Analisis Persepsi Publik Mengenai Resesi Ekonomi Global 2023 Sektor Bisnis di Media Sosial Twitter Menggunakan Algoritma Naïve Bayes dan Topic Modelling

Muhammad Alif Maghriby, Herry Irawan

Abstract


Penelitian ini bertujuan untuk mengetahui bagaimana kondisi sektor bisnis ketika resesi ekonomi global 2023 dengan mengidentifikasi persepsi positif dan negatif serta topik yang sering dibicarakan dari pengguna Twitter mengenai sektor bisnis ketika resesi ekonomi global 2023. Metode yang digunakan pada penelitian ini adalah metode kuantitatif dengan analisis sentimen menggunakan model Naïve Bayes dan Topic Modelling. Teknik pengumpulan data dilakukan dengan crawling data yang didapatkan dari media sosial Twitter pada 1 November 2022 hingga 30 November 2022. Data didapatkan sebanyak 7.542 tweets dan kemudian dilakukan pre-processing data yang kemudian menghasilkan 4.458 tweets yang siap dianalisis. Hasil penelitian menunjukkan terdapat 1.466 sentimen positif dan 2.992 sentimen negatif dengan model Naïve Bayes didapatkan nilai sebesar 97.84 persen accuracy, 94.03 persen precision, dan 100 persen recall. Informasi yang didapatkan dari hasil penelitian adalah pelaku UMKM tidak perlu cemas akan terkena dampak resesi ekonomi justru UMKM menjadi solusi dalam melawan resesi ekonomi. Kemudian, tingkat bunga hipotek di Eropa lebih tinggi daripada tingkat suku bunga KPR di Indonesia. Depresiasi mata uang yang terjadi memiliki sisi positif yang mana ketika depresiasi mata uang terjadi para pengusaha dapat meningkatkan ekspor karena barang dan jasanya lebih murah di pasar internasional.



This study aims to find out how the business sector is in the 2023 global economic recession by identifying positive and negative perceptions and topics that are often discussed by Twitter users regarding the business sector during the 2023 global economic recession. The method used in this study is a quantitative method with sentiment analysis using the Naïve Bayes and Topic Modeling models. The data collection technique was carried out by crawling data obtained from social media Twitter from November 1, 2022, to November 30, 2022. Data were obtained from 7,542 tweets and then data pre-processing was carried out, producing 4,458 tweets that were ready to be analyzed. The results showed that there were 1,466 positive sentiments and 2,992 negative sentiments with the Naïve Bayes model obtaining values of 97.84 percent accuracy, 94.03 percent precision, and 100 percent recall. The information obtained from the research results is that MSME actors do not need to worry about being affected by the economic recession MSMEs are the solution to fighting the economic recession. Then, mortgage interest rates in Europe are higher than mortgage interest rates in Indonesia. Currency depreciation occurs has a positive side where when currency depreciation occurs entrepreneurs can increase exports because their goods and services are cheaper on international markets.


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DOI: https://doi.org/10.31294/widyacipta.v7i2.15577

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