Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231866
Choirun Nisa, Amang Sudarsono, Mike Yuliana
In recent years, the Internet of Things (IoT) becomes popular technology. The one aspect that makes important concern in IoT is the confidentiality of communications. For securing communication in IoT, cryptography algorithm such as symmetrical cryptography requires the secret key exchange process in a public wireless network to ensure the sameness of the secret key. However, the exchange of secret keys in the public wireless network can be exploited by adversaries. So, we present the secret key generation scheme that generates a shared random key through observation of the communication channel parameter i.e. Receive Signal Strength (RSS) between two devices that no need to exchange the secret key. We use Middle-Point quantization to convert the RSS into bit sequences and use Clover Filter to eliminate the error bits after the quantization process. Measurement results showed that the proposed scheme improves the performance of existing schemes if the interval used is 25. The proposed scheme improves the KGR 24 times and improves efficiency to 63%. While for KDR, the proposed scheme can decrease the KDR value of 67.9%. Also, in all scenarios, the proposed scheme can pass the NIST randomness test.
{"title":"RSS-based Secret Key Establishment using Middle-Point Quantization and Clover Filter Algorithm","authors":"Choirun Nisa, Amang Sudarsono, Mike Yuliana","doi":"10.1109/IES50839.2020.9231866","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231866","url":null,"abstract":"In recent years, the Internet of Things (IoT) becomes popular technology. The one aspect that makes important concern in IoT is the confidentiality of communications. For securing communication in IoT, cryptography algorithm such as symmetrical cryptography requires the secret key exchange process in a public wireless network to ensure the sameness of the secret key. However, the exchange of secret keys in the public wireless network can be exploited by adversaries. So, we present the secret key generation scheme that generates a shared random key through observation of the communication channel parameter i.e. Receive Signal Strength (RSS) between two devices that no need to exchange the secret key. We use Middle-Point quantization to convert the RSS into bit sequences and use Clover Filter to eliminate the error bits after the quantization process. Measurement results showed that the proposed scheme improves the performance of existing schemes if the interval used is 25. The proposed scheme improves the KGR 24 times and improves efficiency to 63%. While for KDR, the proposed scheme can decrease the KDR value of 67.9%. Also, in all scenarios, the proposed scheme can pass the NIST randomness test.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116866427","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}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231663
Qurina Firdaus, R. Sigit, T. Harsono, A. Anwar
Lung cancer is all malignant diseases in the lungs, including malignancies originating from the lungs themselves (primary) or those originating from other organs (metastasis). Lung cancer is one of the leading causes of death worldwide. Lung cancer is a tumor that grows rapidly and can spread to other organs. The onset of cancer is characterized by abnormal cell growth that can damage other normal tissue cells. Computerized Tomography (CT) is an imaging technique often used to diagnose lung cancer. Lung cancer can be classified into benign and malignant cancer. It is very important to diagnose lung cancer at an early stage to speed up the treatment process and the actions that will be taken. This study aims to develop a lung cancer detection system based on CT-scan images. This detection system has 4 main stages, namely pre-processing of CT-Scan images to improve image quality, segmentation to identify and separate the desired cancer object from the background, feature extraction based on area, contrast, energy, entropy, and homogeneity. The classification of lung cancer into cancer benign and malignant cancer. From the system trial, the accuracy level based on the system decision in determining the diagnosis of lung cancer is benign or malignant was 83.33%.
