2020 6th International Conference on Science in Information Technology (ICSITech)最新文献_第2页

Utilizing Morphological Features for Part-of-Speech Tagging of Bahasa Indonesia in Bidirectional LSTM 基于形态特征的印尼语词性标注双向LSTM

2020 6th International Conference on Science in Information Technology (ICSITech) Pub Date : 2020-10-21 DOI: 10.1109/ICSITech49800.2020.9392076

I. N. P. Trisna, Aina Musdholifah, Yunita Sari

引用次数: 2

Prediction of Junior High School National Exam Results Based on Academic Report Using K-Nearest Neighbor 基于k近邻的学业报告预测初中统考成绩

2020 6th International Conference on Science in Information Technology (ICSITech) Pub Date : 2020-10-21 DOI: 10.1109/ICSITech49800.2020.9392052

U. Pujianto, Mei Candra Kartikasari, Harits Ar Rosyid

引用次数: 0

Graduates Profile Mapping based on Job Vacancy Information Clustering 基于职位空缺信息聚类的毕业生Profile映射

2020 6th International Conference on Science in Information Technology (ICSITech) Pub Date : 2020-10-21 DOI: 10.1109/ICSITech49800.2020.9392067

R. Megasari, E. Piantari, R. Nugraha

{"title":"Graduates Profile Mapping based on Job Vacancy Information Clustering","authors":"R. Megasari, E. Piantari, R. Nugraha","doi":"10.1109/ICSITech49800.2020.9392067","DOIUrl":"https://doi.org/10.1109/ICSITech49800.2020.9392067","url":null,"abstract":"Nowadays, an industry’s expectation that’s often not fulfilled by job applicants require companies to actively cooperate with universities, one of the reasons is through employees that is considered to have good performance to find talents within their alma mater. This research aims to analyze job vacancy information uploaded by graduates for juniors in their university that can be mapped into a graduate’s profile and evaluation materials in making a curriculum. Collected job vacancy information from several communication media are generally unstructured data which requires it to be preprocessed first through a data mining convention to produce several terms ready to be processed, continued with implementation of TF-IDF, feature extraction using PCA, and grouping using k-Means algorithm. The clustering analysis found 3 job clusters i.e. developer, teacher and researcher/lecturer as job vacancies that frequently shared by graduates. This result obtained from clustering analysis using 10 words as a minimum document frequency based on Elbow Method and Silhouette Coefficient analysis.","PeriodicalId":408532,"journal":{"name":"2020 6th International Conference on Science in Information Technology (ICSITech)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131952187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Performance Study of Facial Expression Recognition Using Convolutional Neural Network 基于卷积神经网络的面部表情识别性能研究

2020 6th International Conference on Science in Information Technology (ICSITech) Pub Date : 2020-10-21 DOI: 10.1109/ICSITech49800.2020.9392070

Marde Fasma’ul Aza, N. Suciati, S. Hidayati

引用次数: 2

Stevedoring Time Estimation on Smart Port Services Using K-NN Algorithm 基于K-NN算法的智能港口服务装卸时间估计

2020 6th International Conference on Science in Information Technology (ICSITech) Pub Date : 2020-10-21 DOI: 10.1109/ICSITech49800.2020.9392055

Dimas Khrisna Ramadhani, F. Novian, Okkie Puspitorini, N. Siswandari, H. Mahmudah, A. Wijayanti

