Pub Date : 2020-09-07DOI: 10.1109/ICST50505.2020.9732792
Iman Paryudi, E. Winarko, Sigit Priyanta, Sri Rezeki Candra Nursari
The current method to predict personality in personality-based recommender systems is by using Personality Extraction from Text (PET). Since this method has a flexibility weakness, a new method that is based on demographic data is proposed. The objective of this paper is to study the effect of race on the resulted model. In this study, we compare models obtained from International data, which comprise many races, and SE Asian data containing only one race. The results of the study reveal that races do influence the accuracy of the model. The International models are less accurate than those of SE Asian models are. We suspect that this happens because each race has its own personality level. This claim is supported by previous studies on personality differences across nations. These studies have found that personality differences across nations do exist. Therefore, we hypothesize that the more homogenous the data in terms of race, the more accurate the model.
{"title":"Modeling of Personality Traits based on Demographic Data on Multi-Races Samples of Ages from 13 to 50 Years Old: Investigating the Effect of Race on Model","authors":"Iman Paryudi, E. Winarko, Sigit Priyanta, Sri Rezeki Candra Nursari","doi":"10.1109/ICST50505.2020.9732792","DOIUrl":"https://doi.org/10.1109/ICST50505.2020.9732792","url":null,"abstract":"The current method to predict personality in personality-based recommender systems is by using Personality Extraction from Text (PET). Since this method has a flexibility weakness, a new method that is based on demographic data is proposed. The objective of this paper is to study the effect of race on the resulted model. In this study, we compare models obtained from International data, which comprise many races, and SE Asian data containing only one race. The results of the study reveal that races do influence the accuracy of the model. The International models are less accurate than those of SE Asian models are. We suspect that this happens because each race has its own personality level. This claim is supported by previous studies on personality differences across nations. These studies have found that personality differences across nations do exist. Therefore, we hypothesize that the more homogenous the data in terms of race, the more accurate the model.","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":"115431524","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/ICST50505.2020.9732825
S. Arjasakusuma, Sandiaga Swahyu Kusuma
Normalized Difference Vegetation Index (NDVI) data is the most commonly used vegetation proxy from remote sensing data to model the vegetation biophysical properties. The longest time-series data of NDVI from the earlier era of remote sensing satellites is available from AVHRR GIMMS employing the red and near-infrared bands in NOAA sensors from 1981 to 2015 in 8-km spatial resolution in the monthly interval. This study aims to evaluate the compatibility of NDVI data from the newer sensors such as MODIS Terra (MOD13C2), Proba-V and Visible Infrared Imaging Radiometer Suite (VIIRS) data when combined with GIMMS data. Calibration between two time-series data from different sensors was constructed by using image-matching Pseudo Invariant Features (PIF) method and the fitness levels using all pixels and at different land-cover classes were assessed. In addition, structural change analysis was conducted to identify the sensor-shift problems at the best data combination. Our results suggested the best fit of GIMMS when being paired with VIIRS data with the R2 of 0.91 (n = 3132) and 0.89 (n = 1044) for model and validation analysis. Although the fitness level from the linear regression showed a good fit, an artifact as a result of sensor-shift problems still can be detected from structural change analysis, revealing the imperfection of linear calibration method. Future works should aim to explore the performance of non-linear methods to calibrate the different time-series data and explore the combination with other sensors.