{"title":"Lung Cancer Detection Based On CT-Scan Images With Detection Features Using Gray Level Co-Occurrence Matrix (GLCM) and Support Vector Machine (SVM) Methods","authors":"Qurina Firdaus, R. Sigit, T. Harsono, A. Anwar","doi":"10.1109/IES50839.2020.9231663","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231663","url":null,"abstract":"Lung cancer is all malignant diseases in the lungs, including malignancies originating from the lungs themselves (primary) or those originating from other organs (metastasis). Lung cancer is one of the leading causes of death worldwide. Lung cancer is a tumor that grows rapidly and can spread to other organs. The onset of cancer is characterized by abnormal cell growth that can damage other normal tissue cells. Computerized Tomography (CT) is an imaging technique often used to diagnose lung cancer. Lung cancer can be classified into benign and malignant cancer. It is very important to diagnose lung cancer at an early stage to speed up the treatment process and the actions that will be taken. This study aims to develop a lung cancer detection system based on CT-scan images. This detection system has 4 main stages, namely pre-processing of CT-Scan images to improve image quality, segmentation to identify and separate the desired cancer object from the background, feature extraction based on area, contrast, energy, entropy, and homogeneity. The classification of lung cancer into cancer benign and malignant cancer. From the system trial, the accuracy level based on the system decision in determining the diagnosis of lung cancer is benign or malignant was 83.33%.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123965350","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}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231747
Ade Verdinata Pratama, Novita Astin, C. D. Murdaningtyas
In this era, technology and the Internet have become a thing that can’t be separated from human life. Humans can fulfill their needs and other human beings with the internet One such need is a tertiary need such as video entertainment on Youtube and movies that can be viewed on multiple paid sites. Videos that are on Youtube or movies on the paid site are quite related to the broadcasting world, where they are located at the Electronic Engineering Polytechnic Institute of Surabaya (EEPIS), or more precisely in the Multimedia Broadcasting Technology (MMB) study program. Lots of tools and supporting software that can support MMB student learning so that they can learn the world of broadcasting even further. One of the software that can be used for broadcasting is VMix. VMix is a software that can be used to produce videos and movies according to the wishes of its users. However, due to the limitations of the devices in the MMB study program, the Arduino Uno-based console is built and integrated with VMix software. Users can utilize this console to set the audio level of the video or movie theyfre producing. With this product, MMB students are expected to operate VMix software more easily and able to improve the quality of the videos or movies they produce.
{"title":"Design and Implementation of VMix Console for Audio in Music Show","authors":"Ade Verdinata Pratama, Novita Astin, C. D. Murdaningtyas","doi":"10.1109/IES50839.2020.9231747","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231747","url":null,"abstract":"In this era, technology and the Internet have become a thing that can’t be separated from human life. Humans can fulfill their needs and other human beings with the internet One such need is a tertiary need such as video entertainment on Youtube and movies that can be viewed on multiple paid sites. Videos that are on Youtube or movies on the paid site are quite related to the broadcasting world, where they are located at the Electronic Engineering Polytechnic Institute of Surabaya (EEPIS), or more precisely in the Multimedia Broadcasting Technology (MMB) study program. Lots of tools and supporting software that can support MMB student learning so that they can learn the world of broadcasting even further. One of the software that can be used for broadcasting is VMix. VMix is a software that can be used to produce videos and movies according to the wishes of its users. However, due to the limitations of the devices in the MMB study program, the Arduino Uno-based console is built and integrated with VMix software. Users can utilize this console to set the audio level of the video or movie theyfre producing. With this product, MMB students are expected to operate VMix software more easily and able to improve the quality of the videos or movies they produce.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127707506","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}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231941
Muhammad Rizal Prasetyo, Iwan Kumianto Wibowo, M. Bachtiar, Renardi Adryantoro Priambudi, Khoirul Anwar, Putu Bagus Kertha Segara
ERSOW is a wheeled soccer robot that is included in the Middle Size League (MSL) category in the Indonesian Wheeled Robot Soccer Contest division (Wheeled KRSBI). Wheeled soccer robot has Artificial Intelligent (AI) for kick the ball, receive the ball, feed the ball, recognize the ball, recognize the opponent, recognize the goal, receive instructions from the base station, and so forth. This research focuses on giving instructions to ERSOW through the base station using the voice command system. The system uses speech as input in the form of analog signals. Speech recognition is done by using a deep speech package so as to produce output in the form of text. The system will run on the Robot Operating System (ROS). The result of speech recognition using 13 trained speakers when tested by one speaker in different distance show average Word Error Rate (WER) 0.46% and Word Accuracy (W Acc) is 99.54%. When tested by five different speaker using trained speakers show average WER is 4.37% and W Acc is 95.63%, when using non trained speakers show average WER is 28.25% and W Acc is 71.75%. Base station implementation shows the simulation of the robot when the user gives instruction by his or her own voice.
