Proceedings of The International Conference on Data Science and Official Statistics最新文献_第3页

Implementation of User-Oriented Geovisualization Web Dashboard for Monitoring Access to Improved Water using Satellite Imageries Data 实施面向用户的地理可视化网络控制面板，利用卫星成像数据监测获得改良水的情况

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2023-12-29 DOI: 10.34123/icdsos.v2023i1.365

F. F. Anggita, Arie Wahyu Wijayanto

引用次数: 0

GLMM and GLMMTree for Modelling Poverty in Indonesia 印度尼西亚贫困模型的 GLMM 和 GLMMTree

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2023-12-29 DOI: 10.34123/icdsos.v2023i1.333

Suseno Bayu, K. Notodiputro, B. Sartono

引用次数: 0

Automated Indonesian Text Augmentation with Web-Based Application Using Flask Framework 使用 Flask 框架的网络应用程序自动扩充印尼语文本

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2023-12-29 DOI: 10.34123/icdsos.v2023i1.324

I. A. Rahma, L. H. Suadaa

{"title":"Automated Indonesian Text Augmentation with Web-Based Application Using Flask Framework","authors":"I. A. Rahma, L. H. Suadaa","doi":"10.34123/icdsos.v2023i1.324","DOIUrl":"https://doi.org/10.34123/icdsos.v2023i1.324","url":null,"abstract":"Text classification is one of the fundamental tasks in natural language processing (NLP). In the real world, data and resources available for text classification are limited. One of the issues with labeled data is imbalanced data. The problem of imbalanced data affects the performance and accuracy of the model because the model only focuses on data with majority labels. This impacts the model performance, which tends to classify correctly for the majority label only. Meanwhile, in some cases, it is more important for the minority label to be predicted correctly. Therefore, the measure of model accuracy cannot describe the true performance of the model. To overcome this, an oversampling approach is carried out. Text-based oversampling is known as text augmentation. However, NLP resources for the Indonesian language are still limited, especially in performing text augmentation. Therefore, this research conducts the development of a web application to augment Indonesian text automatically. The application was built using the prototype method. Users can perform augmentation automatically for the entire text in the dataset. Users can select preferred augmentation techniques and are required to upload datasets as input. The output of the application is the same dataset file as the input, with an additional column containing synthetic text augmented by the application.","PeriodicalId":151043,"journal":{"name":"Proceedings of The International Conference on Data Science and Official Statistics","volume":"24 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139147897","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

Energy Poverty and Its Determinants at Subnational Level of Indonesia in 2021 2021 年印度尼西亚国家以下各级的能源贫困及其决定因素

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2023-12-29 DOI: 10.34123/icdsos.v2023i1.389

Salbila Anandia Ramadanti, Wahyuni Andriana Sofa

{"title":"Energy Poverty and Its Determinants at Subnational Level of Indonesia in 2021","authors":"Salbila Anandia Ramadanti, Wahyuni Andriana Sofa","doi":"10.34123/icdsos.v2023i1.389","DOIUrl":"https://doi.org/10.34123/icdsos.v2023i1.389","url":null,"abstract":"In the coming decades, the energy sector will soon be faced with three major transformations, one of which is energy poverty. The World Economic Forum defines energy poverty as people's limited access to modern energy services and products. Access to modern energy has not been fully met for all regions in Indonesia and disparities between regions still occur. For this reason, indicators are needed to measure the level of energy poverty at both the national and district/city levels. This study aims to analyze energy poverty in Indonesia and determine its determinants using the Multidimensional Energy Poverty Index (MEPI) approach. The data used is the March National Socio-Economic Survey and BPS Village Potential in 2021. This research uses Geographically Weighted Regression (GWR) to determine the determinants of Indonesia's multidimensional energy poverty at the district/city level in 2021. It was found that there were still inequalities in energy poverty conditions in most of Indonesia's districts/cities. Analysis using the GWR model resulted in 66 regional groups that were grouped based on the similarity of variables that had a significant effect. The level of influence of the independent variables vary across districts/cities as consequence of spatial heterogeneity in the data.","PeriodicalId":151043,"journal":{"name":"Proceedings of The International Conference on Data Science and Official Statistics","volume":"107 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139147009","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

Is The Wealth Index Better than The Proxy Means Test in Poverty Targeting? A Study in Brebes and East Jakarta 在确定贫困目标时，财富指数是否优于代理经济情况调查？布雷布斯和东雅加达研究

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2023-12-29 DOI: 10.34123/icdsos.v2023i1.302

