Pub Date : 2019-10-01DOI: 10.1109/ICITEED.2019.8929969
A. E. Permanasari, Abd. Dzuljalali Wal Ikram, Marcus Nurtiantara Aji, H. A. Nugroho, Intan Sulistyaningrum Sakkinah
The development of the supporting system is an essential component at the hospital. In general, animal hospitals have a similar form of service in human hospitals. The problem is arising because of limited inpatient room of the animal hospital. It can directly affect the quality of service to patients, especially if the number of patients is booming. The implementation of the Decision Support System (DSS) can enhance hospital services section by predicting patient recovery time. It is needed to help staff in arranging available inpatient rooms. We utilize the Iterative Dichotomiser 3 (ID3) algorithm to build a decision tree which is then translated into classification rules. ID3 algorithm is used to classify the variables contained in a patient’s medical record dataset. The results yielded a classification of estimated recovery time into three categories, namely 1-5 days, 6-10 days, and >10 days with 60% testing accuracy. Finally, we develop a prototype based decision tree to display the computation. The system can assist the administrative staff in maximizing inpatient room management, while animal owners can estimate the costs needed.
{"title":"A Web-Based Decision Support System of Patient Time Prediction Using Iterative Dichotomiser 3 Algorithm","authors":"A. E. Permanasari, Abd. Dzuljalali Wal Ikram, Marcus Nurtiantara Aji, H. A. Nugroho, Intan Sulistyaningrum Sakkinah","doi":"10.1109/ICITEED.2019.8929969","DOIUrl":"https://doi.org/10.1109/ICITEED.2019.8929969","url":null,"abstract":"The development of the supporting system is an essential component at the hospital. In general, animal hospitals have a similar form of service in human hospitals. The problem is arising because of limited inpatient room of the animal hospital. It can directly affect the quality of service to patients, especially if the number of patients is booming. The implementation of the Decision Support System (DSS) can enhance hospital services section by predicting patient recovery time. It is needed to help staff in arranging available inpatient rooms. We utilize the Iterative Dichotomiser 3 (ID3) algorithm to build a decision tree which is then translated into classification rules. ID3 algorithm is used to classify the variables contained in a patient’s medical record dataset. The results yielded a classification of estimated recovery time into three categories, namely 1-5 days, 6-10 days, and >10 days with 60% testing accuracy. Finally, we develop a prototype based decision tree to display the computation. The system can assist the administrative staff in maximizing inpatient room management, while animal owners can estimate the costs needed.","PeriodicalId":6598,"journal":{"name":"2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"26 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77104908","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 : 2019-10-01DOI: 10.1109/ICITEED.2019.8929967
D. I. Sensuse, Venniesa Dhevanty, Ernestina Rahmanasari, D. Permatasari, Bimo Eka Putra, Jonathan Sofian Lusa, M. Misbah, P. Prima
ELISA chatbot acts as an automated answering machine to users' problem in PT ABC. Implemented in May 2018, it succeeded to provide a faster response time than offline customer service. However, it still has issues in delivering accurate and appropriate responses. One of the reasons is the lack of system control and evaluation. This paper aims to evaluate how ELISA chatbot, as a knowledge application, benefits the company using DeLone & McLean model of information system as a reference. A survey was conducted, and SEM-PLS was utilized to process the data. The result shows that information quality, service quality, and intention to use significantly affect user satisfaction in ELISA. Suggestions for ELISA improvement includes machine learning technology utilization and nonfunctional improvements.