{"title":"Evaluating Multi-sensor Combination of Normalized Difference Vegetation Index (NDVI) Time Series Data over Southeast Asia","authors":"S. Arjasakusuma, Sandiaga Swahyu Kusuma","doi":"10.1109/ICST50505.2020.9732825","DOIUrl":"https://doi.org/10.1109/ICST50505.2020.9732825","url":null,"abstract":"Normalized Difference Vegetation Index (NDVI) data is the most commonly used vegetation proxy from remote sensing data to model the vegetation biophysical properties. The longest time-series data of NDVI from the earlier era of remote sensing satellites is available from AVHRR GIMMS employing the red and near-infrared bands in NOAA sensors from 1981 to 2015 in 8-km spatial resolution in the monthly interval. This study aims to evaluate the compatibility of NDVI data from the newer sensors such as MODIS Terra (MOD13C2), Proba-V and Visible Infrared Imaging Radiometer Suite (VIIRS) data when combined with GIMMS data. Calibration between two time-series data from different sensors was constructed by using image-matching Pseudo Invariant Features (PIF) method and the fitness levels using all pixels and at different land-cover classes were assessed. In addition, structural change analysis was conducted to identify the sensor-shift problems at the best data combination. Our results suggested the best fit of GIMMS when being paired with VIIRS data with the R2 of 0.91 (n = 3132) and 0.89 (n = 1044) for model and validation analysis. Although the fitness level from the linear regression showed a good fit, an artifact as a result of sensor-shift problems still can be detected from structural change analysis, revealing the imperfection of linear calibration method. Future works should aim to explore the performance of non-linear methods to calibrate the different time-series data and explore the combination with other sensors.","PeriodicalId":125807,"journal":{"name":"2020 6th International Conference on Science and Technology (ICST)","volume":"5 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":"116809808","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/ICST50505.2020.9732785
Rifqi Fauzi Rahmadzani, Widyawan, T. B. Adji
The rapid development of technology, especially in the internet field, is influencing the increasing number of texts available. In recent years, there has been an increase in research on the internet or social media to find out the sentiments in the review text. Sentiment analysis is a part of Natural Language Processing (NLP), which can help to show whether certain opinions tend to contain positive opinions or negative opinions. In this study, three sentiment polarities were studied using an Indonesian novel review dataset. Data was classified using the Long Short-Term Memory (LSTM) approach, one of the deep learning methods. To increase success rate, we used pre-trained word embedding to represent words into vectors. The analysis was performed by comparing the word embedding model using GloVe, Word2Vec i.e. Continuous Bag of Words and Skip-gram, and FastText i.e. Continuous Bag of Words and Skip-gram. The experimental results showed that sentiment analysis using the FastText Continuous Bag of Words model reached the highest accuracy of 80% while the Word2Vec Skip-gram model had the lowest accuracy of 78.3%. So, it can be concluded that the implementation of the FastText CBOW model is accurately used as a word representation to analyze sentiments on Indonesian novel review.
{"title":"Deep Learning for Sentiment Analysis in Indonesian Novel Review","authors":"Rifqi Fauzi Rahmadzani, Widyawan, T. B. Adji","doi":"10.1109/ICST50505.2020.9732785","DOIUrl":"https://doi.org/10.1109/ICST50505.2020.9732785","url":null,"abstract":"The rapid development of technology, especially in the internet field, is influencing the increasing number of texts available. In recent years, there has been an increase in research on the internet or social media to find out the sentiments in the review text. Sentiment analysis is a part of Natural Language Processing (NLP), which can help to show whether certain opinions tend to contain positive opinions or negative opinions. In this study, three sentiment polarities were studied using an Indonesian novel review dataset. Data was classified using the Long Short-Term Memory (LSTM) approach, one of the deep learning methods. To increase success rate, we used pre-trained word embedding to represent words into vectors. The analysis was performed by comparing the word embedding model using GloVe, Word2Vec i.e. Continuous Bag of Words and Skip-gram, and FastText i.e. Continuous Bag of Words and Skip-gram. The experimental results showed that sentiment analysis using the FastText Continuous Bag of Words model reached the highest accuracy of 80% while the Word2Vec Skip-gram model had the lowest accuracy of 78.3%. So, it can be concluded that the implementation of the FastText CBOW model is accurately used as a word representation to analyze sentiments on Indonesian novel review.","PeriodicalId":125807,"journal":{"name":"2020 6th International Conference on Science and Technology (ICST)","volume":"164 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":"125962424","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/ICST50505.2020.9732789
Annisa Izmi Amalia, Akhmad Hambali, Brian Pamukti
This research evaluates the performance of On-Off Keying (OOK) Modulation on the Underwater Visible Light Communication (UVLC) system. This research analyses the performance of two types of OOK signal formats, Non-Return to Zero (OOK-NRZ) and Return to Zero (OOK-RZ). This signal formats tested on distance, acceptability, Signal to Noise Ratio (SNR), Q-factor and Bit Error Rate (BER) parameters. From extensive simulations that have been done, the results show that the received power decreased 21.7249 % at the maximum distance. In this condition, the UVLC system produced the BER value of the NRZ format 3.28 × smaller than the RZ format. The SNR minimum that produced BER value less than the threshold for NRZ format is 17.925% smaller than the RZ format. Meanwhile, the minimum Q-factor that produced BER value less than 10−3for NRZ modulation is 6 × smaller than the RZ modulation format. From the results, we take the conclusion that the OOK-NRZ better than OOK-RZ on the UVLC system.
