ijconsist.v2i02.50","url":null,"abstract":"Research in digital images is expanding widely and includes several sectors. One sector currently being carried out research is in insects; specifically, butterflies are used as a dataset. A total of 890 types of butterflies divided into ten classes were used as a dataset and classified based on color. Ten types of butterflies include Danaus plexippus, Heliconius charitonius, Heliconius erato, Junonia coenia, Lycaena phlaeas, Nymphalis antiopa, Papilio cresphontes, Pieris rapae, Vanessa atalanta, Vanessa cardui. The process of extracting color features on butterfly wings uses the RGB method to become HSV color space with color quantization (CQ). The purpose of adding CQ is that the computation process is carried out faster without reducing the image's information. In the color feature extraction process, the image is converted into 3-pixel sizes and normalized. The process of normalizing the dataset has the aim that the value ranges in the dataset have the same value. The 890 butterfly dataset was classified using the Support Vector Machine (SVM) method. Based on this research process, the accuracy of the 256x160 pixel size is 72%, the 420x315 pixel is 75%, and the 768x576 pixel is 75%. The test results on a system with a 768x576 pixel get the highest results with a precision value of 74.6%, a recall of 72%, and an f-measure of 73.2% \u0000Keywords—image processing; classification; butterflies; color features; features extraction","PeriodicalId":163873,"journal":{"name":"IJCONSIST JOURNALS","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124201759","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}

引用次数: 1

Imam Safii Heart Disease Classification using Gain Ratio Feature Selection with Hidden Layer Modification in Extreme Learning Machine 基于增益比特征选择和隐层修正的极限学习机心脏病分类

IJCONSIST JOURNALS Pub Date : 2021-06-01 DOI: 10.33005/ijconsist.v2i02.48

Imam Safii, Made Kamisutara, Tresna Maulana Faahrudin

{"title":"Imam Safii Heart Disease Classification using Gain Ratio Feature Selection with Hidden Layer Modification in Extreme Learning Machine","authors":"Imam Safii, Made Kamisutara, Tresna Maulana Faahrudin","doi":"10.33005/ijconsist.v2i02.48","DOIUrl":"https://doi.org/10.33005/ijconsist.v2i02.48","url":null,"abstract":"Heart disease is a non-communicable disease that causes a high mortality rate and is still a problem both in developed and developing countries. This disease often occurs because of the narrowing of blood vessels which causes the functioning of the heart is disturbed. The number of cases of heart disease in Indonesia is still quite high, making medical staff require a fairly in diagnosing the patient's conditional. The research proposed to implement Gain Ratio in selecting the most important feature that influences heart disease and building the classification models based on the modification of hidden layer weight on Extreme Learning Machine. The research collected the heart disease dataset which was obtained from Kaggle UCI Machine Learning consist of 1.025 samples, 14 attributes, and 2 labels. The data preprocessing include using data cleaning and normalization to find out dirty data or missing values. The experiment reported that Gain Ratio succeeds to generate the attribute ranking of heart disease dataset, then Gain Ratio score was added to the weighting of the hidden layer input on learning methods. The research used various validation sampling using the splitting test between training data and testing such as 70:30, 80:20, 90:10%, and set up 1500 hidden layers. The accuracy average performance of Extreme Learning Machine with modification using Gain Ratio reached 100% for the training phase and 97.67% for the testing phase. \u0000 \u0000Keyword: Heart Disease, Gain Ratio, Modification, Classification, Extreme Learning Machine","PeriodicalId":163873,"journal":{"name":"IJCONSIST JOURNALS","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134462056","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}

引用次数: 1

Maturity Level for IT Implementation Measurement Focus on Business Goal 14 and 15 at Diskominfo Province 在Diskominfo省，IT实现度量的成熟度级别关注业务目标14和15

IJCONSIST JOURNALS Pub Date : 2021-06-01 DOI: 10.33005/ijconsist.v2i02.36

S. Mukaromah, Eva Y Puspaningrum, Doddy Riddwandono

引用次数: 0

Exploratory Data Analysis and Machine Learning Algorithms to Classifying Stroke Disease 脑卒中疾病分类的探索性数据分析和机器学习算法

IJCONSIST JOURNALS Pub Date : 2021-06-01 DOI: 10.33005/ijconsist.v2i02.49

P. Riyantoko, Tresna Maulana Fahrudin, K. M. Hindrayani, M. Idhom

引用次数: 0

Determining Students Preparation for College Entrance Examinations in Indonesia From Twitter Data Using Exploratory Data Analysis 利用探索性数据分析从Twitter数据中确定印度尼西亚学生的高考准备情况

IJCONSIST JOURNALS Pub Date : 2021-06-01 DOI: 10.33005/ijconsist.v2i02.47

Kartika Maulida Hindrayani, Tresna Maulana F, Prismahardi Aji R, Kartini

引用次数: 0

Classification of Toddler Nutritional Status Based on Antrophometric Index and Feature Discrimination using Support Vector Machine Hyperparameter Tuning 基于抗营养指标和支持向量机超参数调谐特征判别的幼儿营养状况分类

IJCONSIST JOURNALS Pub Date : 2021-06-01 DOI: 10.33005/ijconsist.v2i02.45

Much. afif masykur mughni, Tresna Maulana Fahrudin, Made Kamisutara

{"title":"Classification of Toddler Nutritional Status Based on Antrophometric Index and Feature Discrimination using Support Vector Machine Hyperparameter Tuning","authors":"Much. afif masykur mughni, Tresna Maulana Fahrudin, Made Kamisutara","doi":"10.33005/ijconsist.v2i02.45","DOIUrl":"https://doi.org/10.33005/ijconsist.v2i02.45","url":null,"abstract":"Nutritional status is the study of food and is related to health. Nutritional status is a benchmark to assess the health development of toddler. The nutritional status of toddler is assessed according to three index, such as body weight to age (BW / A), body height to age (BH / A), body weight to body height (BW / BH). The issue of nutrition is still a major factor in the growth and development of toddler in Indonesia. Public Health Center (Puskesmas) and Integrated Healthcare Center (Posyandu) as public health services work together to control the growth and development of toddler in Indonesia. To help control the growth and development of toddler, we proposed a research to classify the nutritional status of toddler based on anthropometric index. The nutritional status of toddler dataset was formed into a classification model using SVM Hyperparameter Tuning. SVM is a machine learning which the classification model used a hypothesis space in the form of linear functions in a high dimensional feature space. Adjustment of the hyperparameter was involved to reach a model that can optimally solve machine learning problems. We implemented feature selection using Fisher's Discriminant Ratio as a preprocessing stage, which the most important features were body weight (BB) and height (BH). The experimental results showed the classification model using SVM on training and testing data with a ratio of 70:30 reached accuracy of 84%, while SVM Hyperparameter Tuning with parameter of Cost = 100 parameters, Gamma = 0.01, Kernel = RBF reached accuracy of 97%. They represented a significant accuracy difference of 13%.","PeriodicalId":163873,"journal":{"name":"IJCONSIST JOURNALS","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134212942","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}

引用次数: 0