UNS — Researchers of Universitas Sebelas Maret (UNS) Surakarta conducted a study entitled ‘Poverty and Digital Divide: A Study in Urban Poor Neighborhoods.’ The research was conducted by three UNS academic members, namely, Dr. Tri Mulyaningsih, SE., M.Si., Ph.D., Dr. Rutiana Dwi Wahyunengseh, S.Sos., M.Si., and Dr. Sri Hastjarjo, S.Sos, Ph.D.
The research, which started in 2019 and is funded by the Directorate of Higher Education (Dikti), discusses the poverty and digital divide in poor urban neighborhoods, especially in Magelang City. The city was chosen after being ranked second under Surakarta as the city with the highest poverty level in Central Java. Data collected from the Central Bureau of Statistics (BPS) shows that the poverty level in Magelang in 2016 reached 8.79% or roughly 10,630 people. The number decreased in 2017to 7.85% but still does not reach its poverty reduction target. According to the Magelang Vice Major, Windarti Agustina states that the targeted poverty level for Magelang is 6.44% in 2021.
“Magelang is a city in Central Java with a quite high population density and poverty level,” reveals Tri Mulyaningsih on Wednesday (4/8/2021). She added that the number is correlated with technology usage in this digital age. Almost all parts of the community use technology for communication, which also applies to a poor urban neighborhood.
Through a partnership with the Bappeda for Magelang city, Tri Mulyaningsih and the team decides to go to the research site directly to collect research data. Following suggestions from the Magelang Bappeda, the data is collected from three sub-district with the highest poverty level in Magelang. The sub-districts are Rejowinangun Selatan, Rejowinangun Utara, and Wates.
When asked about the research result, Tri Mulyaningsih states that poor communities in urban areas are facing difficulty in accessing digital technology because not all of the community members owned a smartphone. This condition is known as the digital divide in terms of accessibility. Other than the digital divide, the poor community is also facing low digital literacy. “They can only consume digital media, but not consuming the media critically. Not to mention on utilize the technology such as for online selling,” said Tri Mulyaningsih.
This result is in line with the initial hypothesis proposed by Tri Mulyaningsih and team, which signify the role of social-economy condition on digital technology accessibility. Therefore, according to the research result, the team proposed two policies to solve the poverty and digital divide condition.
“In general, there are two policy implications i.e., how to improve digital penetration and to provide access to the community in the form of hardware availability and infrastructure, such as equal signal quality for an urban and rural region. The second is competency to utilize technology or digital literacy,” Tri Mulyaningsih explained. Further, she states that digital literacy improvement can be conducted through various methods such as community education to filter information and technology application workshops.
The real contribution made by the team shows an effort to enhance digital literacy in the community that was realized through assistance for 10 MSMEs to use digital marketing. In the future, Tri Mulyaningsih reveals that she wants to observe whether there are any positive improvements in terms of digital access and literacy during the Covid-19 pandemic. Therefore, Dr. Mulyaningsih wishes to expand their research focus to the education sector, specifically on online learning faced by the students during the pandemic. Humas UNS
Reporter: Alinda Hardiantoro
Editor: Dwi Hastuti