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INDONESIA
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS
Published by Politeknik Statistika STIS
ISSN : 28099842     EISSN : -     DOI : -
Core Subject : Science,
Computer Science & IT
International Conference on Data Science and Official Statistics International Conference on Data Science and Official Statistics (ICDSOS) 2023 is organized by Politeknik Statistika STIS and Statistics Indonesia (BPS). This international conference in collaboration with Forum Pendidikan Tinggi Statistika (FORSTAT), Ikatan Statistisi Indonesia (ISI), United Nations Economic and Social Commission for Asia and the Pacific (UNESCAP), and United Nations Statistics Division (UNSD). The ICDSOS will bring together statisticians and data scientists from academia, official statistics, health sector and business, junior and senior professionals, in an inviting hybrid environment on November 24th - 25th, 2023. Dealing with the theme of this conference is Harnessing Innovation in Data Science and Official Statistics to Address Global Challenges towards the Sustainable Development Goals. DATA SCIENCE Machine Learning and Deep Learning Data Science and Artificial Intelligence (AI) Data Mining and Big Data Statistical Software Information System Development for Official Statistics Remote Sensing to Strengthen Official Statistics Other data science relevant topic APPLIED STATISTICS Applied Multivariate Analysis Applied Time Series Analysis Applied Spatial Statistics Applied Bayesian Statistics Microeconomics Modelling and Applications Macroeconomics Modelling and Applications Econometrics Modelling and Applications Quantitative Public Policy and Statistical Analysis Applied Statistics on Demography Applied Statistics on Population Studies Applied Statistics on Biostatistics and Public health Other applied statistics relevant topic OFFICIAL STATISTICS Official Statistics Survey Methodology Developments Data Collection Improvements Sustainable Development Goals (SDGs) Indicators Estimation Small Area Estimation (SAE) Non Response and Imputation Methods Sampling Error and Non Sampling Error Evaluation Benchmarking Regional Official Statistics Other official statistics relevant topic
Arjuna Subject : Umum - Umum
Articles 251 Documents
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Unlocking potential of data: A localized data-driven approach for stunting reduction in South Kalimantan Province Farah Rizkiah
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2023 No. 1 (2023): Proceedings of 2023 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2023i1.394

Abstract

This study addresses the issue of stunting in South Kalimantan Province, where high stunting prevalence rates persist. Through a comprehensive analysis of factors influencing stunting prevalence, predictive modeling using machine learning, and clustering analysis of districts based on stunting rates, the research aims to support the provincial government in formulating effective and sustainable strategies. The findings highlight influential factors such as HDI, poverty rates, immunization coverage, breasfed babies, number of uninhabitable houses, and access to clean water. The study also utilise machine learning to build model that aids in predicting future stunting prevalence, while clustering analysis categorizes districts into distinct groups. These insights guide the government in prioritizing interventions, setting prevalence targets, and determining strategic areas for stunting reduction efforts.
Role of E-Commerce on Entrepreneurial Welfare in Indonesia Fitriani Aditya Putri
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2023 No. 1 (2023): Proceedings of 2023 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2023i1.397

Abstract

This study aims to determine the role of the use of e-commerce on the welfare of entrepreneurs in Indonesia during the Covid-19 pandemic. Based on the August 2021 Sakernas data sourced from BPS, the estimation results using binomial logistic regression show that e-commerce has an important role in increasing the welfare of entrepreneurs in Indonesia during the Covid-19 pandemic. The use of e-commerce was able to increase the income of entrepreneurs in Indonesia. Entrepreneurial activities using e-commerce are quite promising in the midst of limited business fields and post-pandemic economic recovery conditions in Indonesia, so the government needs to provide economic support and training to develop digital entrepreneurship activities in the labor force in Indonesia.
Lean User Experience (Lean UX) Approach in the Redesign of the SOBAT BPS Application Migunani Puspita Eugenia; Lutfi Rahmatuti Maghfiroh
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2023 No. 1 (2023): Proceedings of 2023 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2023i1.398

