Pub Date : 2020-09-07DOI: 10.1109/ICST50505.2020.9732822
Faiz Kautsar, I. Budi
PT XYZ is a state-owned company that implements SAP-based ERP system as the part of its IT Governance. However there are many problems that occur since the implementation process is carried out, there are a lot of user complaints related to the system and some users do not understand the use of the system which results in obstruction of their work (blockers). This cause some negative impacts on the company, especially related to financial aspects and employee productivity. Therefore, it is necessary to conduct a study to evaluate what factors influence the success of the implementation process and after that this research will suggest recommendations related to these factors. This study uses a research model adapted from D&M Model, TAM, and ERP CSF. Research variables in this study are Information Quality (IQ), System Quality (SYQ), and Service Quality (SEQ), Perceived Usefulness (PU), Perceived Ease of Use (PE), and Project Success (PS). Data processing and analysis methods in this study used a statistical descriptive analysis approach and SEM-PLS variant analysis. The results of this research are, PS positively affected by PU and PE, PE is positively affected SYQ and SEQ, and PU is positively affected by SYQ, SEQ, and IQ.
{"title":"Analysis of Success Factors in The Implementation of ERP System In State Owned Enterprise Case Study PT. XYZ","authors":"Faiz Kautsar, I. Budi","doi":"10.1109/ICST50505.2020.9732822","DOIUrl":"https://doi.org/10.1109/ICST50505.2020.9732822","url":null,"abstract":"PT XYZ is a state-owned company that implements SAP-based ERP system as the part of its IT Governance. However there are many problems that occur since the implementation process is carried out, there are a lot of user complaints related to the system and some users do not understand the use of the system which results in obstruction of their work (blockers). This cause some negative impacts on the company, especially related to financial aspects and employee productivity. Therefore, it is necessary to conduct a study to evaluate what factors influence the success of the implementation process and after that this research will suggest recommendations related to these factors. This study uses a research model adapted from D&M Model, TAM, and ERP CSF. Research variables in this study are Information Quality (IQ), System Quality (SYQ), and Service Quality (SEQ), Perceived Usefulness (PU), Perceived Ease of Use (PE), and Project Success (PS). Data processing and analysis methods in this study used a statistical descriptive analysis approach and SEM-PLS variant analysis. The results of this research are, PS positively affected by PU and PE, PE is positively affected SYQ and SEQ, and PU is positively affected by SYQ, SEQ, and IQ.","PeriodicalId":125807,"journal":{"name":"2020 6th International Conference on Science and Technology (ICST)","volume":"184 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132959937","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 : 2020-09-07DOI: 10.1109/ICST50505.2020.9732800
Hudalizaman, I. Ardiyanto, S. Wibirama
Deep Learning is a widely used method to solve various kinds of problems. One of the deep learning methods that are used for image classification is Convolutional Neural Network. Convolutional Neural Network has a lot of architecture. Those architectures were manually made and had excellent performance. However, due to a large number of cases tested, it results in the architecture has to be adjusted to the case. If this is manually done, then it should be time-consuming. So there should be an automatic approach to search the appropriate architecture. Neural Architecture Search is one method that is used to search for the appropriate architecture. This paper is containing reviews of Neural Architecture Search method for hyperparameter optimization on Convolutional Neural Network which is done by today's researchers.
