Proceedings of The International Conference on Data Science and Official Statistics最新文献_第7页

Impact Evaluation of Child Labor on Health in Next 7 and 14 Years in Indonesia 印度尼西亚未来7年和14年童工对健康的影响评价

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2022-01-04 DOI: 10.34123/icdsos.v2021i1.195

Febri Hamdani, Eny Sulistyaningrum

引用次数: 0

Data Input Quality Metrics on Mobile Positioning Data (MPD) 移动定位数据的数据输入质量度量

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2022-01-04 DOI: 10.34123/icdsos.v2021i1.134

A. R. M. Munaf, Amanda Pratama Putra, Wa Ode Zuhayeni Madjida, Ignatius Aditya Setyadi, Amin R. S. Nugroho

{"title":"Data Input Quality Metrics on Mobile Positioning Data (MPD)","authors":"A. R. M. Munaf, Amanda Pratama Putra, Wa Ode Zuhayeni Madjida, Ignatius Aditya Setyadi, Amin R. S. Nugroho","doi":"10.34123/icdsos.v2021i1.134","DOIUrl":"https://doi.org/10.34123/icdsos.v2021i1.134","url":null,"abstract":"Statistics Indonesia (BPS) has been using Mobile Positioning Data (MPD) to support official statistics since 2016. As a source of big data, MPD also has veracity characteristics, indicating uncertainty in the data. Therefore, it is necessary to check that the data are good enough to allow further analysis and the quality assurance process. Currently, there is no established international standard for quality assurance of MPD. This paper describes the quality matrix used by BPS in examining data from mobile operators. BPS uses thirteen indicators in conducting quality assurance, where the inspection uses several different methods, such as setting a threshold, checking data completeness, and checking the form of data distribution. Exploratory Data Analysis is carried out to determine whether the data meets the requirements for further analysis. We conducted this research on a mobile network operator data for June - July 2020 as the basis for MPD analysis in 2021. Based on the inspection during this period, BPS can cooperate with this cellular operator to conduct data analysis in 2021. However, the operator must repeat the calculation of the required matrix as quality assurance every month.","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":"129433775","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

SMOTE and Nearmiss Methods for Disease Classification with Unbalanced Data 非平衡数据下疾病分类的SMOTE和near - miss方法

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2022-01-04 DOI: 10.34123/icdsos.v2021i1.240

Anas Rulloh Budi Alamsyah, Salsabila Rahma Anisa, Nadira Sri Belinda, A. Setiawan

{"title":"SMOTE and Nearmiss Methods for Disease Classification with Unbalanced Data","authors":"Anas Rulloh Budi Alamsyah, Salsabila Rahma Anisa, Nadira Sri Belinda, A. Setiawan","doi":"10.34123/icdsos.v2021i1.240","DOIUrl":"https://doi.org/10.34123/icdsos.v2021i1.240","url":null,"abstract":"Unbalanced data are often encountered in practice. They complicate the search for a model suitable for classification. This is because the number of individuals who have a history of a disease is less than the number of individuals who do not. We analyse the IFLS 5 data on medical history of a set of patients. We split the dataset in the proportion 80:20 to training and test subsets. Of course, both datasets are unbalanced, with only a small minority of patients who had a stroke. We apply the SMOTE and Nearmiss methods and evaluate the rate of correct classification. After being treated using the two methods, the training data was transformed into balanced data. The classification process is carried out to test the comparison of the effectiveness of the two methods in solving the problem of unbalanced data. Based on the results obtained, it can be concluded that the Nearmiss method is better than SMOTE in balancing the data. It was obtained by comparing several measures such as accuracy, F-score, Kappa, sensitivity, and specificity on the SMOTE and Nearmiss methods.","PeriodicalId":151043,"journal":{"name":"Proceedings of The International Conference on Data Science and Official Statistics","volume":"54 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":"127543993","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