Nuri Taufiq, I. M. G. Suyasa

{"title":"Is The Wealth Index Better than The Proxy Means Test in Poverty Targeting? A Study in Brebes and East Jakarta","authors":"Nuri Taufiq, I. M. G. Suyasa","doi":"10.34123/icdsos.v2023i1.302","DOIUrl":"https://doi.org/10.34123/icdsos.v2023i1.302","url":null,"abstract":"The ranking of household welfare status in targeting recipients of social protection programs is important and needs attention. Appropriate welfare status ranking is one of the keys for making the various types of programs designed by the government right on target. The Proxy Means Test method is popular in Indonesia in the 2015 Integrated Database Updating. Based on another popular statistical approach to ranking welfare status, the Wealth Index method is also known. Global surveys, such as Demographic and Health Surveys, Multiple Indicator Cluster Surveys, and World Food Program Surveys, have always used the Wealth Index to rank household welfare. Using Susenas data from March 2017 to March 2022, this study found that the Proxy Means Test method is better than the Wealth Index method in both Brebes Regency and East Jakarta City. The value of the classification error rate in Brebes Regency and East Jakarta City using the Proxy Means Test method is 13.94 percent and 10.37 percent, respectively. In comparison, the Wealth Index method is 25.12 percent and 14.74 percent. This research emphasizes that the results of the ranking of household welfare status are not only influenced by the method used but also by the socioeconomic conditions and characteristics of households data in the areas targeted by the program.","PeriodicalId":151043,"journal":{"name":"Proceedings of The International Conference on Data Science and Official Statistics","volume":"135 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139146378","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

Land cover change analysis of buffer areas in New Capital City of Nusantara, Indonesia: A cellular automata approach on satellite imageries data 印度尼西亚新首都努桑达拉缓冲区土地覆被变化分析：基于卫星成像数据的蜂窝自动机方法

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2023-12-29 DOI: 10.34123/icdsos.v2023i1.338

Maria Shawna Cinnamon Claire, Salwa Rizqina Putri, Arie Wahyu Wijayanto

{"title":"Land cover change analysis of buffer areas in New Capital City of Nusantara, Indonesia: A cellular automata approach on satellite imageries data","authors":"Maria Shawna Cinnamon Claire, Salwa Rizqina Putri, Arie Wahyu Wijayanto","doi":"10.34123/icdsos.v2023i1.338","DOIUrl":"https://doi.org/10.34123/icdsos.v2023i1.338","url":null,"abstract":"The proposed plan to move Indonesia's capital city to the New Capital City of Nusantara in East Kalimantan Province undoubtedly requires careful efforts to ensure food supply for the population. Population migration to the new capital may pose a food security challenge. To address this fundamental issue, one of the most crucial approaches is to establish buffer areas that can support the food needs of the new capital. The currently existing official Area Sampling Frame survey conducted by the government to assess food vulnerability faced several limitations, including weather conditions, field terrain variations, and high cost. In this study, we propose the utilization of remote sensing satellite imagery data in buffer areas to analyze changes and predict future land cover, which can provide valuable data for assessing food availability. We investigate the integration of a Cellular Automata method with the two most popular analytical methods of classical Logistic Regression and data-driven Artificial Neural Networks, known as CA-LR and CA-ANN, to identify and map land cover changes in the new capital buffer zones. Our findings reveal that both combined methods, CA-LR and CA-ANN, yield fairly promising results, with correctness and kappa statistic values exceeding 80%. Prediction results indicate that buffer areas are predominantly covered by trees, while built-up areas are still limited. The flooded vegetation cover, including rice fields, is predicted to decrease by 2024. This should be a matter of concern for stakeholders, considering the construction of the new capital city is still ongoing and the number of migrants is expected to keep rising.","PeriodicalId":151043,"journal":{"name":"Proceedings of The International Conference on Data Science and Official Statistics","volume":"14 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139147402","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

Cost-Sensitive Boosting Algorithm for Classifying Underdeveloped Regions in Indonesia 用于印度尼西亚欠发达地区分类的成本敏感提升算法

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2023-12-29 DOI: 10.34123/icdsos.v2023i1.373

Suseno Bayu, B. Sartono, K. Notodiputro

引用次数: 0

Achievement of Creative Economy Dimensions in Regional Development Indonesia in 2021 2021 年印度尼西亚区域发展实现创意经济目标

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2023-12-29 DOI: 10.34123/icdsos.v2023i1.354