{"title":"Chatbot Evaluation as Knowledge Application: a Case Study of PT ABC","authors":"D. I. Sensuse, Venniesa Dhevanty, Ernestina Rahmanasari, D. Permatasari, Bimo Eka Putra, Jonathan Sofian Lusa, M. Misbah, P. Prima","doi":"10.1109/ICITEED.2019.8929967","DOIUrl":"https://doi.org/10.1109/ICITEED.2019.8929967","url":null,"abstract":"ELISA chatbot acts as an automated answering machine to users' problem in PT ABC. Implemented in May 2018, it succeeded to provide a faster response time than offline customer service. However, it still has issues in delivering accurate and appropriate responses. One of the reasons is the lack of system control and evaluation. This paper aims to evaluate how ELISA chatbot, as a knowledge application, benefits the company using DeLone & McLean model of information system as a reference. A survey was conducted, and SEM-PLS was utilized to process the data. The result shows that information quality, service quality, and intention to use significantly affect user satisfaction in ELISA. Suggestions for ELISA improvement includes machine learning technology utilization and nonfunctional improvements.","PeriodicalId":6598,"journal":{"name":"2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"16 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76533859","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 : 2019-10-01DOI: 10.1109/ICITEED.2019.8929966
Chukwan Siridhipakul, P. Vateekul
Our task is to forecast the next day’s power consumption in the half-hour interval for a total of 48 intervals. There are many studies that proposed models for power consumption forecasting problems but most of the previously proposed techniques focus on impact from different time step to power consumption, the importance of different features was not considered in these works. The Dual-Stage Attention-Based Recurrent Neural Network (DA-RNN) is the state-of-the-art in time series forecasting that considers both varying impacts from different time features for one-step-ahead forecasting. On the contrary, our work focuses on multi-step-ahead forecasting. In this paper, we aim to apply Dual-Stage Attentional LSTM for a multi-step-ahead power consumption forecasting problem. Experiments were conducted on Thailand’s power consumption data consisting of 5 control areas, weather data, and day type (weekday/weekend). We use RMSE and MAPE as evaluation metrics, the results showed that the Dual-Stage Attentional LSTM outperformed traditional models in both metrics.
{"title":"Multi-step Power Consumption Forecasting in Thailand Using Dual-Stage Attentional LSTM","authors":"Chukwan Siridhipakul, P. Vateekul","doi":"10.1109/ICITEED.2019.8929966","DOIUrl":"https://doi.org/10.1109/ICITEED.2019.8929966","url":null,"abstract":"Our task is to forecast the next day’s power consumption in the half-hour interval for a total of 48 intervals. There are many studies that proposed models for power consumption forecasting problems but most of the previously proposed techniques focus on impact from different time step to power consumption, the importance of different features was not considered in these works. The Dual-Stage Attention-Based Recurrent Neural Network (DA-RNN) is the state-of-the-art in time series forecasting that considers both varying impacts from different time features for one-step-ahead forecasting. On the contrary, our work focuses on multi-step-ahead forecasting. In this paper, we aim to apply Dual-Stage Attentional LSTM for a multi-step-ahead power consumption forecasting problem. Experiments were conducted on Thailand’s power consumption data consisting of 5 control areas, weather data, and day type (weekday/weekend). We use RMSE and MAPE as evaluation metrics, the results showed that the Dual-Stage Attentional LSTM outperformed traditional models in both metrics.","PeriodicalId":6598,"journal":{"name":"2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"46 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86466530","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 : 2019-10-01DOI: 10.1109/ICITEED.2019.8929956
Sarjiya, Rizki Firmansyah Setya Budi, S. P. Hadi
Delay on power plant constructions is a big problem in Ambon power system. Independent power producer (IPP) is an alternative solution to mitigate the risk of delays. The using of IPP makes the electricity market in Ambon power system becomes a deregulated market. So, before determining the IPP as the expansion power plants in Ambon power system, it is necessary to analyze the interest of investors to invest in the deregulated market (Ambon power system). The research’s purpose is to mitigate the delay risk of GEP implementation by IPP. This research carried out an investor interest analysis so it can be determined which power plants can be built by IPP and which ones must be handled by PLN. This research used modification of game theory method to analyze the investor interest in Ambon system. The research result showed that IPP solution is impossible because they are not interested. All power plants will be built by PLN. The alternative solutions to minimize the delay risk are utilizing capital market, increasing the ability of PLN to generate internal funds, and developed a project finance model where EPC contractors also give a portion on project funding.
{"title":"Delay Risk Mitigation of Generation Expansion Planning Implementation in the Deregulated Market based on Game Theory Approach","authors":"Sarjiya, Rizki Firmansyah Setya Budi, S. P. Hadi","doi":"10.1109/ICITEED.2019.8929956","DOIUrl":"https://doi.org/10.1109/ICITEED.2019.8929956","url":null,"abstract":"Delay on power plant constructions is a big problem in Ambon power system. Independent power producer (IPP) is an alternative solution to mitigate the risk of delays. The using of IPP makes the electricity market in Ambon power system becomes a deregulated market. So, before determining the IPP as the expansion power plants in Ambon power system, it is necessary to analyze the interest of investors to invest in the deregulated market (Ambon power system). The research’s purpose is to mitigate the delay risk of GEP implementation by IPP. This research carried out an investor interest analysis so it can be determined which power plants can be built by IPP and which ones must be handled by PLN. This research used modification of game theory method to analyze the investor interest in Ambon system. The research result showed that IPP solution is impossible because they are not interested. All power plants will be built by PLN. The alternative solutions to minimize the delay risk are utilizing capital market, increasing the ability of PLN to generate internal funds, and developed a project finance model where EPC contractors also give a portion on project funding.","PeriodicalId":6598,"journal":{"name":"2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"14 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88362348","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 : 2019-10-01DOI: 10.1109/ICITEED.2019.8930001
Dian Rusdiyanto, F. Zulkifli
A design of dual-band circularly polarized microstrip antenna for Global Positioning System and WLAN application is presented. This antenna proposed an inverted-L shaped with a stub as a feedline to achieve dual resonant frequency and characterize polarization of the antenna. From the simulated and measurement result showed this antenna can operate at frequency 1575.42 MHz and 2450 MHz. At those frequencies, it has right-hand circular polarization where its circular polarization bandwidth is 57.1 MHz and 223.2 MHz respectively. Using FR4-Epoxy dielectric substrate, measured GPS frequency obtained 1.49 dBi of gain while at WLAN frequency has 3.16 dBi.
