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PANDEMI COVID-19 BAGI PENERAPAN INOVASI DI INDONESIA: ANALISIS PENAMBANGAN TEKS BERITA DENGAN MODEL TOPIK LATENT DIRICHLET ALLOCATION

JOVITA ANGELA, Nofie Iman Vidya Kemal, M.Sc., Ph.D.

2021 | Tesis | MAGISTER SAINS MANAJEMEN

Pandemi COVID-19 telah membawa penurunan yang amat signifikan dalam perkembangan ekonomi global. Kondisi "black swan", kejadian langka dan tidak terduga, memaksa bisnis untuk bertahan, beradaptasi dengan berbagai kondisi sulit. Berawal dari "point of no return", inovasi dianggap sebagai strategi sekaligus solusi untuk bertahan dari pandemi. Beragam inovasi, terutama terkait inovasi teknologi, yang coba diciptakan di Indonesia selama pandemi, namun sayangnya belum ada reviu manual terkait inovasi teknologi yang sudah diterapkan di Indonesia, padahal pandemi di Indonesia sudah melewati tahun pertama. Dalam penelitian ini, beberapa teori digunakan, selain itu digunakan kombinasi metode analisis wacana, termasuk penambangan teks dan pemodelan topik. Tujuan dari penelitian ini adalah untuk menangkap topik inovasi lalu memetakkannya menjadi beberapa klasifikasi. Sebanyak 440 artikel berita digunakan untuk memenuhi tujuan penelitian ini. Bahasa pemrograman Python dan perangkat Google Colaboratory, digunakan untuk membantu dalam analisis. Hasilnya adalah 20 topik inovasi diidentifikasikan, dan ditawarkan beberapa analisis lainnya. Diharapkan penelitian ini dapat mengisi kesenjangan penelitian sebelumnya terkait model topik dan khususnya inovasi

The COVID-19 pandemic has brought about a very significant decline in global economic development. The black swan condition, a rare and unexpected occurrence, forces businesses to survive, adapting to various difficulties. Starting from point of no return, innovation is considered as a strategy as well as a solution to survive the pandemic. Forced innovations, especially related to technological innovations, were tried to be created in Indonesia during the COVID-19 pandemic. Unfortunately, there has been no manual review regarding forced technological innovations that have been implemented in Indonesia, even though the pandemic in Indonesia has passed its first year. In this study, several theories were used. Moreover, a combination of discourse analysis methods was used, including text mining and LDA topic modeling. The aim is to capture the topic of innovation and then map it into several classifications and analyses. A total of 440 news articles were used to answer the question of this study. Python and Google Collaboratory tools were used to assist in the analysis. As the result, 20 innovation topics were identified and several other analyses were offered. Hopefully, this research can fill the gaps in previous research around topic models and especially forced innovation during the pandemic.

Kata Kunci : inovasi, COVID-19, pandemi, analisis wacana, model LDA, sektoral, Indonesia, berita