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All Journal Indonesian Journal of electronics, electromedical engineering, and medical informatics JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Pengabdian Polinema Kepada Masyarakat Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics
Gunawan Budi Prasetyo
Teknologi Informasi, Politeknik Negeri Malang
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Health Professions Materials Science & Nanotechnology

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Media Pembelajaran Aplikasi Tata Cara Pengurusan Jenazah Berbasis Multimedia Ulla Delfana Rosiani; Mungkin Astiningrum; Faisal Rahutomo; Gunawan Budi Prasetyo; Yushintia Pramitarini
Jurnal Pengabdian Polinema Kepada Masyarakat Vol. 8 No. 2 (2021): Jurnal Pengabdian Polinema Kepada Masyarakat
Publisher : UPT Penelitian dan Pengabdian Kepada Masyarakat Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jppkm.v8i2.95

Abstract

Agama Islam mengajarkan ilmu fiqih dimana dalam kajian tersebut salah satunya membahasan tentang pengurusan jenazah. Namun, masyarakat masih membutuhkan pemahaman tentang bagaimana mengurus jenazah di lingkungan daerah sekitar mereka. Untuk membantu memberikan pemahaman tersebut maka akan dilakukan pelatihan tata cara pengurusan jenazah. Pelatihan ini akan menggunakan metode pembelajaran dengan teknik demonstrasi dimana salah satunya adalah dengan menggunakan aplikasi sebagai media pembelajaran berbasis multimedia. Aplikasi tata cara pengurusan jenazah berbasis multimedia dirancang dan dibuat guna untuk menyajikan informasi dengan tampilan yang menarik. Aplikasi dilengkapi dengan suara dan keterangan serta fitur berdasarkan materi persiapan apa saja yang harus disediakan untuk pengurusan hingga menguburkan jenazah. Dengan dibuatnya aplikasi tata cara pengurusan jenazah diharapkan dapat meningkatkan pemahaman masyarakat tentang tata cara pengurusan jenazah. Kegiatan pengabdian masyarakat ini dapat berjalan lancar, peserta pelatihan mendapatkan pemahaman ilmu tentang tata cara pengurusan jenazah dengan media pembelajaran yang menarik
The Detection of Indonesian Hoax Content about COVID-19 Vaccine using Naive Bayes Multinomial Method Annisa Puspa Kirana; Gunawan Budi Prasetyo; Ela Widya Lestari
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 5 No 1 (2023): February
Publisher : Department of electromedical engineering, Health Polytechnic of Surabaya, Ministry of Health Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v5i1.262

Abstract

One media currently famously used in all worlds is twitter. The ease of dissemination and the exchange of information is accelerating. Every day, millions of tweets exist using various information, such as politics, technology, sports, academics, and others. The information that is widely found is about COVID-19-19 nowadays. The information on Twitter is not entirely accurate or according to facts and needs to be proven true. Therefore, this study aims to try to detect the information contained in Indonesia using methods of Naive Bayes Multinomial by using the Information Gain feature selection. The classification process is carried out by crawling tweets, preprocessing, then using feature selection, namely Information Gain, and classification using the Multinomial Naive Bayes method. Meanwhile, the validation needs in this study use k-fold cross-validation where the existing dataset is divided into training and testing data that will be tested with a confusion matrix. Researchers have carried out the confusion matrix testing process using 720 datasets divided as train data & the test data received an average accuracy value of 81.39%, precision of 80.36%, and recall of 79.73%. The highest accuracy is using k-fold two. The accuracy value reaches 88.8%, the precision value is 79.1%, and the recall value is 86.3%. The lowest accuracy was obtained on the 8th k-fold with an accuracy value of 73.6%, precision 75.4%, and recall 86.9%.
Detection of Indonesian Hoax Content about COVID-19 Vaccine using Naive Bayes Multinomial Method Kirana, Annisa Puspa; Prasetyo, Gunawan Budi; Lestari, Ela Widya
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 5 No. 1 (2023): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v5i1.166

Abstract

One media currently famously used in all worlds is Twitter. The ease of dissemination and the exchange of information is accelerating. Every day, millions of tweets exist using various information, such as politics, technology, sports, academics, and others. The information that is widely found is about COVID-19-19 nowadays. The information on Twitter is not entirely accurate or according to facts and needs to be proven true. Therefore, this study aims to try to detect the information contained in Indonesia using methods of Naive Bayes Multinomial by using the Information Gain feature selection. This research contributes to utilizing data spread on Twitter and social media in detecting hoaxes spread in the community, primarily related to COVID-19 infections. The classification process is carried out by crawling tweets, preprocessing, then using feature selection, namely Information Gain, and classification using the Multinomial Naive Bayes method. Meanwhile, the validation needs in this study use k-fold cross-validation where the existing dataset is divided into training and testing data that will be tested with a confusion matrix. Researchers have carried out the confusion matrix testing process using 720 datasets divided as train data & the test data received an average accuracy value of 81.39%, precision of 80.36%, and recall of 79.73%. The highest accuracy is using k-fold two. The accuracy value reaches 88.8%, the precision value is 79.1%, and the recall value is 86.3%. The lowest accuracy was obtained on the 8th k-fold with an accuracy value of 73.6%, a result precision of 75.4%, and a recall of 86.9%.
ANALISIS SENTIMEN MULTI-PLATFORM UNTUK STRATEGI PEMASARAN DIGITAL PADA DESTINASI WISATA Endah Septa Sintiya; Syahira Azizah Rendra Putri; Gunawan Budi Prasetyo; Candra Bella Vista
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 10 No. 3 (2026): JATI Vol. 10 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v10i3.18253

Abstract

Media sosial dan platform ulasan digital berperan penting dalam membentuk citra destinasi wisata, namun perbedaan karakteristik antar platform sering menghasilkan distribusi sentimen yang tidak merata. Penelitian ini bertujuan untuk menganalisis sentimen publik terhadap destinasi wisata melalui pendekatan multi-platform serta merumuskan strategi pemasaran digital yang efektif. Data dikumpulkan dari Google Maps, TikTok, dan Instagram menggunakan teknik scraping. Pelabelan sentimen dilakukan dengan pendekatan hybrid yang mengombinasikan metode lexicon-based dan Support Vector Machine (SVM). Proses klasifikasi menggunakan algoritma Random Forest dengan fitur TF-IDF, serta evaluasi model dilakukan menggunakan 10-Fold Cross Validation. Hasil penelitian menunjukkan bahwa model Random Forest mencapai akurasi sebesar 87,60%, precision 87,68%, recall 87,93%, dan F1-score 87,55%. Analisis distribusi sentimen mengungkap perbedaan karakteristik antar platform, di mana Google Maps didominasi sentimen negatif (47,4%), Instagram cenderung netral (46,1%), dan TikTok menunjukkan dominasi sentimen netral (53,5%). Selain itu, hasil analisis divisualisasikan menggunakan Priority Action Matrix yang mengidentifikasi strategi Quick Wins seperti peningkatan respons pada Google Maps dan kampanye user-generated content sebagai prioritas utama karena berdampak tinggi dengan upaya rendah. Penelitian ini memberikan kontribusi dalam pengembangan analisis sentimen multi-platform serta perumusan strategi pemasaran digital berbasis data pada destinasi wisata.
Co-Authors Annisa Puspa Kirana Candra Bella Vista Ela Widya Lestari Endah Septa Sintiya Faisal Rahutomo Lestari, Ela Widya Mungki Astiningrum Syahira Azizah Rendra Putri Ulla Delfana Rosiani Yushintia Pramitarini