{"title":"Dual Band Circularly Polarized Microstrip Antenna Fed By Inverted-L Shaped With A Stub for GPS And WLAN Application","authors":"Dian Rusdiyanto, F. Zulkifli","doi":"10.1109/ICITEED.2019.8930001","DOIUrl":"https://doi.org/10.1109/ICITEED.2019.8930001","url":null,"abstract":"A design of dual-band circularly polarized microstrip antenna for Global Positioning System and WLAN application is presented. This antenna proposed an inverted-L shaped with a stub as a feedline to achieve dual resonant frequency and characterize polarization of the antenna. From the simulated and measurement result showed this antenna can operate at frequency 1575.42 MHz and 2450 MHz. At those frequencies, it has right-hand circular polarization where its circular polarization bandwidth is 57.1 MHz and 223.2 MHz respectively. Using FR4-Epoxy dielectric substrate, measured GPS frequency obtained 1.49 dBi of gain while at WLAN frequency has 3.16 dBi.","PeriodicalId":6598,"journal":{"name":"2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"72 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86326481","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 : 2019-10-01DOI: 10.1109/ICITEED.2019.8929957
Damayanti Elisabeth, M. F. Rokhman, N. C. Harahap, Shidiq Al Hakim, D. I. Sensuse
Research collaboration is needed to accomplish the University’s targets: improve quality, collaboration, and partnerships in research. Identifying research collaboration is required as located research elements to facilitate research and encourage interdisciplinary collaboration. This research is aimed to discover scientific collaboration activities in the computer science domain on the Faculty of Computer Science, Universitas Indonesia. Using metadata as research data is a solution for embedded knowledge in unstructured documents. The information was collected online publications metadata from Scopus that published from 1988 to 2018. We used social network analysis (SNA) to map and measure scientific actors’ relationships to understand collaboration activities from various views of different elements and to build the author’s research profile. Based on the data, we can get information about the expertise of institution researchers and their relationships with other collaborators. Moreover, we can get information about the most popular actor, influenced actors, the bridge actors based on the relation map. The methodology in this research can be used to discover knowledge in other research domains and organizations, and the analysis of this research can be used for research management.
{"title":"Discovering Scientific Collaboration Activities using Social Network Analysis. A Case Study: Faculty of Computer Science Universitas Indonesia","authors":"Damayanti Elisabeth, M. F. Rokhman, N. C. Harahap, Shidiq Al Hakim, D. I. Sensuse","doi":"10.1109/ICITEED.2019.8929957","DOIUrl":"https://doi.org/10.1109/ICITEED.2019.8929957","url":null,"abstract":"Research collaboration is needed to accomplish the University’s targets: improve quality, collaboration, and partnerships in research. Identifying research collaboration is required as located research elements to facilitate research and encourage interdisciplinary collaboration. This research is aimed to discover scientific collaboration activities in the computer science domain on the Faculty of Computer Science, Universitas Indonesia. Using metadata as research data is a solution for embedded knowledge in unstructured documents. The information was collected online publications metadata from Scopus that published from 1988 to 2018. We used social network analysis (SNA) to map and measure scientific actors’ relationships to understand collaboration activities from various views of different elements and to build the author’s research profile. Based on the data, we can get information about the expertise of institution researchers and their relationships with other collaborators. Moreover, we can get information about the most popular actor, influenced actors, the bridge actors based on the relation map. The methodology in this research can be used to discover knowledge in other research domains and organizations, and the analysis of this research can be used for research management.","PeriodicalId":6598,"journal":{"name":"2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"19 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87511305","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 : 2019-10-01DOI: 10.1109/ICITEED.2019.8930002
Sattaya Singkul, K. Woraratpanya
Dependency parsing (DP) becomes an important part of natural language processing (NLP) applications. However, most of DP methods have been developed for English language, but not for Thai language. In addition, the existing DP methods were still unsolved the problems of long and complex sentences. Therefore, this paper proposes seven Thai DP algorithms. Five different Thai DP algorithms was developed from transition-based parsing and the other two was developed from graph-based parsing. Based on Thai-PUD and English-PUD datasets, containing both long and complex sentences, the experimental results showed that all Thai DP algorithms bundled with character embedding can outperform the baselines.
