Brilliance: Research of Artificial Intelligence最新文献_第6页

Smart Chicken Coop Control and Monitoring System Design Automatically with Smartphone Notifications 智能鸡笼控制和监控系统设计自动与智能手机通知

Brilliance: Research of Artificial Intelligence Pub Date : 2021-11-29 DOI: 10.47709/brilliance.v1i2.1193

Sri Novida Sari, R. Aritonang, Sumarlin Sumarlin

引用次数: 0

Literature Study: Highway Traffic Management with Sentiment Analysis and Data Mining 文献研究:基于情感分析和数据挖掘的公路交通管理

Brilliance: Research of Artificial Intelligence Pub Date : 2021-09-16 DOI: 10.47709/brilliance.v1i1.1096

N. Khairina, M. K. Harahap

{"title":"Literature Study: Highway Traffic Management with Sentiment Analysis and Data Mining","authors":"N. Khairina, M. K. Harahap","doi":"10.47709/brilliance.v1i1.1096","DOIUrl":"https://doi.org/10.47709/brilliance.v1i1.1096","url":null,"abstract":"In today's era, technology is growing rapidly, many of the latest technologies are in great demand by the Indonesian people, one of which is social media. Various social media such as Facebook, Twitter, Instagram, have become very popular applications for various ages, including teenagers, adults, and the elderly. Social media has a positive impact that can help people convey the latest information through posts on their respective accounts. Social media can disseminate information in a short time, this is why social media is an interesting application to research. The problem of road traffic congestion is strongly influenced by the number of vehicles that pass every day. A large number of private vehicles and public vehicles that pass greatly confuses the atmosphere of highway traffic. Congestion often occurs during working hours. Road congestion also often occurs when an unwanted incident occurs. Sentiment analysis algorithms and data mining algorithms can be combined to find information on traffic jams through social media such as Facebook, Twitter, Instagram, and other social media. The results show that sentiment analysis methods and data mining algorithms can be used to find information about current traffic jams through social media. The conclusion from this literature study can be seen that the K-Nearest Neighbor data mining algorithm is the best choice to overcome road traffic congestion, which will then be further developed in the form of highway traffic management modeling.","PeriodicalId":440433,"journal":{"name":"Brilliance: Research of Artificial Intelligence","volume":"200 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125605459","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

Implementation of restaurant location searching Geographic Information Systems using Android-based local based services method 利用基于android的基于本地服务的方法实现餐厅位置搜索地理信息系统

Brilliance: Research of Artificial Intelligence Pub Date : 2021-09-13 DOI: 10.47709/brilliance.v1i1.1087

Raja Nasrul Fuad, H. Hafni, Fadli Pratama

引用次数: 0

Prototype of IoT-Based Fruit Alcohol Level Measurement Tool 基于物联网的水果酒精浓度测量工具原型

Brilliance: Research of Artificial Intelligence Pub Date : 2021-09-04 DOI: 10.47709/brilliance.v1i1.1078

Nursila Nursila, D. N. Ilham, A. Yunan, M. K. Harahap, R. Candra

{"title":"Prototype of IoT-Based Fruit Alcohol Level Measurement Tool","authors":"Nursila Nursila, D. N. Ilham, A. Yunan, M. K. Harahap, R. Candra","doi":"10.47709/brilliance.v1i1.1078","DOIUrl":"https://doi.org/10.47709/brilliance.v1i1.1078","url":null,"abstract":"The effect of alcohol on health is very large if you consume too much, and the fact that excessive alcohol levels can interfere with digestion can cause eye function disorders, decreased brain and nerve function as well as cancer. Knowing the alcohol content in fruits that are suitable for consumption by the body from an early age is very important. Based on this problem, this study aims to create a prototype measuring instrument for the alcohol content of fruits using the Blynk application. This circuit consists of 3 circuits, namely the input part in the form of an Mq3 sensor, the control part in the form of Nodemcu, and the output port in the form of the Blynk application. From the results of testing tools for four samples including durian, grapes, papaya, and apples for 25 times the test of the fruit is peeled for the next 2 hours the average percentage of durian alcohol content is 28.57%, grapes are 12.68%, papaya is 5.79 %, and apples by 18.6%. In this study, there is also the notification facility to the third smartphone that the alcohol content exceeds the alcohol content which is not good from the value set on the device.","PeriodicalId":440433,"journal":{"name":"Brilliance: Research of Artificial Intelligence","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129533263","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: 5