{"title":"Implementation Voice Command System for Soccer Robot ERSOW","authors":"Muhammad Rizal Prasetyo, Iwan Kumianto Wibowo, M. Bachtiar, Renardi Adryantoro Priambudi, Khoirul Anwar, Putu Bagus Kertha Segara","doi":"10.1109/IES50839.2020.9231941","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231941","url":null,"abstract":"ERSOW is a wheeled soccer robot that is included in the Middle Size League (MSL) category in the Indonesian Wheeled Robot Soccer Contest division (Wheeled KRSBI). Wheeled soccer robot has Artificial Intelligent (AI) for kick the ball, receive the ball, feed the ball, recognize the ball, recognize the opponent, recognize the goal, receive instructions from the base station, and so forth. This research focuses on giving instructions to ERSOW through the base station using the voice command system. The system uses speech as input in the form of analog signals. Speech recognition is done by using a deep speech package so as to produce output in the form of text. The system will run on the Robot Operating System (ROS). The result of speech recognition using 13 trained speakers when tested by one speaker in different distance show average Word Error Rate (WER) 0.46% and Word Accuracy (W Acc) is 99.54%. When tested by five different speaker using trained speakers show average WER is 4.37% and W Acc is 95.63%, when using non trained speakers show average WER is 28.25% and W Acc is 71.75%. Base station implementation shows the simulation of the robot when the user gives instruction by his or her own voice.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126417279","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}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231842
T. Badriyah, Yunaz Gilang Ramadhan, I. Syarif
Recommendation systems have been widely applied in many areas, such as E-commerce, and so on. However, in some complex systems such as missed sparse data, it will be increasingly difficult to build a model for user recommendations. In this research we develop a recommendation system on E-Commerce. This system will be able to adapt and provide the best recommendations for each user dynamically even in sparse environment. The system will be created in a web-based application to display the product recommendations to users. The recommendation system developed is expected to be able to solve cold-start problem when there is no other relevant data to be recommended for the new added product and also the sparsity problem. To overcome this problem, the system will implement multi-mode algorithm that uses more than one search algorithm for the closest characteristics in the recommendation system and can choose one of the best algorithms to use in accordance with the existing data and hybrid-filtering that can use a combination of Collaborative Filtering is to make recommendations based on information equations between users and Content-Based Filtering is to make recommendations based on information representation of a content. Thus the system will be able to provide product recommendations on any state of data on E-Commerce.
{"title":"An Efficient Framework of Hybrid Recommendation System based on Multi Mode","authors":"T. Badriyah, Yunaz Gilang Ramadhan, I. Syarif","doi":"10.1109/IES50839.2020.9231842","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231842","url":null,"abstract":"Recommendation systems have been widely applied in many areas, such as E-commerce, and so on. However, in some complex systems such as missed sparse data, it will be increasingly difficult to build a model for user recommendations. In this research we develop a recommendation system on E-Commerce. This system will be able to adapt and provide the best recommendations for each user dynamically even in sparse environment. The system will be created in a web-based application to display the product recommendations to users. The recommendation system developed is expected to be able to solve cold-start problem when there is no other relevant data to be recommended for the new added product and also the sparsity problem. To overcome this problem, the system will implement multi-mode algorithm that uses more than one search algorithm for the closest characteristics in the recommendation system and can choose one of the best algorithms to use in accordance with the existing data and hybrid-filtering that can use a combination of Collaborative Filtering is to make recommendations based on information equations between users and Content-Based Filtering is to make recommendations based on information representation of a content. Thus the system will be able to provide product recommendations on any state of data on E-Commerce.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"375 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121760731","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}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231661
Ferry Astika Saputra, A. Barakbah, Putri Riza Rokhmawati
The value of the Human Development Index (HDI) in Indonesia is increasing every year. Indonesia has many provinces and districts/cities, it makes the government need more time to analyze data. This research purpose a new method to analyze the data of HDI with a descriptive and predictive mining method. There are two main results of this research. First, a segmentation of HDI data into four segments, there are low, medium, high, and very high. Second, a prediction of HDI data. Before analyzing data, the system does data preprocessing to repair the missing data (cleaning) and normalization (transformation) to convert data into a smaller range(from 0 to 1). To get a segmentation result use the descriptive mining method, in this method, there are two steps, the first system does grouping and labeling data based on the value of HDI indicators(life expectancy, expected years of schooling, mean years of schooling and income per capita) use Hierarchical Clustering Centroid Linkage Method. Second, the system does the interpretation process based on the distance between centroid every cluster and ground(0,0). To get a prediction result use the predictive mining method, this process uses a Weighted Moving Average(WMA) with the last three years of HDI data. The result of this research, the variance accuracy value of the descriptive mining method is 0,203, and the Mean Absolute Percentage Error(MAPE) value of the predictive mining method is 0,27%.