What We Know from Telemedicine Data in Indonesia? Study case using Alodokter, Dokter.id, and Honestdocs 我们从印尼的远程医疗数据中了解到什么?使用Alodokter的学习案例，Dokter。id和Honestdocs

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2022-01-04 DOI: 10.34123/icdsos.v2021i1.53

Faza Nur Fuadina, Nucke Widowati Kusumo Projo, Siti Mariyah

{"title":"What We Know from Telemedicine Data in Indonesia? Study case using Alodokter, Dokter.id, and Honestdocs","authors":"Faza Nur Fuadina, Nucke Widowati Kusumo Projo, Siti Mariyah","doi":"10.34123/icdsos.v2021i1.53","DOIUrl":"https://doi.org/10.34123/icdsos.v2021i1.53","url":null,"abstract":"The internet and technology development arise in various aspects of life in Indonesia, including in the health sector with e-health. Telemedicine utilization as a form of e-health was still rare among Indonesians because its existence is not as much as e-commerce that is more related to the economic sector. The COVID-19 pandemic has limited people's movement to get health care, but it made people use telemedicine in Indonesia. This research aims to analyze telemedicine utilization in Indonesia and see the health phenomena captured in the data. This research uses descriptive analysis and text mining to determine the utilization of telemedicine with the Named Entity Recognition (NER) and Latent Dirichlet Allocation (LDA) methods. In addition, a literature review is also used to identify the potential use of telemedicine data in collecting health statistics in Indonesia. The results show that telemedicine has been widely used in Indonesia. The clinical teleconsultation data and article titles on telemedicine produce various health topics. Therefore, telemedicine data can potentially be used as a source for collecting health statistics.","PeriodicalId":151043,"journal":{"name":"Proceedings of The International Conference on Data Science and Official Statistics","volume":"7 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":"131870679","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

Welfare Index of Person with Disabilities in Indonesia, 2018 2018年印度尼西亚残疾人福利指数

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2022-01-04 DOI: 10.34123/icdsos.v2021i1.225

Ni Putu Ayu Chyntia Manikka Sari, T. Siagian

{"title":"Welfare Index of Person with Disabilities in Indonesia, 2018","authors":"Ni Putu Ayu Chyntia Manikka Sari, T. Siagian","doi":"10.34123/icdsos.v2021i1.225","DOIUrl":"https://doi.org/10.34123/icdsos.v2021i1.225","url":null,"abstract":"Most people with disabilities in Indonesia still live in vulnerable, backward, or poor conditions due to restrictions, obstacles, difficulties, and reduction or elimination of the rights of persons with disabilities. In realizing prosperity for all Indonesian people, it should be fair and not contain discriminatory elements, including persons with disabilities. For this reason, a measure of the achievement of the welfare of persons with disabilities is needed as evaluation support material in making plans and policies. This study aims to obtain the welfare factors of persons with disabilities and compile them into the Welfare Index of Persons with Disabilities (WIPD). The construction of the WIPD was carried out using the exploratory factor analysis method. Based on the results, 20 indicators formed five factors, namely accessibility, housing and access to information, physical and spiritual well-being, social relations and sanitation, and economic well-being. From the WIPD scores, it is known that there is a gap in WIPD achievement between the Western and the Eastern Region of Indonesia. For this reason, the government needs to prioritize inclusive development in provinces with very low and low WIPD achievements.","PeriodicalId":151043,"journal":{"name":"Proceedings of The International Conference on Data Science and Official Statistics","volume":"3 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113936761","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

Measuring Child Poverty in Jakarta Metropolitan Area Using a Multidimensional Perspective 多维视角下的雅加达大都市区儿童贫困测算

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2022-01-04 DOI: 10.34123/icdsos.v2021i1.219

Nigel Roy Tantan, Erni Tri Astuti

引用次数: 0

Estimation of Inflation Threshold of Indonesia and Its Effect on Economic Growth Periode 1981-2019 1981-2019年印尼通胀阈值估算及其对经济增长的影响

