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All Journal MEDISAINS Child Education Journal JITSI : Jurnal Ilmiah Teknologi Sistem Informasi
Ariyanto, Fajar
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Computer Science & IT Education Medicine & Pharmacology Nursing Public Health

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The Effectiveness of Power Point-Assisted Picture Books on Receptive Language Development in Early Childhood Ariyanto, Fajar; Tanto, Octavian Dwi
Jurnal Pendidikan Anak Vol 3 No 2 (2021): Child Education Journal: August
Publisher : Universitas Nahdlatul Ulama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33086/cej.v3i2.2103

Abstract

This study aims to determine the interests of children from the use of picture storybooks assisted by the Microsoft PowerPoint application in the development of receptive language in early childhood with a research focus on the ability to listen to simple stories. The type of research used is descriptive with a quantitative approach. The data collection technique used in this study was a questionnaire with a Likert scale of 4, where the answer choices were on each question item. The number of questionnaire items used in this study amounted to 6 questions. The results of this study indicate that there are various responses about the impact of using picture storybooks. First, about the difficulty of applying online storybook media too early childhood, the results are 71.4% relatively easy to use, second, children's interest in listening to stories using the PowerPoint application results in 54% of children being very interested, the three PowerPoint applications being an alternative to PAUD learning today. Getting 38.1% results is quite alternative, the four stimulations of early childhood development can be given through impressions on the PowerPoint screen getting 60.3% results can be stimulated, the five children feel unfamiliar with the technology used to get 66.7% results do not feel foreign Regarding the media used, the six obstacles in learning to use PowerPoint media got results 66.7% answered that they did not experience problems in the implementation of storytelling using the powerpoint application.
Psychosocial therapy model to reduce anxiety levels in hemodialysis patients Ariyanto, Fajar; Pratiwi, Arum; Hudiyawati, Dian
MEDISAINS Vol 22, No 3 (2024)
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/medisains.v22i3.23788

Abstract

Background: Chronic kidney disease (CKD) is a global health issue that significantly impacts the quality of life of patients undergoing hemodialysis. Anxiety is one of the common psychological challenges faced by these patients. While various studies have addressed psychological and social interventions, most have focused on only one aspect, such as family support or psychological therapy, without considering the biological, social, and spiritual needs simultaneously. No research has integrated all these dimensions into a holistic approach.Purpose: This study aims to develop and evaluate a holistic nursing management model that combines all of these aspects to reduce anxiety levels for hemodialysis patients.Methods: This study used a mixed-method approach with an action research design. It was conducted at the Klaten Islamic Hospital. The population in the study was patients undergoing hemodialysis; as many as 15 patients participated in this study. The holistic nursing module was tested in five sessions, each lasting 15-30 minutes. Anxiety levels were measured using the Hamilton Rating Scale for Anxiety (HRS-A) before and after the intervention.Results: The study's results showed that the average level of anxiety in patients before the intervention was 35.13±3.22; after the intervention, it decreased to 24.87±1.68 (p<0.001).Conclusion: The application of the holistic nursing management model effectively reduced anxiety levels in hemodialysis patients.
Komparasi Tingkat Akurasi Sentimen Algoritma K-Nearest Neighbor Dan Naïve Bayes Pemilihan Gubernur Jawa Tengah 2024 di Sosial Media X Ariyanto, Fajar; Saefurrohman
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 6 No 2 (2025)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.6.2.332

Abstract

This study highlights the importance of selecting appropriate algorithms for text data analysis and provides recommendations for future exploration of other machine learning and deep learning models to improve the accuracy of sentiment analysis. This research compares the accuracy level of the K-Nearest Neighbor (KNN) and Naïve Bayes algorithms in sentiment analysis in the 2024 Central Java gubernatorial election using data from the social media platform X (formerly Twitter). The data consists of 1,337 posts classified as positive or negative sentiment. Data crawling was done using RapidMiner, and analysis was done via Python in Google Colab. The research results show that the KNN algorithm achieves the highest accuracy of 81%, while Naïve Bayes has a maximum accuracy of 79%. The KNN algorithm is superior in handling text data because of the dependent calculations between attributes, while Naïve Bayes which uses independent calculations has slightly lower performance. This research provides insight into the reaction of public sentiment towards the candidate for governor of Central Java, where the Andhika-Hendi pair received more positive sentiment than Lutfi-Yasin
Co-Authors Arum Pratiwi Dian Hudiyawati Octavian Dwi Tanto Saefurrohman