Proceedings of The International Conference on Data Science and Official Statistics最新文献_第6页

Knowledge Management System in Official Statistics: An Empirical Investigation on Indonesia Population Census 官方统计中的知识管理系统:基于印尼人口普查的实证调查

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2022-01-04 DOI: 10.34123/icdsos.v2021i1.25

Achmad Muchlis Abdi Putra, A. Wijayanto

{"title":"Knowledge Management System in Official Statistics: An Empirical Investigation on Indonesia Population Census","authors":"Achmad Muchlis Abdi Putra, A. Wijayanto","doi":"10.34123/icdsos.v2021i1.25","DOIUrl":"https://doi.org/10.34123/icdsos.v2021i1.25","url":null,"abstract":"National statistical offices around the world show a strong interest in producing reliable, objective, and accurate information in compliance with a high level of professional and scientific standards. Such a set of information provided by government agencies is known as the official statistics. To support the potential of knowledge-based business processes and deliver high-quality public services, knowledge management systems (KMS) are undoubtedly required. In this work, we study the impact of embracing KMS in one of the most massive scale statistical census in South East Asia, the 2020 Indonesia Population Census (IPC2020). The regression analysis is utilized in this study where the perceived usefulness is the dependent variable and the perceived ease of use become the independent variable. Our findings reveal that KMS utilization gains a positive influence on the perceived ease of use and usefulness among the stakeholders and organizing personnel. This provides an incentive to enlarge the range of implementation and improve the system and infrastructure capability to better support the knowledge-driven collaboration among stakeholders of the statistical office.","PeriodicalId":151043,"journal":{"name":"Proceedings of The International Conference on Data Science and Official Statistics","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133617142","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: 3

Demographics Characteristics of Smoker in Poor Households in Riau Islands Province 廖内群岛省贫困家庭吸烟者的人口统计学特征

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2022-01-04 DOI: 10.34123/icdsos.v2021i1.85

Dio Dwi Saputra

{"title":"Demographics Characteristics of Smoker in Poor Households in Riau Islands Province","authors":"Dio Dwi Saputra","doi":"10.34123/icdsos.v2021i1.85","DOIUrl":"https://doi.org/10.34123/icdsos.v2021i1.85","url":null,"abstract":"Smoking habits in Indonesia have been formed since the colonial era. Smoking habits that need attention are in poor households. In 2020, Riau Islands Province as the one of youngest provinces in Indonesia has a smoking prevalence of 26.16% and the percentage of poor people is 5.92%. This condition is the basis for researchers to conduct a study that aims to determine the demographics characteristics of smokers. This study uses raw data from the National Socio-Economic Survey (SUSENAS) in Riau Islands Province in March 2020. The variables used are smoking status, gender, age group, education level, region, and recent migrant. The output of the processing stage is that the prevalence of smoking will be greater in the male population (OR = 132.04), the age group of 46-65 (OR = 4.77), the age group of 66 and over (OR = 2.11), the junior high school level (OR = 4.66), the senior high school level (OR = 5.98), the college level (OR = 3.13), living in the urban area (OR = 1.22) and the recent migrant (OR = 3.12). Thus, it is necessary to make a specific policy following the above characteristics in reducing smoking habits among poor households.","PeriodicalId":151043,"journal":{"name":"Proceedings of The International Conference on Data Science and Official Statistics","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127422177","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

R Package Development for Difference Benchmarking in Small Area Estimation Fay-Herriot Model 小面积估计Fay-Herriot模型差分基准的R包开发

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2022-01-04 DOI: 10.34123/icdsos.v2021i1.69