{"title":"Performance Analysis of On-Off Keying Modulation on Underwater Visible Light Communication","authors":"Annisa Izmi Amalia, Akhmad Hambali, Brian Pamukti","doi":"10.1109/ICST50505.2020.9732789","DOIUrl":"https://doi.org/10.1109/ICST50505.2020.9732789","url":null,"abstract":"This research evaluates the performance of On-Off Keying (OOK) Modulation on the Underwater Visible Light Communication (UVLC) system. This research analyses the performance of two types of OOK signal formats, Non-Return to Zero (OOK-NRZ) and Return to Zero (OOK-RZ). This signal formats tested on distance, acceptability, Signal to Noise Ratio (SNR), Q-factor and Bit Error Rate (BER) parameters. From extensive simulations that have been done, the results show that the received power decreased 21.7249 % at the maximum distance. In this condition, the UVLC system produced the BER value of the NRZ format 3.28 × smaller than the RZ format. The SNR minimum that produced BER value less than the threshold for NRZ format is 17.925% smaller than the RZ format. Meanwhile, the minimum Q-factor that produced BER value less than 10−3for NRZ modulation is 6 × smaller than the RZ modulation format. From the results, we take the conclusion that the OOK-NRZ better than OOK-RZ on the UVLC system.","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":"115277670","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/ICST50505.2020.9732870
Sesillia Fajar Kristyanti, T. F. Kusumasari, E. N. Alam
Data quality is a crucial thing presently. Poor data quality can lead to business failure and wrong decision making. One problem that arises when merging several databases is the emergence of data duplication. When merging two applications of a government agency first, it causes 39,3% of data duplication. It can cause some business problems such as storage cost, wasted marketing budget, lack of a single customer view, and lost productivity. For this reason, data quality monitoring needed to monitor and control the duplicated data. This study is a follow-up study focusing on developing a data quality monitoring module using data deduplication profiling results. The method used to develop the dashboard in this study is the operational dashboard development methodology that proposed by Suryatiningsih on her research (2011). The methodology consists of six stages, namely requirement identification, plan process, prototype design, review prototype, implementation process, and system testing. By adjusting to the predefined business rule and KPI, the operational dashboard will help the organization to monitor and control their data quality.
{"title":"Operational Dashboard Development as A Data Quality Monitoring Tools Using Data Deduplication Profiling Result","authors":"Sesillia Fajar Kristyanti, T. F. Kusumasari, E. N. Alam","doi":"10.1109/ICST50505.2020.9732870","DOIUrl":"https://doi.org/10.1109/ICST50505.2020.9732870","url":null,"abstract":"Data quality is a crucial thing presently. Poor data quality can lead to business failure and wrong decision making. One problem that arises when merging several databases is the emergence of data duplication. When merging two applications of a government agency first, it causes 39,3% of data duplication. It can cause some business problems such as storage cost, wasted marketing budget, lack of a single customer view, and lost productivity. For this reason, data quality monitoring needed to monitor and control the duplicated data. This study is a follow-up study focusing on developing a data quality monitoring module using data deduplication profiling results. The method used to develop the dashboard in this study is the operational dashboard development methodology that proposed by Suryatiningsih on her research (2011). The methodology consists of six stages, namely requirement identification, plan process, prototype design, review prototype, implementation process, and system testing. By adjusting to the predefined business rule and KPI, the operational dashboard will help the organization to monitor and control their data quality.","PeriodicalId":125807,"journal":{"name":"2020 6th International Conference on Science and Technology (ICST)","volume":"55 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":"121028257","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/ICST50505.2020.9732882
Aditia Putra Kurniawan, F. D. Wijaya, S. P. Hadi
Lightning is an inevitable natural phenomenon that causes damage to wind turbines both mechanical and electronic damage. Damage caused by overcurrent which is not immediately discharged to the ground then induces mechanical and electrical equipment. To do the analysis, simple modeling is needed so that the capability of lightning protection on the wind turbine can be determined, both already installed and to be installed. Simple modeling includes down conductor on the blade, sliding contact, spark gap, down conductor on the tower, and grounding. From the results of modeling that has been simulated using ATP Draw 3.5p10 indicates that the wind turbine which has a lightning protection system that uses down conductors on the tower is sufficient to secure the wind turbine from the risk of lightning strikes.