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2022-01-04 DOI: 10.34123/icdsos.v2021i1.230

Monika Stevany Manurung, Aisyah Fitri Yuniasih

{"title":"Estimation of Inflation Threshold of Indonesia and Its Effect on Economic Growth Periode 1981-2019","authors":"Monika Stevany Manurung, Aisyah Fitri Yuniasih","doi":"10.34123/icdsos.v2021i1.230","DOIUrl":"https://doi.org/10.34123/icdsos.v2021i1.230","url":null,"abstract":"Sustainable economic growth with a low and stable inflation rate is one of the goals of macroeconomic policy in improving people's welfare. High inflation can be detrimental to economic growth in the medium and long term, while a certain level of inflation is needed to move the economy. Therefore, the question arises about the level of inflation that does not have a negative impact on economic growth. This study aims to estimate the inflation threshold level and identify its effect on Indonesia's economic growth 1981-2019. The research begins by determining the best model among the models that regress inflation on economic growth with quadratic regression, Hansen's (2000) threshold regression, and Mubarik's (2005) threshold regression (2005). The best model is the Mubarik threshold regression model (2005) with an inflation threshold of 6.85 percent. Mubarik's (2005) threshold regression analysis was reused in the model involving the FDI variable, the inflation threshold was 7.11 percent, and FDI had a positive effect. Inflation below the inflation threshold encourages economic growth, while inflation above the inflation threshold is detrimental to economic growth. The result of the estimated threshold level is higher than the inflation target by BI, so that inflation targeting can be increased.","PeriodicalId":151043,"journal":{"name":"Proceedings of The International Conference on Data Science and Official Statistics","volume":"40 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":"128022335","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

Does Palapa Ring Project Infrastructure Bridging Connectivity and Economic Activity? 帕拉帕环项目的基础设施能连接互联互通和经济活动吗?

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2022-01-04 DOI: 10.34123/icdsos.v2021i1.99

Realita Eschachasthi, Taly Purwa, Diyang Gita Cendekia

引用次数: 0

The Effect of the Digital Economy on Indecent Work in Indonesia 2019 2019年印度尼西亚数字经济对不雅工作的影响

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2022-01-04 DOI: 10.34123/icdsos.v2021i1.88

Yuniar Putri Awaliyah Risky, Nucke Widowati Kusumo Projo

引用次数: 0

Development of The Welfare Index at Sub-district Level in West Java 2020: A Small Area Estimation Approach 西爪哇2020年街道级福利指数的发展:小区域估算方法

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2022-01-04 DOI: 10.34123/icdsos.v2021i1.144

Nimas Ezra Monadiyan, Faisal Haris

{"title":"Development of The Welfare Index at Sub-district Level in West Java 2020: A Small Area Estimation Approach","authors":"Nimas Ezra Monadiyan, Faisal Haris","doi":"10.34123/icdsos.v2021i1.144","DOIUrl":"https://doi.org/10.34123/icdsos.v2021i1.144","url":null,"abstract":"Welfare as an alternative measure for poverty, is an important indicator to measure. But there is no composite indicator that specifically measures the prosperity of a population yet. Considering the increase of data needed and the lack of available data at the smaller level, this study develops the Welfare Index at sub-district level for West Java in 2020 using a small area estimation approach to explain the condition of welfare of the population. The indicators in sub-district level formed in this study were created from two kinds of data. The first type of indicators were formed from SUSENAS using Small Area Estimation and the other type of indicators were formed from PODES aggregation. All the indicators were then processed with factor analysis to form the Welfare Index. The Welfare Index formed shows the range of 22.86 to 83.76 and generally higher in the northern part of West Java. This index has a correlation of 0.798 with the Human Development Index because of the components that defined both indexes. The existence of this correlation shows that the Welfare Index formed is able to explain the conditions/phenomena being measured.","PeriodicalId":151043,"journal":{"name":"Proceedings of The International Conference on Data Science and Official Statistics","volume":"10 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":"124625864","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