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All Journal Jurnal Tata Kelola dan Akuntabilitas Keuangan Negara Indonesian Journal of Statistics and Its Applications
Simanjuntak, Tigor Nirman
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Computer Science & IT Economics, Econometrics & Finance Mathematics Social Sciences Other

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Overlapping assistance distribution of the Indonesian government’s scheme for small and micro-scale enterprises during COVID-19 Tusianti, Ema; Abdurrahman, Abdurrahman; Simanjuntak, Tigor Nirman
Jurnal Tata Kelola dan Akuntabilitas Keuangan Negara Vol. 9 No. 2 (2023): JTAKEN Vol. 9 No. 2 December 2023
Publisher : Badan Pemeriksa Keuangan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28986/jtaken.v9i2.1211

Abstract

The Indonesian Government introduced a financial government scheme called Bantuan Produktif Usaha Mikro (the BPUM) to protect and support the operations of small and microscale enterprises (SMEs) during the difficulties of the COVID-19 pandemic. This study describes the BPUM distribution based on the characteristics of its recipients. Using the 2021 National Socioeconomic Survey and the binary logistic regression method, it is found that BPUM tends to be allocated to recipients with levels of education below university level, who are male, have access to the internet, and live in urban areas. Surprisingly, the BPUM is also distributed to the beneficiaries accessing microfinance, such as People’s Business Credit (Kredit Usaha Rakyat, KUR). However, those beneficiaries are not supposed to be the scheme’s recipients. This situation indicates that BPUM is not being accurately distributed. In contrast, the BPUM is also distributed to households that receive several social protection programs simultaneously, including those from the State Budget, Local Government Budget, and Special Autonomy Funds (Otsus) at the local level. Furthermore, the study reveals issues with data integration and highlights inefficiencies in budget allocation. These findings serve as valuable insights for program evaluation, aiming to enhance the allocation of BPUM or another similar program to rightful recipients and increase its effectiveness in supporting SMEs.
Sentiment Analysis on Overseas Tweets on the Impact of COVID-19 in Indonesia Simanjuntak, Tigor Nirman; Pramana, Setia
Indonesian Journal of Statistics and Applications Vol 5 No 2 (2021)
Publisher : Statistics and Data Science Program Study, SSMI, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v5i2p304-313

Abstract

This study aims to conduct analysis to determine the trend of sentiment on tweets about Covid-19 in Indonesia from the Twitter accounts overseas on big data perspective. The data was obtained from Twitter in the period of April 2020, with the word query "Indonesian Corona Virus" from foreign user accounts in English. The process of retrieving data comes from Twitter tweets by crawling the text using Twitter's API (Application Programming Interface) by employing Python programming language. Twitter was chosen because it is very fast and easy to spread through status updates from and among the user accounts. The number of tweets obtained was 8,740 in text format, with a total engagement of 217,316. The data was sorted from the tweets with the largest to smallest engagement, then cleaned from unnecessary fonts and symbols as well as typo words and abbreviations. The sentiment classification was carried out by analytical tools, extracting information with text mining, into positive, negative, and neutral polarity. To sharpen the analysis, the cleaned data was selected only with the largest engagement until those with 100 engagements; then was grouped into 30 sub-topics to be analyzed. The interesting facts are found that most tweets and sub-topics were dominated by the negative sentiment; and some unthinkable sub-topics were talked by many users.
Co-Authors Abdurahman Abdurrahman Pramana, Setia Tusianti, Ema