{"title":"A Simple Modeling of Wind Turbine When the Lightning Strike","authors":"Aditia Putra Kurniawan, F. D. Wijaya, S. P. Hadi","doi":"10.1109/ICST50505.2020.9732882","DOIUrl":"https://doi.org/10.1109/ICST50505.2020.9732882","url":null,"abstract":"Lightning is an inevitable natural phenomenon that causes damage to wind turbines both mechanical and electronic damage. Damage caused by overcurrent which is not immediately discharged to the ground then induces mechanical and electrical equipment. To do the analysis, simple modeling is needed so that the capability of lightning protection on the wind turbine can be determined, both already installed and to be installed. Simple modeling includes down conductor on the blade, sliding contact, spark gap, down conductor on the tower, and grounding. From the results of modeling that has been simulated using ATP Draw 3.5p10 indicates that the wind turbine which has a lightning protection system that uses down conductors on the tower is sufficient to secure the wind turbine from the risk of lightning strikes.","PeriodicalId":125807,"journal":{"name":"2020 6th International Conference on Science and Technology (ICST)","volume":"282 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":"121055200","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/ICST50505.2020.9732892
Bravyto Takwa Pangukir, M. R. Shihab, Bambang Parikenan, Faiz Kautsar, Kevin Christian
XYZ is one of the online marketplace businesses in Indonesia that applied extended enterprise to support its business processes. This study aimed to find out how the application of extended enterprise carried out by XYZ and its partners. The capabilities, benefits, and challenges faced by XYZ in implementing this extended enterprise were analyzed. This research also formulate recommendations for the improvement of XYZ's extended enterprise. The qualitative methodology used in this study. Data collected based on observations, interviews, and literature studies which mapped to list out challenges based on factors of the extended enterprise and ABC model to show recommendations. The results of this study indicate several challenges faced, such as information mismatch, lack of service standards by partners, and differences in work culture between partners and XYZ. Recommendations that given include the provision of tools and support systems, establishing SLAs with partners, and the application of knowledge sharing between the organization's business units.