{"title":"Thai Dependency Parsing with Character Embedding","authors":"Sattaya Singkul, K. Woraratpanya","doi":"10.1109/ICITEED.2019.8930002","DOIUrl":"https://doi.org/10.1109/ICITEED.2019.8930002","url":null,"abstract":"Dependency parsing (DP) becomes an important part of natural language processing (NLP) applications. However, most of DP methods have been developed for English language, but not for Thai language. In addition, the existing DP methods were still unsolved the problems of long and complex sentences. Therefore, this paper proposes seven Thai DP algorithms. Five different Thai DP algorithms was developed from transition-based parsing and the other two was developed from graph-based parsing. Based on Thai-PUD and English-PUD datasets, containing both long and complex sentences, the experimental results showed that all Thai DP algorithms bundled with character embedding can outperform the baselines.","PeriodicalId":6598,"journal":{"name":"2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"21 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77801701","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 : 2019-10-01DOI: 10.1109/ICITEED.2019.8929974
Thanaporn Yooprasopchok, N. Wichaipanich, K. Hozumi
This paper presents the variations of E-layer critical frequency (foE) and Sporadic E (foEs) layer during low (2010) and high (2014) solar activity over Chumphon (Latitude 10.72°N, Longitude 99.37°E and Magnetic Dip Latitude 3.0°N) station, Thailand. Both foE and foEs parameters are manually scaled from ionograms recorded by FM/CW ionosonde at King Mongkut’s Institute of Technology Ladkrabang, Chumphon campus, Thailand. Chumphon is located at the magnetic equator. The observed data in the year of 2010 and 2014 are analyzed for low and high solar activity, respectively. For foE, the data during daytime (07:00-18:00 LT) are analyzed. For foEs, the daily hourly values and the seasonal (March equinox, June solstice, September equinox and December solstice) variations are analyzed. The results showed that the variation of foE during low and high solar activity were similarly, increasing during sunrise hours, reaching the highest values during noontime (11:00-13:00 LT) hours and decreasing after noontime until sunset hours. However, the foE values in 2014 were higher than those in 2010 because the sunspot number in 2014 was higher than that in 2010. For foEs, the results showed that the monthly hourly median was the maximum values in June solstice season for both years while was the minimum levels in December solstice season for 2010 and in March equinox season for 2014, respectively. This study will be helpful for communication designs and model predictions in the future.
{"title":"Variations of foE and foEs During Low and High Solar Activity Over Equatorial Latitude Station, Thailand","authors":"Thanaporn Yooprasopchok, N. Wichaipanich, K. Hozumi","doi":"10.1109/ICITEED.2019.8929974","DOIUrl":"https://doi.org/10.1109/ICITEED.2019.8929974","url":null,"abstract":"This paper presents the variations of E-layer critical frequency (foE) and Sporadic E (foEs) layer during low (2010) and high (2014) solar activity over Chumphon (Latitude 10.72°N, Longitude 99.37°E and Magnetic Dip Latitude 3.0°N) station, Thailand. Both foE and foEs parameters are manually scaled from ionograms recorded by FM/CW ionosonde at King Mongkut’s Institute of Technology Ladkrabang, Chumphon campus, Thailand. Chumphon is located at the magnetic equator. The observed data in the year of 2010 and 2014 are analyzed for low and high solar activity, respectively. For foE, the data during daytime (07:00-18:00 LT) are analyzed. For foEs, the daily hourly values and the seasonal (March equinox, June solstice, September equinox and December solstice) variations are analyzed. The results showed that the variation of foE during low and high solar activity were similarly, increasing during sunrise hours, reaching the highest values during noontime (11:00-13:00 LT) hours and decreasing after noontime until sunset hours. However, the foE values in 2014 were higher than those in 2010 because the sunspot number in 2014 was higher than that in 2010. For foEs, the results showed that the monthly hourly median was the maximum values in June solstice season for both years while was the minimum levels in December solstice season for 2010 and in March equinox season for 2014, respectively. This study will be helpful for communication designs and model predictions in the future.","PeriodicalId":6598,"journal":{"name":"2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"285 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79969975","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 : 2019-10-01DOI: 10.1109/ICITEED.2019.8929959
Arisara Noppakaow, O. Uchida
This research aims to examine automatic models to classify Thai online news articles. The data set is six thousands of news articles from three mainstream websites. The news articles are classified into four categories—crime news, politic news, sport news, and entertainment news. Examinations on the classification algorithms of Decision Tree, Support Vector Machine (SVM), and Deep Learning are conducted. The performance is measured by the accuracy, the recall, the precision, and the F-Measure. The results show that the accuracies of Decision Tree, SVM, and Deep Learning models are 86%, 94%, and 95%, respectively.