{"title":"Stevedoring Time Estimation on Smart Port Services Using K-NN Algorithm","authors":"Dimas Khrisna Ramadhani, F. Novian, Okkie Puspitorini, N. Siswandari, H. Mahmudah, A. Wijayanti","doi":"10.1109/ICSITech49800.2020.9392055","DOIUrl":"https://doi.org/10.1109/ICSITech49800.2020.9392055","url":null,"abstract":"Smart Port Service serves the process of ship queuing automatically using a configured system. Inside is an estimated ship docking time (Stevedoring Time). The ship docking time estimation is done to predict the loading and unloading time of the ship at the port. This will later support smart port to create a queue on each dock. To create a stevedoring time estimation system, KNN (K-Nearest Neighbor) is used to classify ships based on specifications from the ship. This ship classification is based on Length of All (LOA) or length of ship, Grosston or tonnage of ships and commodities from ships. Ship specifications will be provided by the Long Range (LoRa) device after LoRa has previously detected the ship to be docking. KNN will make the class based on data from the port of Tanjung Perak. This class is divided into 5 which is the estimated time of docking from the ship. The results after the system was tested resulted in an accuracy of 94.3% in providing estimated docking time from ships. And the most influential parameter in this research is ship commodity. The efficiency of stevedoring process in port could minimize the budget of ship expenses.","PeriodicalId":408532,"journal":{"name":"2020 6th International Conference on Science in Information Technology (ICSITech)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123467903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Strategic Alignment Maturity Level Model Using Drivers of Change in a Business Environment 在商业环境中使用变更驱动的战略一致性成熟度级别模型

2020 6th International Conference on Science in Information Technology (ICSITech) Pub Date : 2020-10-21 DOI: 10.1109/ICSITech49800.2020.9392036

A. Wahyudin, Widodo, Aulia Fauziah Nasuha, E. Junaeti

{"title":"Strategic Alignment Maturity Level Model Using Drivers of Change in a Business Environment","authors":"A. Wahyudin, Widodo, Aulia Fauziah Nasuha, E. Junaeti","doi":"10.1109/ICSITech49800.2020.9392036","DOIUrl":"https://doi.org/10.1109/ICSITech49800.2020.9392036","url":null,"abstract":"Achieving results, we often used the word “change”, nevertheless the process behind that word is not easy and sometimes intricate. On the other hand, determining whether an organization has changed or not is another matter that requires standardize assessment. It is clear that the business environment is uncertain and faced with tremendous change due to the influence of globalization, information systems and technology, and the knowledge economy which affects the behavior of our society and will continue to do so. Alignment between business strategy and information system strategy remains a challenge for business organizations, especially in the current digital era. The purpose of this research is to produce a Strategic Alignment Maturity Level Model of business-IS alignment through three drivers of change, namely business, technology, customer, and management. Luftman’s Strategic Alignment Maturity Model is the reference used. Preliminary studies, designing and developing an instrument model, determining the strategic alignment maturity level, determining strategic recommendations, and built an application system are the stages of this research. Expert judgment is involved in linguistic assessment and strategy recommendations. The last step was an experiment to see the suitability of the final level and the strategy recommendations issued. The model for determining the alignment level of IS-Business with business, technology and management and customers as a driver of change and dedicated software is the result of this research, can be used as an alternative technique in the information system strategic planning process to determine needs or to evaluate the implementation of recommendations.","PeriodicalId":408532,"journal":{"name":"2020 6th International Conference on Science in Information Technology (ICSITech)","volume":"273 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132958472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Conformed Dimension Identification on Fusion Cubes Using Synonym, Hypernym, and Hyponym 使用同义词、上义和下义的融合多维数据集的一致维度识别

2020 6th International Conference on Science in Information Technology (ICSITech) Pub Date : 2020-10-21 DOI: 10.1109/ICSITech49800.2020.9392042