{"title":"Network Architecture Search Method on Hyperparameter Optimization of Convolutional Neural Network: Review","authors":"Hudalizaman, I. Ardiyanto, S. Wibirama","doi":"10.1109/ICST50505.2020.9732800","DOIUrl":"https://doi.org/10.1109/ICST50505.2020.9732800","url":null,"abstract":"Deep Learning is a widely used method to solve various kinds of problems. One of the deep learning methods that are used for image classification is Convolutional Neural Network. Convolutional Neural Network has a lot of architecture. Those architectures were manually made and had excellent performance. However, due to a large number of cases tested, it results in the architecture has to be adjusted to the case. If this is manually done, then it should be time-consuming. So there should be an automatic approach to search the appropriate architecture. Neural Architecture Search is one method that is used to search for the appropriate architecture. This paper is containing reviews of Neural Architecture Search method for hyperparameter optimization on Convolutional Neural Network which is done by today's researchers.","PeriodicalId":125807,"journal":{"name":"2020 6th International Conference on Science and Technology (ICST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124357481","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 : 2020-09-07DOI: 10.1109/ICST50505.2020.9732809
B. Aditya, R. Ferdiana, S. Kusumawardani
The implementation of digital transformation has been carried out in various industrial sectors, including the higher education sector. Many countries have considered changing their education system by doing digital transformation. Although digital transformation has the potential to improve the education system, developing countries still find it difficult to reap the benefits caused by certain barriers. The purpose of this study is to investigate the barriers faced when implementing digital transformation in higher education, in this case in Indonesia. The results of the questionnaire survey ensured that of the twenty-two barriers identified based on a literature review, eleven barriers significantly affecting the implementation of digital transformation in Indonesian higher education. This study contributes by revealing initial set barriers of digital transformation in the higher education sector. The findings of this study will help identify barriers that influence the direction of decision strategies for implementing digital transformation in higher education institutions in Indonesia.
{"title":"The Study of the Barriers to Digital Transformation in Higher Education: A Preliminary Investigation in Indonesia","authors":"B. Aditya, R. Ferdiana, S. Kusumawardani","doi":"10.1109/ICST50505.2020.9732809","DOIUrl":"https://doi.org/10.1109/ICST50505.2020.9732809","url":null,"abstract":"The implementation of digital transformation has been carried out in various industrial sectors, including the higher education sector. Many countries have considered changing their education system by doing digital transformation. Although digital transformation has the potential to improve the education system, developing countries still find it difficult to reap the benefits caused by certain barriers. The purpose of this study is to investigate the barriers faced when implementing digital transformation in higher education, in this case in Indonesia. The results of the questionnaire survey ensured that of the twenty-two barriers identified based on a literature review, eleven barriers significantly affecting the implementation of digital transformation in Indonesian higher education. This study contributes by revealing initial set barriers of digital transformation in the higher education sector. The findings of this study will help identify barriers that influence the direction of decision strategies for implementing digital transformation in higher education institutions in Indonesia.","PeriodicalId":125807,"journal":{"name":"2020 6th International Conference on Science and Technology (ICST)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122882846","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 : 2020-09-07DOI: 10.1109/ICST50505.2020.9732854
Nurul Ninatin, N. Widjajanti, C. Pratama
The 2006 Yogyakarta earthquake was indicated as a result of the Opak fault which is still active today. Global Navigation Satellite System (GNSS) measurements as soon as possible after an earthquake are very important because it is an early indication of postseismic deformation. The characteristics of postseismic deformation can be modeled by logarithmic equations with the assumption that the deformations that occur due to the influence of afterslip. In this study, fifteen periodic GNSS data provided by Geodetic Laboratory Universitas Gadjah Mada (UGM) and four continuous GNSS data provided by Geospatial Information Agency of Indonesia (BIG) were used to determine the velocity and strain rate around the Opak fault. The result showed that the Yogyakarta region especially in the Opak fault area has been deformed with the variying horizontal velocity rate. The stations move to the southeast direction as an effect of the movement of the Eurasian and Indo-Australian plates. Based on the computation of the principal strain using modified least square method, strain rate value in the Opak fault area are less than 1 micro strain/yr with extensional strain is dominated. Some stations especially on continuous stations have decreased of strain values and their standard deviasion after corrected by postseismic parameters in logarithmic functions. It shows that to captured the postseismic deformation would be better to use continuous data.