{"title":"Data Analytics of Human Development Index(HDI) with Features Descriptive and Predictive Mining","authors":"Ferry Astika Saputra, A. Barakbah, Putri Riza Rokhmawati","doi":"10.1109/IES50839.2020.9231661","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231661","url":null,"abstract":"The value of the Human Development Index (HDI) in Indonesia is increasing every year. Indonesia has many provinces and districts/cities, it makes the government need more time to analyze data. This research purpose a new method to analyze the data of HDI with a descriptive and predictive mining method. There are two main results of this research. First, a segmentation of HDI data into four segments, there are low, medium, high, and very high. Second, a prediction of HDI data. Before analyzing data, the system does data preprocessing to repair the missing data (cleaning) and normalization (transformation) to convert data into a smaller range(from 0 to 1). To get a segmentation result use the descriptive mining method, in this method, there are two steps, the first system does grouping and labeling data based on the value of HDI indicators(life expectancy, expected years of schooling, mean years of schooling and income per capita) use Hierarchical Clustering Centroid Linkage Method. Second, the system does the interpretation process based on the distance between centroid every cluster and ground(0,0). To get a prediction result use the predictive mining method, this process uses a Weighted Moving Average(WMA) with the last three years of HDI data. The result of this research, the variance accuracy value of the descriptive mining method is 0,203, and the Mean Absolute Percentage Error(MAPE) value of the predictive mining method is 0,27%.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130254554","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}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231949
Narendra Yogha Prathama, Rengga Asmara, Ali Ridho Barakbah
The game industry is an industry that includes game development, marketing, and monetization. However, to be able to enter the game industry is not easy. Game developers must know how the market is going to be able to reap huge profits. By knowing the market situation, game developers can also determine whether the games made are in accordance with market conditions. Getting this information is not easy, especially for small game studios. In this research, we made a new application to find knowledge about games that are and will be trending. We used data mining is used to obtain this information. Data mining uses data from the Steam API to do clustering using the Hierarchical K-Means method and predictive using the Multiple Linear Regression method. The use of the Hierarchical K-Means method produces 3 clusters for the game's popularity level. The use of the Multiple Linear Regression method produces predictions of the game's popularity in the future. This new system will be able to help indie game studios to be able to obtain information about the condition of the gaming market thereby increasing the benefits that can be obtained.
{"title":"Game Data Analytics using Descriptive and Predictive Mining","authors":"Narendra Yogha Prathama, Rengga Asmara, Ali Ridho Barakbah","doi":"10.1109/IES50839.2020.9231949","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231949","url":null,"abstract":"The game industry is an industry that includes game development, marketing, and monetization. However, to be able to enter the game industry is not easy. Game developers must know how the market is going to be able to reap huge profits. By knowing the market situation, game developers can also determine whether the games made are in accordance with market conditions. Getting this information is not easy, especially for small game studios. In this research, we made a new application to find knowledge about games that are and will be trending. We used data mining is used to obtain this information. Data mining uses data from the Steam API to do clustering using the Hierarchical K-Means method and predictive using the Multiple Linear Regression method. The use of the Hierarchical K-Means method produces 3 clusters for the game's popularity level. The use of the Multiple Linear Regression method produces predictions of the game's popularity in the future. This new system will be able to help indie game studios to be able to obtain information about the condition of the gaming market thereby increasing the benefits that can be obtained.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"372 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131836359","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}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231850
Ni Putu Devira Ayu Martini, N. Tamami, Ali Husein Alasiry
Technological advances in this time are developing very rapidly, especially in agriculture. Watering activity is still done manually so that it consumes a lot of energy. Actually there are easy solutions in maintaining plants, one of which is by ensuring adequate water intake. However, this is still a problem if the intensity of watering does not obtain the needs and conditions of mineral intake in plants. In addition to observing the condition of plants, soil checking is also needed to determine the water content and soil conditions so as not to cause drought, the plants wither to death. Unfortunately, to know the conditions for when to flush, the community must also be aware of when to stop flushing, a lot of water is needed and how often watering must be done. In this paper, we propose a novel agricultural robot based on CNC machine namely Automatic Gardening Robot, which can walk at any point of the plant for farming crops autonomously without any human intervention. Automatic sprinkler robot is designed to be able to plant plants with soil media and dimensions of planting area that can be adjusted according to your own needs are still within the specified area limits
{"title":"Design and Development of Automatic Plant Robots with Scheduling System","authors":"Ni Putu Devira Ayu Martini, N. Tamami, Ali Husein Alasiry","doi":"10.1109/IES50839.2020.9231850","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231850","url":null,"abstract":"Technological advances in this time are developing very rapidly, especially in agriculture. Watering activity is still done manually so that it consumes a lot of energy. Actually there are easy solutions in maintaining plants, one of which is by ensuring adequate water intake. However, this is still a problem if the intensity of watering does not obtain the needs and conditions of mineral intake in plants. In addition to observing the condition of plants, soil checking is also needed to determine the water content and soil conditions so as not to cause drought, the plants wither to death. Unfortunately, to know the conditions for when to flush, the community must also be aware of when to stop flushing, a lot of water is needed and how often watering must be done. In this paper, we propose a novel agricultural robot based on CNC machine namely Automatic Gardening Robot, which can walk at any point of the plant for farming crops autonomously without any human intervention. Automatic sprinkler robot is designed to be able to plant plants with soil media and dimensions of planting area that can be adjusted according to your own needs are still within the specified area limits","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129383354","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}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231730
Guskoro Pradipta Prana Arief, A. Barakbah, A. Basuki
In the current search system we often encounter difficult in determining an impression on the painting, it is caused by the impression of a painting that often invites a variety of people's perception, the most appropriate way to know the impression is to ask the pronunciation. But not all painters still exist, Indonesian cultural paintings have historical value and have been there since ten and even hundred years, it is impossible to get the right painting impressions. In this paper, we conducted a new study to obtain impressions from Indonesian cultural paintings, using impression context recognition based on the context that exists on color features of the paintings. Then we calculate the features of the painting on the impression that has been determined in previous research. 3D Color Vector Quantization is used to extract color features from paintings. In this experiment, we used 605 paintings obtained from 3 museum sources in Indonesia, namely the Indonesian National Museum (Jakarta), Affandi Museum (Yogyakarta) and the Puri Lukisan Museum (Bali) combined with 30 impressions from previous research. The results of this study can facilitate culturalists, artists, historians or the public who want to know the value contained in Indonesian cultural paintings through the impression created by creating the basic features of paintings.
