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This Author published in this journals
All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING Indonesian Journal of Global Health research
Marwanta, Y Yohakim
Unknown Affiliation
Computer Science & IT Education Health Professions Languange, Linguistic, Communication & Media Nursing Public Health

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Analisis Sentimen Pencitraan Perguruan Tinggi di Yogyakarta Menggunakan Metode Naive Bayes Classifier Marwanta, Y Yohakim; B, Badiyanto
Journal of Applied Informatics and Computing Vol. 7 No. 1 (2023): July 2023
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v7i1.5103

Abstract

This research utilizes data from Twitter to analyze sentiment in Yogyakarta's universities using the Naive Bayes Classifier method. The Naive Bayes Classifier method is one of the text classification methods based on the probability of keywords in comparing training and testing documents. The data used consists of tweets in Indonesian language with keywords from the top 10 universities in Yogyakarta based on webometrics, as well as four other relevant keywords about Yogyakarta that are frequently searched through Google. From the conducted research, there are 1710 data collected from Twitter, which are used for classification and categorized into 3 labels: positive, negative, and neutral. The data is divided into 70% for training and 30% for testing randomly. The result of sentiment analysis classification from the test data shows that 82.1% of the data is categorized as neutral, 14.8% as positive, and 3.1% as negative, with an accuracy value of 73%.
The Impact of Using the Maternal Neonatal Emergency Application (SIGNAL) for Midwives Margaretha, Sumarti Endah Purnamaningsih Maria; Putrianti, Berlina; Wulandari, Amri; Urrahman, Dhiya; Marwanta, Y Yohakim
Indonesian Journal of Global Health Research Vol 7 No 3 (2025): Indonesian Journal of Global Health Research
Publisher : GLOBAL HEALTH SCIENCE GROUP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37287/ijghr.v7i3.6185

Abstract

Maternal mortality rate (MMR) and neonatal mortality rate (NMR) in Indonesia are still a challenge in health services. Technological innovations such as the SIGNAL application (Maternal Neonatal Emergency Information System) were developed to improve early detection of high risk in pregnant women and neonates. Objective to determine the impact of using the SIGNAL application for midwives in improving the speed and accuracy of maternal neonatal emergency services in Bantul Regency. Descriptive quantitative research with a cross-sectional approach was conducted on 50 midwives using SIGNAL at the Bantul Regency Health Center. The sampling technique used purposive sampling with a total of 50 respondents who actively used the SIGNAL application. Data were collected through questionnaires and analyzed descriptively. The results showed that 82% of midwives felt helped in early identification of high risk, 76% stated that referrals were faster, and 70% felt that the application increased confidence in making clinical decisions. The main obstacles were internet network and device limitations. The use of the SIGNAL application has a positive impact on improving the quality of maternal neonatal emergency services by midwives in Bantul Regency, although improvements in supporting infrastructure are still needed.
Co-Authors B, Badiyanto Dhiya Urrahman putrianti, Berlina Sumarti Endah Purnamaningsih Maria Margaretha Wulandari, Amri