{"title":"Estimation of Strain Rate in the Opak Fault with Postseismic Correction After the 2006 Yogyakarta Earthquake","authors":"Nurul Ninatin, N. Widjajanti, C. Pratama","doi":"10.1109/ICST50505.2020.9732854","DOIUrl":"https://doi.org/10.1109/ICST50505.2020.9732854","url":null,"abstract":"The 2006 Yogyakarta earthquake was indicated as a result of the Opak fault which is still active today. Global Navigation Satellite System (GNSS) measurements as soon as possible after an earthquake are very important because it is an early indication of postseismic deformation. The characteristics of postseismic deformation can be modeled by logarithmic equations with the assumption that the deformations that occur due to the influence of afterslip. In this study, fifteen periodic GNSS data provided by Geodetic Laboratory Universitas Gadjah Mada (UGM) and four continuous GNSS data provided by Geospatial Information Agency of Indonesia (BIG) were used to determine the velocity and strain rate around the Opak fault. The result showed that the Yogyakarta region especially in the Opak fault area has been deformed with the variying horizontal velocity rate. The stations move to the southeast direction as an effect of the movement of the Eurasian and Indo-Australian plates. Based on the computation of the principal strain using modified least square method, strain rate value in the Opak fault area are less than 1 micro strain/yr with extensional strain is dominated. Some stations especially on continuous stations have decreased of strain values and their standard deviasion after corrected by postseismic parameters in logarithmic functions. It shows that to captured the postseismic deformation would be better to use continuous data.","PeriodicalId":125807,"journal":{"name":"2020 6th International Conference on Science and Technology (ICST)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120949246","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 : 2020-09-07DOI: 10.1109/ICST50505.2020.9732887
Akintunde O. Iyiola, A. D. Familua, T. Shongwe, T. Swart
Noise is generated on the indoor Narrowband Power Line Communication channel by the uncoordinated activities of several electrical devices connected to the power line networks, and by radiated environmental disturbances. There is a need to overcome these noise and channel impairments for reliable communication to be achieved. Statistical channel modeling of noise will facilitate the development and optimization of dependable PLC systems. Thus, in this work, we have developed a Software-Defined-PLC transceiver and test-bed that adopts 4, 8 and 16 Quadrature amplitude modulation schemes and uses the Universal Software Radio Peripheral and MATLAB/Simulink platforms to facilitate impulsive noise error measurement and modeling using the three-state Fritchman Markov Model (FMM) and the Baum-Welch Algorithm. The statistical channel models obtained are accurate derived channel models based on experimental measurement. The close match between the experimental and model error-free run distribution and error probabilities justify the modeling of the PLC memory channel using the three-state FMM. The model results obtained will assist in the implementation of error correction systems and novel optimization techniques in an impulsive noise PLC channel environment.
{"title":"Impulse Noise Modeling in an Indoor Narrowband Power Line Communication Channel using M-QAM and a Software-Defined Radio Approach","authors":"Akintunde O. Iyiola, A. D. Familua, T. Shongwe, T. Swart","doi":"10.1109/ICST50505.2020.9732887","DOIUrl":"https://doi.org/10.1109/ICST50505.2020.9732887","url":null,"abstract":"Noise is generated on the indoor Narrowband Power Line Communication channel by the uncoordinated activities of several electrical devices connected to the power line networks, and by radiated environmental disturbances. There is a need to overcome these noise and channel impairments for reliable communication to be achieved. Statistical channel modeling of noise will facilitate the development and optimization of dependable PLC systems. Thus, in this work, we have developed a Software-Defined-PLC transceiver and test-bed that adopts 4, 8 and 16 Quadrature amplitude modulation schemes and uses the Universal Software Radio Peripheral and MATLAB/Simulink platforms to facilitate impulsive noise error measurement and modeling using the three-state Fritchman Markov Model (FMM) and the Baum-Welch Algorithm. The statistical channel models obtained are accurate derived channel models based on experimental measurement. The close match between the experimental and model error-free run distribution and error probabilities justify the modeling of the PLC memory channel using the three-state FMM. The model results obtained will assist in the implementation of error correction systems and novel optimization techniques in an impulsive noise PLC channel environment.","PeriodicalId":125807,"journal":{"name":"2020 6th International Conference on Science and Technology (ICST)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116770133","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 : 2020-09-07DOI: 10.1109/ICST50505.2020.9732824
D. Setyawan, T. F. Kusumasari, E. N. Alam
Now is the era of data. Every field has data and uses it to progress towards an innovative future. But often, the amount of data that is not balanced with good data quality ranges from differences in data formats, duplicate data, and errors in the data input process. One technique for maintaining and improving data quality is the data cleansing technique. This paper aims to propose data cleansing processing in the case of data deduplication cases using Pentaho Data Integration tools. Pentaho Data Integration done in 4 phases: Analyze, Mapping function, Design and setting, and Evaluation and test. PDI results are tested and compared with the Talend Open Studio tool. The dataset tested was data on factory names at a company in Indonesia tasked with overseeing the distribution of medicines and food. This research is expected to meet the needs of companies, especially in the field of data quality management, especially cases of data duplication and to find out the comparative results of the tools used.
