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All Journal Abdimas Galuh : Jurnal Pengabdian Kepada Masyarakat International Journal of Mathematics, Statistics, and Computing
Riswandi, Calvin
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Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Law, Crime, Criminology & Criminal Justice Mathematics Nursing

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Pelatihan Visualisasi Data Menggunakan Aplikasi Tableau di BPS Kota Tangerang Selatan Wiyanti, Wiwik; Seleky, Jacob Stevy; Riswandi, Calvin; Jimy, Valensius
Abdimas Galuh Vol 7, No 1 (2025): Maret 2025
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/ag.v7i1.18020

Abstract

Pembangunan sumber daya manusia untuk segera mewujudkan Indonesia maju sesegera mungkin tidak hanya dilakukan dari pemerintah kepada masyarakat saja (upper-bottom), namun bisa dilakukan dari masyarakat kepada pemerintah (bottom-upper) sebagai wujud nyata partisipasi masyarakat kepada negara. Seperti halnya pengabdian kepada masyarakat (PKM) kali ini, adalah dari masyarakat dan untuk masyarakat. Kegiatan PKM ini adalah pelatihan visualisasi data menggunakan Tableau untuk pegawai BPS Kota Tangerang Selatan. Perlu disadari bahwa teknologi semakin maju, dan perkembangan aplikasi untuk visualisasi data sudah tidak hanya dengan excel saja, namun mampu dikerjakan menggunakan Tableau. Tujuan dari pengabdian ini adalah meningkatkan pengetahuan pegawai BPS Kota Tangerang mengenai visualisasi data menggunakan Tableau. Adapun alasan pelatihan ini diadakan adalah aplikasi Tableau belum dikenal oleh pegawai BPS Kota Tangerang. Analisa data yang digunakan adalah menggunakan non-parametrik sign test. Peserta pelatihan sebanyak 20 orang dan yang mengikuti pre-test dan post-test lengkap sebanyak 17 peserta. Hasil analisa data diperoleh kesimpulan bahwa pelatihan visualisasi data dengan menggunakan aplikasi Tableau efektif untuk meningkatkan pengetahuan visualisasi data pegawai BPS Kota Tangerang Selatan.
Sentiment Analysis of Public Comments on the YouTube Video “Trump Unveils Sweeping Global Tariffs in Watershed Moment for World Trade” by BBC News Using the Long Short-Term Memory Method Riswandi, Calvin
International Journal of Mathematics, Statistics, and Computing Vol. 3 No. 3 (2025): International Journal of Mathematics, Statistics, and Computing
Publisher : Communication In Research And Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijmsc.v3i3.210

Abstract

This study aims to analyze public sentiment towards the announcement of global tariffs by the President of the United States, Donald Trump, using the Long Short-Term Memory (LSTM) method. The analysis focused on user comments from one video uploaded by BBC News on its official YouTube channel, titled “Trump Unveils Sweeping Global Tariffs in Watershed Moment for World Trade.”. Sentiment analysis is performed by classifying public comments into positive or negative sentiment categories, through preprocessing stages such as case folding, cleansing, normalization, stop words, stemming and tokenization. The processed data is then used to train and evaluate the LSTM model, which is known to capture temporal relationships and contextual meaning in text data. The results showed that the sentiment was negative, with 64.6% of the comments showing negative sentiment and only 34.4% showing positive sentiment. The performance of this LSTM method gives a performance of 76% Accuracy with 77% precision, 84% recall, and 81% f1-score on negative sentiment and 74% precision, 64% recall, and 69% f1-score on positive sentiment. These findings demonstrate the public's critical view of Donald Trump's global tariff policy and confirm the effectiveness of the LSTM method in extracting sentiment trends from online discussions. This research contributes to the analysis of public opinion in the context of international economic policy.
Co-Authors Jacob Stevy Seleky, Jacob Stevy Jimy, Valensius Wiwik Wiyanti, Wiwik