{"title":"Examinations on the Performance of Classification Models for Thai News Articles","authors":"Arisara Noppakaow, O. Uchida","doi":"10.1109/ICITEED.2019.8929959","DOIUrl":"https://doi.org/10.1109/ICITEED.2019.8929959","url":null,"abstract":"This research aims to examine automatic models to classify Thai online news articles. The data set is six thousands of news articles from three mainstream websites. The news articles are classified into four categories—crime news, politic news, sport news, and entertainment news. Examinations on the classification algorithms of Decision Tree, Support Vector Machine (SVM), and Deep Learning are conducted. The performance is measured by the accuracy, the recall, the precision, and the F-Measure. The results show that the accuracies of Decision Tree, SVM, and Deep Learning models are 86%, 94%, and 95%, respectively.","PeriodicalId":6598,"journal":{"name":"2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"229 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80002720","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 : 2019-10-01DOI: 10.1109/ICITEED.2019.8929939
Narumol Doungpan, Jonathan H. Chan, A. Meechai
Cancer is one of the major causes of death worldwide. Gene biomarkers identification for diagnosis, prognosis or predictive cancer is challenging work. This work aims to study the applicability of gene co-expression network (GCN) to identify gene subnetwork biomarkers for cancer using a previously developed subnetwork-based method. Four lung cancer expression datasets, gene-set, protein-protein interaction (PPI) and gene-gene interaction (GGI) data from public databases were used. The GCN was constructed using two criteria. The GCN constructed by using whole genes in the expression data with minimum spanning of the interaction within the network termed MST-based Gene Co-expression Network (MST-GCN) and the GCN was constructed by using gene members of a certain gene-set termed a Gene-set-based Gene Co-expression Network (gGCN). The subnetworks that resulted from MST-GCN and gGCN were compared with subnetworks that resulted from PPI and GGI data. The identified subnetworks were evaluated by classification performance and the overlapped gene with cancer related genes retrieved from a public database. The gGCN resulted in subnetworks that improved classification performance when compared with other network data. The identified subnetworks results from GGI contained more lung cancer related genes while the results from GCN and PPI contained more well-known lung cancer related genes.
{"title":"Utilizing Gene Co-expression Network for Identifying Subnetwork Biomarkers for Cancer","authors":"Narumol Doungpan, Jonathan H. Chan, A. Meechai","doi":"10.1109/ICITEED.2019.8929939","DOIUrl":"https://doi.org/10.1109/ICITEED.2019.8929939","url":null,"abstract":"Cancer is one of the major causes of death worldwide. Gene biomarkers identification for diagnosis, prognosis or predictive cancer is challenging work. This work aims to study the applicability of gene co-expression network (GCN) to identify gene subnetwork biomarkers for cancer using a previously developed subnetwork-based method. Four lung cancer expression datasets, gene-set, protein-protein interaction (PPI) and gene-gene interaction (GGI) data from public databases were used. The GCN was constructed using two criteria. The GCN constructed by using whole genes in the expression data with minimum spanning of the interaction within the network termed MST-based Gene Co-expression Network (MST-GCN) and the GCN was constructed by using gene members of a certain gene-set termed a Gene-set-based Gene Co-expression Network (gGCN). The subnetworks that resulted from MST-GCN and gGCN were compared with subnetworks that resulted from PPI and GGI data. The identified subnetworks were evaluated by classification performance and the overlapped gene with cancer related genes retrieved from a public database. The gGCN resulted in subnetworks that improved classification performance when compared with other network data. The identified subnetworks results from GGI contained more lung cancer related genes while the results from GCN and PPI contained more well-known lung cancer related genes.","PeriodicalId":6598,"journal":{"name":"2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"160 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80092223","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}
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