现在是数据时代。每个领域都有数据，并利用它向创新的未来迈进。但是，通常情况下，数据量与良好的数据质量不平衡的范围包括数据格式的差异、重复数据和数据输入过程中的错误。维护和改进数据质量的一种技术是数据清理技术。本文旨在提出使用Pentaho数据集成工具在重复数据删除情况下的数据清理处理。Pentaho数据集成分为4个阶段:分析，映射功能，设计和设置，评估和测试。对PDI结果进行了测试，并与Talend Open Studio工具进行了比较。测试的数据集是印度尼西亚一家负责监督药品和食品分销的公司的工厂名称数据。本研究旨在满足公司的需求，特别是在数据质量管理领域，特别是在数据重复的情况下，并找出所使用的工具的比较结果。
{"title":"Data Cleansing Processing using Pentaho Data Integration: Case Study Data Deduplication","authors":"D. Setyawan, T. F. Kusumasari, E. N. Alam","doi":"10.1109/ICST50505.2020.9732824","DOIUrl":"https://doi.org/10.1109/ICST50505.2020.9732824","url":null,"abstract":"Now is the era of data. Every field has data and uses it to progress towards an innovative future. But often, the amount of data that is not balanced with good data quality ranges from differences in data formats, duplicate data, and errors in the data input process. One technique for maintaining and improving data quality is the data cleansing technique. This paper aims to propose data cleansing processing in the case of data deduplication cases using Pentaho Data Integration tools. Pentaho Data Integration done in 4 phases: Analyze, Mapping function, Design and setting, and Evaluation and test. PDI results are tested and compared with the Talend Open Studio tool. The dataset tested was data on factory names at a company in Indonesia tasked with overseeing the distribution of medicines and food. This research is expected to meet the needs of companies, especially in the field of data quality management, especially cases of data duplication and to find out the comparative results of the tools used.","PeriodicalId":125807,"journal":{"name":"2020 6th International Conference on Science and Technology (ICST)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117121259","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 : 2020-09-07DOI: 10.1109/ICST50505.2020.9732883
T. B. Waskita, R. A. Zahra, Muslih Biladi, Muhammad Nadafa Isnain, Pegi Melati, Anugrah Aditya Insani, I. Amri, D. Mardiatno, R. F. Putri
The coastal area of Parangtritis is one of the areas in Indonesia which is potentially exposed to tsunami hazards. Tsunami is a secondary hazard generated from various events before their occurrences, such as volcanic eruptions, earthquakes, landslides, and extra-terrestrial objects, that disrupting the seawater column. This research aims to estimate tsunami susceptibility using Spatial Multi-Criteria Evaluation (SMCE) method in Parangtritis, Yogyakarta, Indonesia. Physical factors such as elevation, slope, distance from the riverbank, distance from the shoreline, landform, and land cover were collected from several sources and were combined to determine the distribution of tsunami susceptible areas. The result shows susceptibility index classes vary from the lowest to the highest level. The area with the lowest susceptibility level is located in Baturagung Hill. Meanwhile, the area near the shoreline and the riverbank has a relatively high level of susceptibility. The sand dunes landform which has been relied on to decrease the susceptibility level is covered by various levels of susceptibility from the very low to high. This susceptibility distribution analysis can be used for disaster mitigation and planning purposes.