Zaza Yuda Perwira, A. Ubaidillah

{"title":"R Package Development for Difference Benchmarking in Small Area Estimation Fay-Herriot Model","authors":"Zaza Yuda Perwira, A. Ubaidillah","doi":"10.34123/icdsos.v2021i1.69","DOIUrl":"https://doi.org/10.34123/icdsos.v2021i1.69","url":null,"abstract":"In recent decades, the use of small area estimation (SAE) for producing official statistics has been widely recognized by many National Statistics Offices including BPS-Statistics Indonesia. For official statistics usage, the aggregation of small area estimates is expected to be numerically consistent and more efficient than the aggregation of the unbiased direct estimates that cannot be guaranteed by Fay-Herriot model. Simulation experiments are performed to assess the behaviour of the difference benchmarking method Fay-Herriot model and to compare the mean squared error (MSE). The result shows that the difference benchmarking method can produce a consistent aggregation towards the direct estimation. Furthermore, an R package was built to implement the method that is easier to be used and is already available in the CRAN website. The package has been evaluated using validity (simulation), performance, case studies, and usability tests. These evaluations show that the package is suitable for use. Implementation of the methodology is also be applied to estimate average household consumption per capita expenditure in districts in D.I. Yogyakarta province, Indonesia 2019","PeriodicalId":151043,"journal":{"name":"Proceedings of The International Conference on Data Science and Official Statistics","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115089044","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

Preserving Women Public Restroom Privacy using Convolutional Neural Networks-Based Automatic Gender Detection 基于卷积神经网络的自动性别检测保护女性公共厕所隐私

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2022-01-04 DOI: 10.34123/icdsos.v2021i1.29

Desi Kristiyani, A. Wijayanto

{"title":"Preserving Women Public Restroom Privacy using Convolutional Neural Networks-Based Automatic Gender Detection","authors":"Desi Kristiyani, A. Wijayanto","doi":"10.34123/icdsos.v2021i1.29","DOIUrl":"https://doi.org/10.34123/icdsos.v2021i1.29","url":null,"abstract":"Personal safety and privacy have been the significant concerns among women to use and access public restrooms/toilets, especially in developing countries such as Indonesia. Privacy-enhancing designs are unquestionably expected to ensure no men entering the rooms neither intentionally nor accidentally without prior notice. In this paper, we propose a facial recognition approach to ensure women's safety and privacy in public restroom areas using Convolutional Neural Networks (CNN) model as a gender classifier. Our main contributions are as follows: (1) a webcam feed automatic gender detection model using CNN which may further be connected to a security alarm (2) a publicly available gender-annotated image dataset that embraces Indonesian facial recognition samples. Supplementary Indonesian facial examples are taken from a government-affiliated college, Politeknik Statistika STIS students' photo datasets. The experimental results show a promising accuracy of our proposed model up to 95.84%. This study could be beneficial and useful for wider implementation in supporting the safety system of public universities, offices, and government buildings.","PeriodicalId":151043,"journal":{"name":"Proceedings of The International Conference on Data Science and Official Statistics","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132958083","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

Antisocial Behavior Monitoring Services of Indonesian Public Twitter Using Machine Learning 使用机器学习的印尼公共推特反社会行为监测服务

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2022-01-04 DOI: 10.34123/icdsos.v2021i1.181

Fitri Andri Astuti

{"title":"Antisocial Behavior Monitoring Services of Indonesian Public Twitter Using Machine Learning","authors":"Fitri Andri Astuti","doi":"10.34123/icdsos.v2021i1.181","DOIUrl":"https://doi.org/10.34123/icdsos.v2021i1.181","url":null,"abstract":"Antisocial behavior is a personality disorder that has characteristics such as repetitive actions that violate social norms, deceit and lying, impulsiveness, irritability and aggression, reckless disregard for the safety of oneself and others, consistently irresponsible, and lack of remorse. The cause can be from various factors, including genetics, psychological conditions, interactions in the environment, and wrong parenting. The impact of antisocial behavior on social life can cause people to tend to be aggressive and take it into action by not having feelings of guilt for their actions. Thus, a monitoring of antisocial behavior disorders is needed so that it can be a warning for the public to be more concerned about the difficulties experienced by each other. The potential gained from the availability of tweet data access from the Twitter API opens up opportunities for monitoring antisocial behavior. By utilizing traditional machine learning and deep learning methods, it can be an opportunity to automate labeling on Twitter data that contains elements of antisocial behavior. Based on the description of the problems and opportunities found, this study proposes a multi-class classification monitoring service to identify public antisocial behavior on Twitter Indonesia using machine learning.","PeriodicalId":151043,"journal":{"name":"Proceedings of The International Conference on Data Science and Official Statistics","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116582000","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

Entity Matching of Shop Accounts in Online Commerce Portals 在线商务门户中店铺账户的实体匹配

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2022-01-04 DOI: 10.34123/icdsos.v2021i1.71

