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All Journal Jupiter Carmin: Journal of Community Service
Hafsah Mukaromah
Universitas Aisyah Pringsewu
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Library & Information Science Social Sciences

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Poster Edukatif sebagai Media dalam Meningkatkan Pemahaman dan Perilaku Cegah Stunting Ratnasari Ratnasari; Hafsah Mukaromah; Sahrul Prayoga
Carmin: Journal of Community Service Vol. 5 No. 2 (2025)
Publisher : Borneo Research and Education Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59329/carmin.v5i2.209

Abstract

The Community Service Program of Aisyah University Pringsewu was held in Pekon Sinar Baru, Sukoharjo District, Pringsewu Regency, from 2 to 27 December 2024, as part of the implementation of the Tri Dharma of Higher Education. This program aims to provide real contributions in overcoming community problems, one of which is stunting in toddlers. Stunting prevention is carried out through counseling and socialization activities, utilizing educational poster media and PowerPoint presentations, held at the Sinar Baru Village Hall. This activity involved residents from four hamlets and health workers, with a total of 50 participants. This activity was conducted in four stages: preparation, counseling, poster installation, and evaluation. The preparation stage involves preparing educational materials and identifying community nutritional problems. Counseling focused on education about the importance of balanced nutrition, exclusive breastfeeding, complementary feeding, and supplements for pregnant women and toddlers. Educational posters were installed to visually and sustainably strengthen community understanding. Evaluation was conducted by distributing pre-test and post-test questionnaires, as well as participant satisfaction surveys. The results of the activity showed an increase in community knowledge about stunting and family nutrition, with a positive response from participants, including health cadres. This activity succeeded in encouraging collective awareness of the importance of early stunting prevention and strengthening synergy between students, the village government, and the community in efforts to improve the quality of children's health in Pekon Sinar Baru.
Komparasi Penerapan Adaboost Pada K-NN Dan Decision Tree Untuk Prediksi Penyakit Hati Hafsah Mukaromah; Ratnasari Ratnasari
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 17 No 2 (2025): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

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Abstract

The liver is a vital human organ that plays a crucial role in detoxification, cholesterol regulation, and various metabolic activities within the body. Impairment of liver function can lead to several diseases such as hepatitis, liver cancer, cirrhosis, and other liver-related conditions. In Indonesia, approximately 0.6% of the population is identified as having hepatitis, despite the implementation of the HB 0–4 immunization program by the Ministry of Health. Liver disease is a common public health issue, with WHO data reporting an annual death toll of 1.2 million people due to liver-related illnesses in Southeast Asia and Africa. The importance of early detection of liver disease symptoms highlights the need for a predictive system capable of accurately identifying individuals at risk. This study employs a machine learning approach using K-Nearest Neighbor (K-NN) and Decision Tree classification algorithms, enhanced by the application of the Adaboost ensemble learning technique to optimize their performance. Evaluation results show that Adaboost improves the accuracy of the K-NN algorithm to 95.77% and the accuracy of the Decision Tree to 100%. Although the improvement in K-NN is quite significant, Adaboost does not have a substantial impact on the accuracy of the Decision Tree. This research indicates that the Adaboost method is effective in enhancing the classification performance for liver disease, particularly when applied to the K-NN algorithm.
Co-Authors Ratnasari Ratnasari Sahrul Prayoga