{"title":"Image Search System for Indonesian Cultural Paintings with Impression Context Recognition","authors":"Guskoro Pradipta Prana Arief, A. Barakbah, A. Basuki","doi":"10.1109/IES50839.2020.9231730","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231730","url":null,"abstract":"In the current search system we often encounter difficult in determining an impression on the painting, it is caused by the impression of a painting that often invites a variety of people's perception, the most appropriate way to know the impression is to ask the pronunciation. But not all painters still exist, Indonesian cultural paintings have historical value and have been there since ten and even hundred years, it is impossible to get the right painting impressions. In this paper, we conducted a new study to obtain impressions from Indonesian cultural paintings, using impression context recognition based on the context that exists on color features of the paintings. Then we calculate the features of the painting on the impression that has been determined in previous research. 3D Color Vector Quantization is used to extract color features from paintings. In this experiment, we used 605 paintings obtained from 3 museum sources in Indonesia, namely the Indonesian National Museum (Jakarta), Affandi Museum (Yogyakarta) and the Puri Lukisan Museum (Bali) combined with 30 impressions from previous research. The results of this study can facilitate culturalists, artists, historians or the public who want to know the value contained in Indonesian cultural paintings through the impression created by creating the basic features of paintings.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129390988","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}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231872
Hari Malik Mu’allimi, Bima Sena Bayu Dewantara, D. Pramadihanto, Bayu Sandi Marta
A robot guide is a robot that is used to guide users from a place of origin to their destination. During carrying out the guiding task, the robot must ensure that the user always follows wherever the direction is headed by the robot until it reaches the destination location. To get this certainty, one of the things that must be considered is the direction the user must walk in the direction of the robot's movement. In this paper, we built a system to monitor user awareness levels to coordinate with robots. We use RGB-D data from the Kinect sensor to detect target partners, their position, and orientation. The level of awareness is calculated using the Social Force Model (SFM) based on the target partner's position and body orientation parameters. This level of awareness will be used by the robot to evaluate the appropriate actions according to the target partner's activities. Based on the results of experiments, the level of awareness of target partners can be calculated and transformed in the form of attractive or repulsive forces towards robots.
{"title":"Human Partner and Robot Guide Coordination System Under Social Force Model Framework Using Kinect Sensor","authors":"Hari Malik Mu’allimi, Bima Sena Bayu Dewantara, D. Pramadihanto, Bayu Sandi Marta","doi":"10.1109/IES50839.2020.9231872","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231872","url":null,"abstract":"A robot guide is a robot that is used to guide users from a place of origin to their destination. During carrying out the guiding task, the robot must ensure that the user always follows wherever the direction is headed by the robot until it reaches the destination location. To get this certainty, one of the things that must be considered is the direction the user must walk in the direction of the robot's movement. In this paper, we built a system to monitor user awareness levels to coordinate with robots. We use RGB-D data from the Kinect sensor to detect target partners, their position, and orientation. The level of awareness is calculated using the Social Force Model (SFM) based on the target partner's position and body orientation parameters. This level of awareness will be used by the robot to evaluate the appropriate actions according to the target partner's activities. Based on the results of experiments, the level of awareness of target partners can be calculated and transformed in the form of attractive or repulsive forces towards robots.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"518 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133698348","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：