{"title":"Analysis of Extended Enterprise Implementation in E-Commerce Business Model Case Study PT. XYZ","authors":"Bravyto Takwa Pangukir, M. R. Shihab, Bambang Parikenan, Faiz Kautsar, Kevin Christian","doi":"10.1109/ICST50505.2020.9732892","DOIUrl":"https://doi.org/10.1109/ICST50505.2020.9732892","url":null,"abstract":"XYZ is one of the online marketplace businesses in Indonesia that applied extended enterprise to support its business processes. This study aimed to find out how the application of extended enterprise carried out by XYZ and its partners. The capabilities, benefits, and challenges faced by XYZ in implementing this extended enterprise were analyzed. This research also formulate recommendations for the improvement of XYZ's extended enterprise. The qualitative methodology used in this study. Data collected based on observations, interviews, and literature studies which mapped to list out challenges based on factors of the extended enterprise and ABC model to show recommendations. The results of this study indicate several challenges faced, such as information mismatch, lack of service standards by partners, and differences in work culture between partners and XYZ. Recommendations that given include the provision of tools and support systems, establishing SLAs with partners, and the application of knowledge sharing between the organization's business units.","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":"125283322","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/ICST50505.2020.9732885
Pulung Hendro Prastyo, I. Ardiyanto, Risanuri Hidayat
Sentiment analysis is one of the text mining fields that classify the polarity of document texts and determine positive, neutral, or negative opinions. Document texts tend to have noise features or irrelevant features, so that feature selection is needed to overcome the problems. The feature selection is a challenge in sentiment analysis to produce accurate models. It is crucial for improving machine learning algorithms because it can reduce the dimensionality of feature space, remove irrelevant features, select valuable features, and increase learning accuracy. Therefore, this study focuses on reviewing feature selection techniques classified into three categories, such as filter, wrapper, and hybrid methods. The review results concluded that all feature selection techniques could select essential features, reduce the dimensionality of feature space, and improve the accuracy of machine learning algorithms. Filter methods are easy to implement and faster than wrapper and hybrid methods, whereas wrapper methods are better than filter methods in terms of accuracy but slower than filter methods. The hybrid techniques are the best feature selection method to resolve redundant and irrelevant data and increase the classifier's performance. However, hybrid methods are complicated. Thus, they need a high computational cost.
{"title":"A Review of Feature Selection Techniques in Sentiment Analysis Using Filter, Wrapper, or Hybrid Methods","authors":"Pulung Hendro Prastyo, I. Ardiyanto, Risanuri Hidayat","doi":"10.1109/ICST50505.2020.9732885","DOIUrl":"https://doi.org/10.1109/ICST50505.2020.9732885","url":null,"abstract":"Sentiment analysis is one of the text mining fields that classify the polarity of document texts and determine positive, neutral, or negative opinions. Document texts tend to have noise features or irrelevant features, so that feature selection is needed to overcome the problems. The feature selection is a challenge in sentiment analysis to produce accurate models. It is crucial for improving machine learning algorithms because it can reduce the dimensionality of feature space, remove irrelevant features, select valuable features, and increase learning accuracy. Therefore, this study focuses on reviewing feature selection techniques classified into three categories, such as filter, wrapper, and hybrid methods. The review results concluded that all feature selection techniques could select essential features, reduce the dimensionality of feature space, and improve the accuracy of machine learning algorithms. Filter methods are easy to implement and faster than wrapper and hybrid methods, whereas wrapper methods are better than filter methods in terms of accuracy but slower than filter methods. The hybrid techniques are the best feature selection method to resolve redundant and irrelevant data and increase the classifier's performance. However, hybrid methods are complicated. Thus, they need a high computational cost.","PeriodicalId":125807,"journal":{"name":"2020 6th International Conference on Science and Technology (ICST)","volume":"200 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":"131464590","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/ICST50505.2020.9732836
T. F. Kusumasari, S. R. Amethyst, M. A. Hasibuan, W. A. Nurtrisha
Data quality is essential for an enterprise system. However, several problems can eradicate the quality of data. One of them is the unfiltered data received. To overcome this issue, data engineer usually handle this such data by deploying data profiling process. There are several tools available to do this process. Each tool has its advantages according to needs. The main focus of this research is to compare the analysis results of two open-source data profiling tools based on cardinality method. The tools are Pentaho Data Integration (PDI) and Data Cleaner. The results of this study indicate that Pentaho can search for median values and distinct values for the data performed by profiling, while data cleaners cannot search for these values. Thus that Pentaho Data Integration is more detailed and specific compared to Data Cleaner