Abstract

SOBAT BPS is a service provided by BPS to be used by partners and prospective partners of BPS throughout Indonesia. Alongside the utilization of the SOBAT BPS application, user reviews and assessments become significant elements in measuring the quality and success of this application. Feedback obtained from these assessments indicates that a redesign of the SOBAT BPS application is necessary to provide a better user experience. Prior to redesigning the SOBAT BPS application, a preliminary survey was conducted to understand user perceptions of the current system using heuristic evaluation and the user experience questionnaire (UEQ). Based on the preliminary survey results, there are issues related to the implementation of heuristic principles in the SOBAT BPS application, and only the UEQ stimulation scale received a good ranking. Therefore, the aim of this research is to redesign the SOBAT BPS application using the Lean UX method and to evaluate the redesigned results using heuristic evaluation and UEQ. The evaluation results of the redesigned SOBAT BPS application indicate that the redesign is superior to the current SOBAT BPS application.
Curating Multimodal Satellite Imagery for Precision Agriculture Datasets with Google Earth Engine Bagus Setyawan Wijaya; Rinaldi Munir; Nugraha Priya Utama
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2023 No. 1 (2023): Proceedings of 2023 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2023i1.399

Abstract

In the era of modern agriculture, satellite imagery has been widely used to monitor crops, one of which is paddy. This paper tries to describe the vegetation indices, climate, and soil index features related to paddy plants and curates a collection of satellite imagery on the Google Earth Engine (GEE). This paper reveals how GEE can be used to collect and process multimodal satellite imagery to form a precision agriculture dataset. The objective of this study is to establish a comprehensive precision agriculture dataset by leveraging multimodal satellite imagery to monitor paddy crops. The data collected as a dataset originates from 306 locations in Karawang Regency, Indonesia, during the 2019-2020 period. In the first step, we identify the relevant features essential for paddy crop analysis. Subsequently, we carefully select image collections within GEE based on these features. Afterward, we perform data acquisition and necessary preprocessing through the Google Colab environment. The results showed that satellite imagery from Sentinel-2 outperforms Landsat 8 in terms of spatial and temporal resolution. Apart from that, the generated dataset successfully captures the growth patterns of paddy plants.
FORECASTING USING SARIMA AND BAYESIAN STRUCTURAL TIME SERIES METHOD FOR RANGE SEASONAL TIME MUHAMMAD RIZAL; Sri Utami Zuliana
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2023 No. 1 (2023): Proceedings of 2023 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2023i1.402

Abstract

Data containing seasonal patterns, the SARIMA and Bayesian Structural Time Series methods, are time series methods that can be used on this type of data. This research aims to determine the steps of the SARIMA model and Bayesian Structural Time Series, applying the SARIMA model and Structural Bayesians Time Series, get the forecasting results of the SARIMA model and Bayesian Structural Time Series with MAPE measurements. The research method used is a quantitative method applied to data on the number of PT KAI train passengers in the Java region for 2006-2019. The results of this research show that the best model for forecasting the number of PT KAI train passengers in the Java region in 2006-2019 is SARIMA (2,1,0)(0,1,2)[12] with a MAPE value of 4.77% compared to the Bayesian method structural time series [12] namely 5.25%.
Development of FASIH Application for the Badan Pusat Statistisk using Flutter Framework Riofebri Prasetia Prasetia; Lutfi Rahmatuti Maghfiroh Maghfiroh
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2023 No. 1 (2023): Proceedings of 2023 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2023i1.404