Literature Study of Convolutional Neural Network Algorithm for Batik Classification 蜡染分类中卷积神经网络算法的文献研究

Brilliance: Research of Artificial Intelligence Pub Date : 2021-09-04 DOI: 10.47709/brilliance.v1i1.1069

Nardianti Dewi Girsang

{"title":"Literature Study of Convolutional Neural Network Algorithm for Batik Classification","authors":"Nardianti Dewi Girsang","doi":"10.47709/brilliance.v1i1.1069","DOIUrl":"https://doi.org/10.47709/brilliance.v1i1.1069","url":null,"abstract":"Batik is a hereditary cultural heritage that has high aesthetic value and deep philosophy. Currently, Indonesian batik has various types of different motifs and patterns, which are spread in Indonesia with their names and meanings. Batik classification uses Convolutional Neural Network as a pattern recognition method, especially batik image classification. The method used is a literature study, looking at studies from several journals regarding the Convolutional Neural Network Algorithm in Classification and providing conclusions about the usefulness of the algorithm. Analysis This literature study analyzes each journal from previous research related to the Convolutional Neural Network Algorithm in classifying Batik. The results of the analysis, conducted a discussion to better know the characteristics and application of Convolutional Neural Network in the classification of Batik. After discussing, this analysis ends with conclusions about the Convolutional Neural Network algorithm in classifying Batik. Based on previous studies, it can be seen that the convolution neural network can work well for image classification with large datasets. By evaluating the method that has been described by considering the architecture and the level of accuracy, namely getting an accuracy level of 100% with an image size of 128 x 128 and regarding the classification of batik, it shows that image size, image quality, image patterns affect the batik classification process.","PeriodicalId":440433,"journal":{"name":"Brilliance: Research of Artificial Intelligence","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120969072","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: 4

Design of Smoke Detector for Smart Room Based on Arduino Uno 基于Arduino Uno的智能房间感烟探测器设计

Brilliance: Research of Artificial Intelligence Pub Date : 2021-09-04 DOI: 10.47709/brilliance.v1i1.1079

D. N. Ilham, R. Candra, Muhammed Saat Talib, M. Nardo, Khusnul Azima

{"title":"Design of Smoke Detector for Smart Room Based on Arduino Uno","authors":"D. N. Ilham, R. Candra, Muhammed Saat Talib, M. Nardo, Khusnul Azima","doi":"10.47709/brilliance.v1i1.1079","DOIUrl":"https://doi.org/10.47709/brilliance.v1i1.1079","url":null,"abstract":"Smoke is one of the air pollutions that is very detrimental to the health of both the smoker himself and others around him. Inhaling other people's smoke is even more dangerous than inhaling your own smoke. Even the dangers that must be borne by passive smokers are three times greater than the dangers of active smokers. Smoke is also very detrimental to the health of patients in hospitals, especially patients who suffer from asthma. For people with asthma who have problems in the respiratory tract, asthma can recur at any time due to inhaling smoke. This research will develop a smart room that can detect smoke to maintain and protect the room from smoke that interferes with health. The tool to be developed uses an MQ2 sensor, LCD, exhaust fan, buzzer, and Arduino Uno microcontroller. Where an MQ2 sensor is needed to detect smoke around it, an LCD is needed to display the percentage of smoke, a microcontroller as a controller for all components, a buzzer is used as an alarm when the smoke level in the room is unhealthy, and the exhaust fan functions as a sucker for dirty air so that the smoke level in the room can be reduced.","PeriodicalId":440433,"journal":{"name":"Brilliance: Research of Artificial Intelligence","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132554932","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

IoT Based Paint Feed Process Monitoring System Implementation 基于物联网的涂料进料过程监控系统实现

Brilliance: Research of Artificial Intelligence Pub Date : 2021-01-01 DOI: 10.47709/brilliance.v2i1.1492

S. Shahrul, A. Budiansyah, S. Suryadi, R. Candra, D. N. Ilham

引用次数: 0