{"title":"Susceptibility Distribution Analysis of Tsunami Using Spatial Multi-Criteria Evaluation (SMCE) Method in Parangtritis, Indonesia","authors":"T. B. Waskita, R. A. Zahra, Muslih Biladi, Muhammad Nadafa Isnain, Pegi Melati, Anugrah Aditya Insani, I. Amri, D. Mardiatno, R. F. Putri","doi":"10.1109/ICST50505.2020.9732883","DOIUrl":"https://doi.org/10.1109/ICST50505.2020.9732883","url":null,"abstract":"The coastal area of Parangtritis is one of the areas in Indonesia which is potentially exposed to tsunami hazards. Tsunami is a secondary hazard generated from various events before their occurrences, such as volcanic eruptions, earthquakes, landslides, and extra-terrestrial objects, that disrupting the seawater column. This research aims to estimate tsunami susceptibility using Spatial Multi-Criteria Evaluation (SMCE) method in Parangtritis, Yogyakarta, Indonesia. Physical factors such as elevation, slope, distance from the riverbank, distance from the shoreline, landform, and land cover were collected from several sources and were combined to determine the distribution of tsunami susceptible areas. The result shows susceptibility index classes vary from the lowest to the highest level. The area with the lowest susceptibility level is located in Baturagung Hill. Meanwhile, the area near the shoreline and the riverbank has a relatively high level of susceptibility. The sand dunes landform which has been relied on to decrease the susceptibility level is covered by various levels of susceptibility from the very low to high. This susceptibility distribution analysis can be used for disaster mitigation and planning purposes.","PeriodicalId":125807,"journal":{"name":"2020 6th International Conference on Science and Technology (ICST)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123497527","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 : 2020-09-07DOI: 10.1109/ICST50505.2020.9732781
Muhammad Hafizt, Gusti Ayu Ismayanti, Mutiara Rachmat Putri, Yoniar Hufan Ramadhani, Suyarso
The Ayau Islands, located in the Pacific Ocean in Indonesia, has an extensive reef formation. However, information about the characteristics of shallow water, including coral reef and seagrass distribution, is measly in those islands. The aim of this study is to provide the lack of information by utilizing remote sensing technology and field data that was collected by Research Center for Oceanography (RCO-LIPI) through Nusa Manggala Expedition. This study uses Landsat 8 OLI as primary data besides measured field data and Ocean Color data which provide Sea Surface Temperature information. All the data used are processed using image processing and Geographic Information System techniques to obtain the result that reveals the Ayau Islands has 32,347.08 hectares of a shallow areas. The area is dominated by the MIX class due to the long tide time in a reef flat zone and occurs almost throughout the day. The coral reef cover spreads in the deeper and cooler areas while the seagrass cover grows along the coastline, which is nutrient-rich. Moreover, most of the shallow areas are not suitable for the maximum growth of coral reefs in general, which is 78.28% and 21.72% remaining requires protection mainly from anthropogenic factors.