Abstract

One of the data collection methods used by the Badan Pusat Statistik (BPS) is Computer Assisted Personal Interviewing (CAPI). Currently, CAPI, known as FASIH, is continuously updated by BPS using the Kotlin programming language, which can run on the Android platform. It is possible that FASIH will be needed in a multiplatform form. However, there is an alternative for multiplatform application development, namely Flutter, which can be used in the development of FASIH. Nevertheless, BPS has not conducted any study on the development of the FASIH application using Flutter, hence the strengths and weaknesses of implementing this technology in FASIH application development remain unknown. Therefore, the author aims to conduct a study on the development of the FASIH application utilizing Flutter. The application development is carried out using the Rapid Application Development (RAD) Prototyping method. The resulting application is tested using black box testing and performance testing using a third-party application, Apptim. The black box testing results indicate that the application meets the functional requirements of stakeholders. In terms of performance, the Kotlin version of FASIH outperforms the Flutter version. However, Flutter has an advantage in accelerating development time. Additionally, concerning user interface development, the Flutter version of the FASIH application can run on multiple platforms. Nevertheless, further integration is required to ensure the proper functioning of the Flutter version of the FASIH application.
Forest Cover Mapping Using Interactive Dashboards with Google Earth Engine on Sentinel-2 Satellite Imagery Nora Dzulvawan; Arie Wahyu Wijayanto
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2023 No. 1 (2023): Proceedings of 2023 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2023i1.409

Abstract

The study aims to develop an attractive web-based visualization dashboard for mapping forest land cover around the world. The dashboard map was created using the Google Earth Engine application with JavaScript programming language. The built-in map dashboard has several interactive features, including legend, zoom, search, composite index view selection, visualization date selection, and wipers. The results of the dashboard black box test show that the dashboard works well and provides good visualization in mapping forest land cover for better monitoring and analysis.
Agricultural Digitalization: Can This Transformation Increase Farmers' Income In East Java? Reni Amelia; Akhmad Munim
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2023 No. 1 (2023): Proceedings of 2023 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2023i1.412

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.
Using Data Science to Assess the Impact of Disaster Event on Climate Change Belief: Case of Australian Bushfire Catastrophe Diaz Prasetyo; Trisna Mulyati
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2023 No. 1 (2023): Proceedings of 2023 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2023i1.413

Abstract

Australia, vulnerable to bushfire incidents due to its unique climatic conditions, witnessed a transformative event in the 2019-2020 bushfire season. This research examines the impact of these bushfires on public perception of climate change. Leveraging robust statistical techniques, including McNemar's hypothesis testing and logistic regression, the study deciphers survey data collated pre and post these fires. The study's hypothesis that post-fire respondents are more likely to acknowledge climate change's role is confirmed. Factors such as education, political affiliation, and support for fossil fuel reduction are identified as influential predictors of climate change belief. The analysis also highlights the complex interplay of demographic characteristics and media exposure in shaping attitudes. Notably, direct firebush exposure showed a nuanced relationship with belief. The research underscores a significant shift in Australian attitudes toward climate change following the bushfires. These findings contribute to our understanding of public opinion dynamics and the role of experiential factors in climate change belief.
Formulation of Kumaraswamy Generalized Inverse Lomax Distribution Andrew Bony Nabasar Manurung; Siti Nurrohmah; Ida Fithriani
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2023 No. 1 (2023): Proceedings of 2023 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2023i1.416

Abstract

Lifetime data is a type of data that consists of a waiting time until an event occurs and modelled by numerous distributions. One of its characteristics that is interesting to be studied is the hazard function due to the flexibility that it has compared to other characteristics of distribution. Inverse Lomax (IL) distribution is one of the distributions considered to have advantages in modelling hazard shape and extended in several ways to address the problem of non-monotone hazard which is often encountered in real life data. However, it needs to be extended to another family of distribution to increase its modelling potential and Kumaraswamy Generalized (KG) family of distribution is used as it adds two more parameters to the distribution. The newly developed distribution is called the Kumaraswamy Generalized Inverse Lomax (KGIL) distribution. The main characteristics of KGIL distribution will be derived, such as cumulative distribution function (cdf), probability density function (pdf), hazard function, and survival function. Maximum likelihood method will also be used to estimate the parameters. The application of the new model is based on head-and-neck cancer lifetime data set. The modelling results show that the KGIL distribution is the best to capture important details of the data set considered

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