Trisna Ari Roshinta, T. E. Widagdo, F. N. Azizah

{"title":"Conformed Dimension Identification on Fusion Cubes Using Synonym, Hypernym, and Hyponym","authors":"Trisna Ari Roshinta, T. E. Widagdo, F. N. Azizah","doi":"10.1109/ICSITech49800.2020.9392042","DOIUrl":"https://doi.org/10.1109/ICSITech49800.2020.9392042","url":null,"abstract":"The complex analysis needs of decision-makers may require variety data cubes that are spread over heterogeneous cubes. The decision-makers need to obtain as many relevant cubes as possible according to their queries. In this condition, the decision-makers need to combine heterogeneous cubes into new single cube (which is called fusion cubes process). This makes the conformed dimensions identification becomes necessary. Conformed dimensions are dimensions that represent the same objects in the real world, as links between cubes to be merged in fusion cubes. In previous studies, conformed dimensions identification in the fusion cubes was carried out using syntactic similarity with the Jaro-Winkler algorithm and semantic similarity with synonym relation between dimensions. However, not all conformed dimensions are identified. This affects the cubes that should be relevant are not included in the fusion cube. Therefore, this study tries to improve the conformed dimensions identification by adding hypernym and hyponym besides synonym in the conformed dimensions identification method. The proposed method presents a higher recall value than the method using only synonym. This shows that the use of hypernym and hyponym can improve the search for relevant cubes. Meanwhile, the proposed method results lower precision than the method using only synonym. This shows that the error rate of the proposed method is higher than the method using only synonym. However, based on F-measure, that is the balance score of recall and precision, the proposed method has a better F-measure value than method using only synonym.","PeriodicalId":408532,"journal":{"name":"2020 6th International Conference on Science in Information Technology (ICSITech)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127429219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Performance Analysis of Neo4j, MongoDB, and PostgreSQL on 2019 National Election Big Data Management Database Neo4j、MongoDB、PostgreSQL在2019年全国大选大数据管理数据库中的性能分析

2020 6th International Conference on Science in Information Technology (ICSITech) Pub Date : 2020-10-21 DOI: 10.1109/ICSITech49800.2020.9392041

Linggis Galih Wiseso, Mahmud Imrona, A. Alamsyah

{"title":"Performance Analysis of Neo4j, MongoDB, and PostgreSQL on 2019 National Election Big Data Management Database","authors":"Linggis Galih Wiseso, Mahmud Imrona, A. Alamsyah","doi":"10.1109/ICSITech49800.2020.9392041","DOIUrl":"https://doi.org/10.1109/ICSITech49800.2020.9392041","url":null,"abstract":"Data has now become a major commodity and asset for any organization. There’s also a phenomenon called Big Data where it’s a term to describes a large volume of data, both structured and unstructured. With big data, any organization can analyze the data and its results are used for decision making and business strategy. Political parties, for example, use it to analyze the likelihood of their candidate winning in the election based on voter data who votes for their candidate. In Indonesia itself, the use of big data has not been utilized because of limited database infrastructure. Therefore, Indonesia needs a good database that can utilize big data. In this study, the author examines the performance of PostgreSQL, MongoDB, and Neo4J by analyzing each of its complexity using computational complexity theory with Big O notation as its tool. With Big O, the author measures the complexity of each execution time. The conclusion from this study is that MongoDB has excellent performance because it has an O(1) complexity, PostgreSQL has good performance because it has an O(n) and O(1) complexities, and Neo4j has worse performance than MongoDB and PostgreSQL because it has an O(nlog n) complexity.","PeriodicalId":408532,"journal":{"name":"2020 6th International Conference on Science in Information Technology (ICSITech)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121067992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Development Mobile Learning For Vegetable Farming In Indonesia Based On Mobile Cloud Computing 基于移动云计算开发印尼蔬菜种植移动学习

2020 6th International Conference on Science in Information Technology (ICSITech) Pub Date : 2020-10-21 DOI: 10.1109/ICSITech49800.2020.9392074

Erlangga, Y. Wihardi, Eki Nugraha

引用次数: 4

Face Skin Disease Detection with Textural Feature Extraction 基于纹理特征提取的面部皮肤病检测

2020 6th International Conference on Science in Information Technology (ICSITech) Pub Date : 2020-10-21 DOI: 10.1109/ICSITech49800.2020.9392030

Wirdayanti, Irwan Mahmudi, Andi Chairul Ahsan, A. A. Kasim, Rosmala Nur, Rafifah Basalamah, Anindita Septiarini

引用次数: 1