Dina Salsabila, Takdir Takdir

引用次数: 0

Analysis of Rice Field Cluster in Indonesia as an Evaluation of Food Production Availability Using Fuzzy C-Means 基于模糊c均值的印尼稻田集群粮食生产有效性评价

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2022-01-04 DOI: 10.34123/icdsos.v2021i1.245

Heru Setiono, Toto Dianto

引用次数: 0

Do Tourist Attraction Objects Implement Health Protocols? Analysis of Tourist Attraction Object in East Java Province Using Google Maps Review 旅游景点是否执行卫生协议?基于Google地图的东爪哇省旅游景点对象分析

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2022-01-04 DOI: 10.34123/icdsos.v2021i1.64

Disya Pratistaning Ratriatmaja, Nucke Widowati Kusumo Projo

{"title":"Do Tourist Attraction Objects Implement Health Protocols? Analysis of Tourist Attraction Object in East Java Province Using Google Maps Review","authors":"Disya Pratistaning Ratriatmaja, Nucke Widowati Kusumo Projo","doi":"10.34123/icdsos.v2021i1.64","DOIUrl":"https://doi.org/10.34123/icdsos.v2021i1.64","url":null,"abstract":"The COVID-19 pandemic has impacted the tourism sector, particularly the Tourist Attraction Object (TAO) in Indonesia. This research aims: to analyse the implementation of health protocols and facility conditions at TAO, to analyse the change in visitor sentiment and rating towards TAO before and during the COVID-19 pandemic, to analyse the close relationship between ratings and reviews of visitor sentiment on TAO, to analyse the possibility of web scraping data to complement tourism data from BPS Statistics Indonesia. Using Google Maps review, this research uses the Multinomial Naïve Bayes (MNB), Term Frequency-Inverse Document Frequency (TF-IDF), pseudo-labelling, and word association methods. The results show that the health protocol has been implemented in TAO of East Java province, the available facilities are good, and there is no change in reviews during the TAO pandemic. The Stuart-Kendall Tau-c value shows a weak relationship in a positive direction between rating and review sentiment. According to Haversine, Jaro Winkler, and Levenshtein, the data calculation indicates that web scraping data can complement tourism data for BPS-Statistics Indonesia.","PeriodicalId":151043,"journal":{"name":"Proceedings of The International Conference on Data Science and Official Statistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115604772","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

Knowledge-based Utilization in Organizational IT Support. A Case Study at BPS-Statistics Indonesia 组织IT支持中的知识利用。BPS-Statistics Indonesia的案例研究

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2022-01-04 DOI: 10.34123/icdsos.v2021i1.48

Herlambang Permadi, D. I. Sensuse

引用次数: 0

An insight into Youth Unemployment in Indonesia 对印尼青年失业的洞察

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2022-01-04 DOI: 10.34123/icdsos.v2021i1.229

Ayuningtyas Yanindah

{"title":"An insight into Youth Unemployment in Indonesia","authors":"Ayuningtyas Yanindah","doi":"10.34123/icdsos.v2021i1.229","DOIUrl":"https://doi.org/10.34123/icdsos.v2021i1.229","url":null,"abstract":"Youth unemployment in Indonesia has continued to remain at a high level relative to other age categories for several years. The case of Indonesia’s youth unemployment is grave with the presence of a low workforce participation rate, informal employment, and higher unemployment rates in young people compared with adults. Due to the lack of research on a country-wise view of youth unemployment, this study focuses on providing a much better understanding of the youth unemployment problem in emerging countries, especially Indonesia. The main aim of the paper is to bridge the research gap on youth unemployment with reference to microeconomic determinants, such as educational background and participation in training. This study utilized the August 2019 data of SAKERNAS (Survei Angkatan Kerja Nasional) and analyzed the data using the logistic regression method. Logistic regression is a special econometric model where the dependent variable is considered categorical and dichotomous (binary); in this case, it was unemployed (1) or working (0). The study found that training participation has a negative correlation with youth unemployment, while educational attainment generates mixed results.","PeriodicalId":151043,"journal":{"name":"Proceedings of The International Conference on Data Science and Official Statistics","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123274799","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: 4