{"title":"Identification of Reef Characteristics Using Remote Sensing Technology in Ayau Islands, Indonesia","authors":"Muhammad Hafizt, Gusti Ayu Ismayanti, Mutiara Rachmat Putri, Yoniar Hufan Ramadhani, Suyarso","doi":"10.1109/ICST50505.2020.9732781","DOIUrl":"https://doi.org/10.1109/ICST50505.2020.9732781","url":null,"abstract":"The Ayau Islands, located in the Pacific Ocean in Indonesia, has an extensive reef formation. However, information about the characteristics of shallow water, including coral reef and seagrass distribution, is measly in those islands. The aim of this study is to provide the lack of information by utilizing remote sensing technology and field data that was collected by Research Center for Oceanography (RCO-LIPI) through Nusa Manggala Expedition. This study uses Landsat 8 OLI as primary data besides measured field data and Ocean Color data which provide Sea Surface Temperature information. All the data used are processed using image processing and Geographic Information System techniques to obtain the result that reveals the Ayau Islands has 32,347.08 hectares of a shallow areas. The area is dominated by the MIX class due to the long tide time in a reef flat zone and occurs almost throughout the day. The coral reef cover spreads in the deeper and cooler areas while the seagrass cover grows along the coastline, which is nutrient-rich. Moreover, most of the shallow areas are not suitable for the maximum growth of coral reefs in general, which is 78.28% and 21.72% remaining requires protection mainly from anthropogenic factors.","PeriodicalId":125807,"journal":{"name":"2020 6th International Conference on Science and Technology (ICST)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114610739","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 : 2020-09-07DOI: 10.1109/ICST50505.2020.9732848
Y. Pasmawati, A. Tontowi, B. Hartono, T. Wijayanto
Failure rate of technology Products of Start-ups on the Online Crowdfunding Platform is quite high. One of the parameters of the failure is project quality signals of attributes. The Start-ups and the Crowdfunding Platform synergize providing campaign stimulus of project quality signals to attract backers who will give funding to the start-ups. The aims of study is determination of attributes of project quality signals. This study uses online customer reviews as a research data set to plot within 7 project quality signals attributes using Natural Language Processing (NLP). The sentiment analysis was used to classify pro-con review, the features extraction was employed to get structured-words, and TF-IDF was applied to find similarity. It was then analysed to gain response values as representative of attribute levels. Results show that response values lay of in the ranges of 0.0586 to 0.9752. The highest values of 0.9752 was campaign duration and followed by campaign description, information of backers, information of funding, video, main picture and the last was grapic design. It concludes that levelling of 7 attributes based on customer reviews could be developed by NLP method. In this, the campaign duration was the most important attribute compared to other attributes.
{"title":"Determination Of Attributes Leveling Through Online Customer Reviews Using Natural Language Processing","authors":"Y. Pasmawati, A. Tontowi, B. Hartono, T. Wijayanto","doi":"10.1109/ICST50505.2020.9732848","DOIUrl":"https://doi.org/10.1109/ICST50505.2020.9732848","url":null,"abstract":"Failure rate of technology Products of Start-ups on the Online Crowdfunding Platform is quite high. One of the parameters of the failure is project quality signals of attributes. The Start-ups and the Crowdfunding Platform synergize providing campaign stimulus of project quality signals to attract backers who will give funding to the start-ups. The aims of study is determination of attributes of project quality signals. This study uses online customer reviews as a research data set to plot within 7 project quality signals attributes using Natural Language Processing (NLP). The sentiment analysis was used to classify pro-con review, the features extraction was employed to get structured-words, and TF-IDF was applied to find similarity. It was then analysed to gain response values as representative of attribute levels. Results show that response values lay of in the ranges of 0.0586 to 0.9752. The highest values of 0.9752 was campaign duration and followed by campaign description, information of backers, information of funding, video, main picture and the last was grapic design. It concludes that levelling of 7 attributes based on customer reviews could be developed by NLP method. In this, the campaign duration was the most important attribute compared to other attributes.","PeriodicalId":125807,"journal":{"name":"2020 6th International Conference on Science and Technology (ICST)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130056645","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 : 2020-09-07DOI: 10.1109/ICST50505.2020.9732843
M. D. Faraby, O. Penangsang, R. S. Wibowo
The use of electricity will continue to increase along with technological developments and population growth so that electricity provider must maintain the availability of energy for costumers with various complex problems. Distributed Generation (DG) and Capacitor placement and Network Reconfiguration are optimization technique that have been hotly discussed in the last decade regarding power quality improvements in Radial Distribution System. In this paper discusses the effect of harmonic spreading on Radial Distribution System after optimizing DG and Capacitor placement and Network Reconfiguration simultaneously using Particle Swarm Optimization Method (PSO) by considering of the use non-linear load. The objective function in the from of minimizing active power loss and THD is considered to be able to reduce the spread of harmonic presented in several case studies. The more DG and Capacitor numbers are placed with network reconfiguration simultaneously, the better power quality in the system with a good and efficient computing approach.
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