Anisa Nur Jannah, Ekaria Ekaria

{"title":"Achievement of Creative Economy Dimensions in Regional Development Indonesia in 2021","authors":"Anisa Nur Jannah, Ekaria Ekaria","doi":"10.34123/icdsos.v2023i1.354","DOIUrl":"https://doi.org/10.34123/icdsos.v2023i1.354","url":null,"abstract":"So far, measurement for knowing development of creative economy in Indonesia has only seen from GDP and number of workers. Even though there are many other factors used to determine development of creative economy that are not included in these two measurements. Therefore, this study aims to develop a measurement that can be used as a tool for assessing and analyzing the state of creative economy in 34 provinces in Indonesia and for comparison. Data used is secondary that sourced from BPS and several agencies. Creative Economy Index (CEI) refers to Global Innovation Index which is composed from seven dimensions, institution, human capital and research, infrastructure, market sophistication, business sophistication, knowledge and technology outputs, creative outputs. Analysis method used is factor analysis to validate dimensions of CEI based on their indicators. Results showed that Indonesia`s CEI is relatively low. Dimension with highest achievement is institution, while lowest achievement is market sophistication. When compared by region, CEI in Western Region is higher than Eastern Region. There are also similarities with HDI and ICT-DI.","PeriodicalId":151043,"journal":{"name":"Proceedings of The International Conference on Data Science and Official Statistics","volume":" 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139144340","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

Small Area Estimation of Multidimensional Poverty in East Java Province Using Satellite Imagery 利用卫星图像对东爪哇省小面积多维贫困进行估算

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2023-12-29 DOI: 10.34123/icdsos.v2023i1.417

Helen Cantika Laura Aisyatul Ridho, Rindang Bangun Prasetyo

{"title":"Small Area Estimation of Multidimensional Poverty in East Java Province Using Satellite Imagery","authors":"Helen Cantika Laura Aisyatul Ridho, Rindang Bangun Prasetyo","doi":"10.34123/icdsos.v2023i1.417","DOIUrl":"https://doi.org/10.34123/icdsos.v2023i1.417","url":null,"abstract":"The government has so far focused on a monetary approach to overcoming poverty, while poverty is multidimensional. Holistic and accurate poverty indicators are needed as material for policy formulation, such as the Multidimensional Poverty Index (IKM), which is calculated from raw data from the National Socioeconomic Survey (SUSENAS). However, the direct estimation of the multidimensional poverty headcount (AKM) is only accurate at the provincial level, as seen from the relative standard error (RSE) of several districts and cities, which is still above 25 percent. Increasing the sample size requires time, effort, and cost, so the Small Area Estimation (SAE) method can be an alternative. Apart from using official statistics for accompanying variables, satellite imagery has the advantage of being up-to-date and available up to a granular level. This study aims to estimate the AKM at the district/city level in East Java Province by utilizing satellite imagery and official statistics in SAE. The results showed that SAE HB Beta-logistics, with the accompanying variables combined with satellite imagery and official statistics, has a higher accuracy than direct estimation.","PeriodicalId":151043,"journal":{"name":"Proceedings of The International Conference on Data Science and Official Statistics","volume":"54 s188","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139145941","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

Agricultural Digitalization: Can This Transformation Increase Farmers' Income In East Java? 农业数字化：这种变革能否增加东爪哇农民的收入？

Proceedings of The International Conference on Data Science and Official Statistics Pub Date : 2023-12-29 DOI: 10.34123/icdsos.v2023i1.412

Reni Amelia, Akhmad Munim

{"title":"Agricultural Digitalization: Can This Transformation Increase Farmers' Income In East Java?","authors":"Reni Amelia, Akhmad Munim","doi":"10.34123/icdsos.v2023i1.412","DOIUrl":"https://doi.org/10.34123/icdsos.v2023i1.412","url":null,"abstract":"The era of the industrial revolution 4.0 has encouraged various economic sectors to utilize technology and information in their activities, including the agricultural sector. This study provides an overview of the impact of agricultural digitization on farmers' income and examines the characteristics of farmers in East Java who have and have not utilized agricultural digitalization as a first step toward agricultural extension targets. The data comes from the August 2022 National Labor Force Survey in East Java conducted by BPS-Statistics Indonesia with a sample size of 7.852 farmers carrying out agricultural businesses. The t-Student test results show that farmers who utilize agricultural digitization have an average income higher than those who do not utilize it. The binary logistic regression results also show that digitization of agriculture, gender, education, agricultural business field, and business status also affect farmers' income. The results random undersampling analysis and random oversampling classification and regression trees results show that there are two types of characteristics of farmers in East Java who take advantage of agricultural digitization, namely farmers who graduated at least junior high school and farmers who graduated elementary school/equivalent, come from X, Y, or Z generations, and work assisted by permanent workers/paid workers.","PeriodicalId":151043,"journal":{"name":"Proceedings of The International Conference on Data Science and Official Statistics","volume":"28 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139147519","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