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All Journal JUITA : Jurnal Informatika Community Development Journal: Jurnal Pengabdian Masyarakat
Salmon Charles Siahaan
Universitas Ciputra Surabaya
Humanities Computer Science & IT Economics, Econometrics & Finance Education Health Professions Public Health

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What do Indonesians talk when they talk about COVID-19 Vaccine: A Topic Modeling Approach with LDA Theresia Ratih Dewi Saputri; Caecilia Citra Lestari; Salmon Charles Siahaan
JUITA : Jurnal Informatika JUITA Vol. 10 No. 2, November 2022
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (955.666 KB) | DOI: 10.30595/juita.v10i2.13500

Abstract

To end the COVID-19 pandemics, the government attempted to accelerate the vaccination through various programs and collaboration. Unfortunately, the number is still relatively small compared to the number of populations in Indonesia. There are some reasons attributed to this challenge, one of them being the reluctance of citizens to accept the COVID-19 vaccine due to various factors. Knowing this factor to increase public compliance, the vaccination program can be speed-up. Unfortunately, traditionally acquiring the knowledge related to COVID-19 vaccine rejection can be challenging.  One of the ways to capture the knowledge is by conducting a survey or interview related to COVID-19 vaccine acceptance. This method can be inefficient in terms of cost and resources. To address those problem, we propose a novel method for analyzing the topics related to the COVID-19 Indonesians’ opinions on Twitter by implementing topic modeling algorithm called Latent Dirichlet Allocation. We gathered more than 22000 tweets related to the COVID-19 vaccine. By applying the algorithm to the collected dataset, we can capture the what is general opinion and topic when people discuss about COVID-19 vaccine. The result was validated using the labeled dataset that have been gathered in the previous research. Once we have the important term, the strategy based on can be determined by the medical professional who are responsible to administer the COVID-19 vaccine. 
DETEKSI DINI IBU HAMIL UNDERWEIGHT DI PUSKESMAS PAMOLOKAN SUMENEP DENGAN USG UNTUK MENCEGAH PERTUMBUHAN JANIN TERHAMBAT Salmon Charles Siahaan; Florence Pribadi; Natalia Yuwono; Lidya Handayani; Desak Nyoman Surya Suameitria
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 5 No. 3 (2024): Volume 5 No. 3 Tahun 2024
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v5i3.27112

Abstract

Data populasi ibu hamil di Indonesia menunjukkan tingginya persentase ibu hamil dengan Kekurangan Energi Kronis (KEK), yang merupakan faktor risiko potensial untuk kondisi IUGR. Hasil penelitian sebelumnya menunjukkan hubungan antara Indeks Massa Tubuh (BMI) pra kehamilan dan pertambahan berat badan gestasional dengan risiko IUGR, menyoroti pentingnya asupan gizi yang adekuat selama kehamilan. Pengabdian masyarakat ini bertujuan untuk mengkaji kondisi ibu hamil dengan berat badan kurang (underweight) di Puskesmas Pamolokan Sumenep dalam upaya mencegah terjadinya Intrauterine Growth Restriction (IUGR), sebuah kondisi yang berpotensi membahayakan kesehatan janin dan ibu. Melalui sosialisasi dan pemeriksaan Ultrasonografi (USG), kami berupaya untuk mendeteksi dini risiko IUGR yang mungkin timbul pada ibu hamil dengan berat badan kurang. Dengan metode kolaboratif antara Dinas Kesehatan Sumenep, Puskesmas Pamolokan, dan peneliti, diharapkan penelitian ini dapat memberikan pemahaman yang lebih baik tentang hubungan antara kondisi underweight pada ibu hamil dan risiko IUGR. Temuan dari penelitian ini diharapkan dapat menjadi landasan bagi upaya preventif yang lebih efektif dalam mengurangi kasus IUGR pada ibu hamil dengan berat badan kurang.
Co-Authors Desak Nyoman Surya Suameitria Florence Pribadi Lestari, Caecilia Citra Lidya Handayani Natalia Yuwono Theresia Ratih Dewi Saputri