数据质量对企业系统至关重要。然而，有几个问题会影响数据的质量。其中之一是接收到的未经过滤的数据。为了克服这个问题，数据工程师通常通过部署数据分析过程来处理这些数据。有几个工具可以完成这个过程。根据需要，每种工具都有其优点。本研究的重点是比较两种基于基数方法的开源数据分析工具的分析结果。这些工具是Pentaho Data Integration (PDI)和Data Cleaner。本研究的结果表明，Pentaho可以搜索由分析执行的数据的中值和不同值，而数据清理器不能搜索这些值。因此，与Data Cleaner相比，Pentaho Data Integration更加详细和具体
{"title":"Cardinality Single Column Analysis for Data Profiling using an Open Source Platform","authors":"T. F. Kusumasari, S. R. Amethyst, M. A. Hasibuan, W. A. Nurtrisha","doi":"10.1109/ICST50505.2020.9732836","DOIUrl":"https://doi.org/10.1109/ICST50505.2020.9732836","url":null,"abstract":"Data quality is essential for an enterprise system. However, several problems can eradicate the quality of data. One of them is the unfiltered data received. To overcome this issue, data engineer usually handle this such data by deploying data profiling process. There are several tools available to do this process. Each tool has its advantages according to needs. The main focus of this research is to compare the analysis results of two open-source data profiling tools based on cardinality method. The tools are Pentaho Data Integration (PDI) and Data Cleaner. The results of this study indicate that Pentaho can search for median values and distinct values for the data performed by profiling, while data cleaners cannot search for these values. Thus that Pentaho Data Integration is more detailed and specific compared to Data Cleaner","PeriodicalId":125807,"journal":{"name":"2020 6th International Conference on Science and Technology (ICST)","volume":"11 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":"114755367","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/ICST50505.2020.9732794
R. Ferdiana
One of the efforts to improve the quality of Engineering education is to implement Outcome-based education (OBE). OBE emphasizes how every educational process produces outcomes that can help students achieve the competencies listed in student outcomes (SO). In engineering education, one of the aspects that become the competence of Engineering students is the ability to do Engineering Design (ED). Engineering design is a summative ability to identify problems, analyze problems, design solutions, and measure the success of solutions. One way to achieve this capability is to apply the Capstone Project (CP) in the learning delivery. The capstone project provides a multifaceted project that serves as a culminating academic and intellectual experience for students. However, the limitation of credit hours and the uniqueness of each course in a study program implement the Capstone Project challenge. Therefore, the quality of the capstone project will be different between one student to others. This research sees the opportunity of MOOC (Massive Open Online Course) to accelerate the engineering design skill by implementing the capstone project in blended learning delivery or as enrichment material. The article proposes an instructional report that shows how to implement a capstone project with the help of MOOC. As a result, it is shown that the xMOOC model can be applied to enriching engineering design skill. It shows that the assessment model that conducted in MOOC provides an effective way to measure the student skill that planned in course outcome.
{"title":"The Adoption of MOOC to Improve Engineering Design Skill in a Capstone Project","authors":"R. Ferdiana","doi":"10.1109/ICST50505.2020.9732794","DOIUrl":"https://doi.org/10.1109/ICST50505.2020.9732794","url":null,"abstract":"One of the efforts to improve the quality of Engineering education is to implement Outcome-based education (OBE). OBE emphasizes how every educational process produces outcomes that can help students achieve the competencies listed in student outcomes (SO). In engineering education, one of the aspects that become the competence of Engineering students is the ability to do Engineering Design (ED). Engineering design is a summative ability to identify problems, analyze problems, design solutions, and measure the success of solutions. One way to achieve this capability is to apply the Capstone Project (CP) in the learning delivery. The capstone project provides a multifaceted project that serves as a culminating academic and intellectual experience for students. However, the limitation of credit hours and the uniqueness of each course in a study program implement the Capstone Project challenge. Therefore, the quality of the capstone project will be different between one student to others. This research sees the opportunity of MOOC (Massive Open Online Course) to accelerate the engineering design skill by implementing the capstone project in blended learning delivery or as enrichment material. The article proposes an instructional report that shows how to implement a capstone project with the help of MOOC. As a result, it is shown that the xMOOC model can be applied to enriching engineering design skill. It shows that the assessment model that conducted in MOOC provides an effective way to measure the student skill that planned in course outcome.","PeriodicalId":125807,"journal":{"name":"2020 6th International Conference on Science and Technology (ICST)","volume":"517 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":"123096121","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：