Big data for government policy: Potential implementations of bigdata for official statistics in Indonesia

Pramana, Setia; Yuniarto, Budi; Kurniawan, Robert; Yordani, Ricky; Jong-Gun, Lee; Amin, Imaduddin; Satyaning, P. P. Ni Luh Putu; Riyadi, Yulistina; Nashirah, Hasyyati, Atika; Indriani, Rina

doi:10.1109/iwbis.2017.8275097

Cited by 14 publications

(7 citation statements)

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“…Natural disaster data processing is commonly done is using big data techniques (Yu, Yang, and Li, 2018), data mining (Zheng et al, 2013;Caraka et al, 2020;Cios et al, 2007), and IoT (Kamruzzaman et al, 2017;Sakhardande, Hanagal, and Kulkarni, 2016). Big Data is an umbrella term for the explosion in the quantity and diversity of highfrequency digital data and it is not usually coming from traditional sources (Pramana et al, 2017;Cenggoro et al, 2019;Maroco et al, 2011). The cycle in the Big Data program is divided into four.…”

Section: Discussionmentioning

confidence: 99%

Social Vulnerability and How It Matters: A Bibliometric Analysis

Toharudin

Suprijadi

Caraka

et al. 2021

Int. J. Criminol. Sociol.

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nterdisciplinary and cross-cultural studies of the impacts of environment and social vulnerability must be undertaken to address the problem of social vulnerability in the foreseeable future. Scientist or social scientists should first continuously strive towards approaches can integrate municipal technological expertise, experiences, knowledge, perceptions, and expectations into emergency circumstances, so that people can be sharper on issues and offer responses with their matters. In this paper. We performing the Bibliometric Analysis to review published papers on the keyword 'Social Vulnerability'. There are 29,468 papers published in the last 52 years from 1969 to November 2020. Disaster research by implementing the Internet of Things (IoT), data mining, machine learning is still needed.

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Section: Discussionmentioning

confidence: 99%

Social Vulnerability and How It Matters: A Bibliometric Analysis

Toharudin

Suprijadi

Caraka

et al. 2021

Int. J. Criminol. Sociol.

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“…We used in this research are as follows: (1) channel: transaction type for property advertisements, (2) property type: there are 5 categories of property types displayed, (3) subdistrict: subdistricts in Jakarta and advertisements are served, (4) built up: building area of the property, (5) land area: land area of the property, ( 6) bedroom: number of bedrooms in the property, (7) bathroom: number of bathrooms in the property, (8) certificate: description of property certificate, (9) condition: condition of the building, i.e. used or new, (10) completion date: date the advertisement was broadcast, (11) price: property price, (12) price unit: description of the price paid per day, month, or year, and (13) transacted: advertising description has been sold or is still active and not.…”

Section: Datamentioning

confidence: 99%

“…Big Data has great potential to support Official Statistics (Pramana et al, 2017). One of big data sources digital coentent from a website.…”

Section: Introductionmentioning

confidence: 99%

The Impact During of Pandemic COVID-19 on Property Sector Case Study: DKI Jakarta Province

Arkandana¹,

Mariel²,

Pramana³

2023

JEI

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Since the COVID-19 pandemic in Indonesia, economic conditions have declined, especially in the property sector but if we look at the distribution value of the real estate sector in 2020 during the pandemic, its contribution has increased to 6.31% after falling by 5.94% in 2019. Another impact is that the Property Price Index growth value decreases over the years, but in a big city like DKI Jakarta, it does not affect the pandemic condition. Big Data has the potential to produce useful and useful statistics and assist in the collection of Official Statistics data. This study aims to see the condition of the number of advertisings on the property side and the selling price of houses and apartments that can be impacted by the pandemic COVID-19. Based on data from one property site in Indonesia, the condition of ad serving during the pandemic is very influential, with the highest serving during the Micro Indonesia large-scale social restrictions (PSBB).

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“…Standardization of the price of a record is carried out to equalize the size of a unit [14]. According to the concept and definition of BPS-Statistics itself, retail traders use transactions with standard units such as kilograms and liters.…”

Section: • Price Standardizationmentioning

confidence: 99%

Implementation of marketplace data in the production of Consumer Price Index in Indonesia

Haqqoni

Pramana

2022

Self Cite

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Digital Economy in recent years, especially in Southeast Asia, including Indonesia, is growing rapidly. E-commerce is one part of the Digital Economy. BPS-Statistics Indonesia as a Non-ministerial Government Agency responsible directly to the president has conducted an E-commerce Survey in 2019. From this publication, it is concluded that the interest of Indonesian traders using the internet in selling in recent years has increased. So, the urgency of using e-commerce data in its application in official Statistics is increasingly needed. Several studies have carried out the application of e-commerce data in the calculation of The Consumer Price Index (CPI). In this research, e-commerce data is applied with a case study using the data from one of online marketplaces in Indonesia in calculating CPI at city level in Java. The purpose of this study is to compare the marketplace-based CPI data and BPS-Statistics’ survey-based CPI. The data is collected through web scraping techniques and followed by preprocessing data and analyzed descriptively. Web scraper that is built can be used in obtaining data. Commodity-level CPI with marketplace data tends to have relatively large prices which result in higher CPI being compared to BPS-Statistics CPI. Meanwhile, at the expenditure group level, the CPI between the two approaches is broadly similar in general.

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Big data for government policy: Potential implementations of bigdata for official statistics in Indonesia

Cited by 14 publications

References 1 publication

Social Vulnerability and How It Matters: A Bibliometric Analysis

Social Vulnerability and How It Matters: A Bibliometric Analysis

The Impact During of Pandemic COVID-19 on Property Sector Case Study: DKI Jakarta Province

Implementation of marketplace data in the production of Consumer Price Index in Indonesia

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