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All Journal EkBis: Jurnal Ekonomi dan Bisnis Jurnal Pertanahan
Dewi, Ima Sartika
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Agriculture, Biological Sciences & Forestry Humanities Economics, Econometrics & Finance Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences

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Determinants of Poverty in East Java During The COVID-19 Pandemic Dewi, Ima Sartika; Nursiyono, Joko Ade
EkBis: Jurnal Ekonomi dan Bisnis Vol. 7 No. 1 (2023): EkBis: Jurnal Ekonomi dan Bisnis
Publisher : Fakultas Ekonomi dan Bisnis Islam, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/EkBis.2023.7.1.1603

Abstract

The global COVID-19 pandemic has infected million people in Indonesia. East Java has experienced Indonesia’s epicentre of positive COVID-19 cases. The economic disruption in East Java due to COVID-19 pandemic has led to increase the number of poor people. This study aims to examine the determinants of poverty during the pandemic outbreak. In this study, we employed multiple linear regression. The results reveals that simultaneously the cumulative number of COVID-19, unemployment rate, Gini Ratio, population density, human development index (HDI), and GRDP per capita affect the risk of poverty in East Java. Partially, the cumulative number of COVID-19, unemployment rate, population density, and HDI shows a significant effect to poverty. While the Gini ratio and GRDP per capita has an insignificant effect. The increase on cumulative number of COVID-19 cases is likely to increase the risk of poverty. Similarly, unemployment has a positive significant affect on poverty. The increase on unemployment rate tends to increase the number of poor people. Contrary, the HDI and population density have a negatively significant effect to poverty. The increase on HDI and population density tends to increase the number of poor people.
Analisis Tagar #WadasMelawan di Media Sosial Twitter Menggunakan Social Network Analysis (SNA) Nursiyono, Joko Ade; Dewi, Ima Sartika
Jurnal Pertanahan Vol 12 No 2 (2022): Jurnal Pertanahan
Publisher : Sekolah Tinggi Pertanahan Nasional

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Abstract

ABSTRAK Pembebasan tanah Desa Wadas untuk pembangunan Bendungan Bener telah menimbulkan kontroversi antara warga dan pemerintah. Pembangunan Bendungan Bener diharapkan dapat menampung air untuk irigasi lahan pertanian, menyuplai air baku dan energi listrik. Di balik kemanfaatannya, pembangunan Bendungan Bener menimbulkan kerugian besar yang dapat merusak ekosistem. Sebagai bentuk penolakan, netizen membuat tagar #WadasMelawan yang tersebar luas di jejaring Twitter. Penelitian ini bertujuan untuk mengidentifikasi aktor-aktor yang utama dalam penyebarluasan tagar #WadasMelawan dengan menggunakan Social Network Analysis (SNA). Data yang digunakan dalam penelitian ini dikumpulkan dari Twitter dan diolah dengan menggunakan perangkat lunak Gephi. Hasil penelitian menunjukkan bahwa terdapat 1.005 aktor dengan jumlah interaksi sebanyak 1.471 kali. Kedekatan antar aktor bernilai 7, artinya jarak antar aktor cukup dekat dan interaksi antar aktor cukup mudah. Indikator yang digunakan untuk mengetahui aktor yang paling berpengaruh yaitu degree centrality, closeness centrality, betweenness centrality, eigenvector centrality, dan follower rank. Hasilnya, interaksi yang tercipta dalam jaringan tagar #WadasMelawan didominasi oleh akun @oposisicerdas dan @geloraco. ABSTRACTThe land acquisition of Wadas Village for the construction of the Bener Dam has attracted controversy. Bener Dam is expected to hold water for irrigation of agricultural land, supplying water for household and electrical energy. Behind its usefulness, the construction of the Bener Dam causes huge losses that can damage the ecosystem. As a form of rejection, netizens created the hashtag #WadasMelawan that is widespread on Twitter. The study aims to identify the main actors in spreading #WadasMelawan hashtags using Social Network Analysis (SNA). The data used in the study was collected from Twitter and processed using Gephi. The results showed that there were 1,005 actors with the number of interactions as many as 1,471 times. The closeness between actors is 7, it means the distance between actors is quite close, and the interaction between actors is quite easy. Indicators used in this study to determine the most influential actors are degree centrality, closeness centrality, betweenness centrality, eigenvector centrality, and follower rank. As a result, the interactions created in the hashtag network #WadasMelawan are dominated by @oposisicerdas and @geloraco accounts.
Co-Authors Nursiyono, Joko Ade