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Implementasi Strategi Self-care dan Manajemen Stres untuk Meningkatkan Kesehatan Mental Ibu dengan Peran Ganda Amrulloh, Wahyu Edy; Abdillah, Fauzie Nor; Agustin, Dwi Bela; Nisa, Luthfiana Khoirotun; Haidar, Nova Briyan
Muria Jurnal Layanan Masyarakat Vol 7, No 2 (2025): September 2025
Publisher : Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/mjlm.v7i2.15973

Abstract

Along with societal developments, a mother’s role is no longer limited to domestic responsibilities. Many mothers now perform dual roles, such as working, participating in organizations, and engaging in social activities within their communities. These multiple demands can lead to physical fatigue, lack of rest, and psychological pressure that affect mental health. This community service program aims to provide understanding and support for mental health among mothers with dual roles through the implementation of self-care strategies and stress management. The program was carried out using a qualitative method with a participatory approach, including educational sessions, meditation practices, psychological therapy, and counseling. The results showed an increased awareness among participants of the importance of maintaining mental health, as well as the formation of sustainable peer-support groups. This program serves as an effective community-based intervention model for promoting and maintaining the mental well-being of mothers with dual roles. Seiring perkembangan zaman, peran seorang ibu tidak lagi terbatas pada tugas domestik di rumah tangga. Banyak ibu yang menjalani peran ganda, seperti bekerja, aktif dalam organisasi, serta terlibat dalam kegiatan sosial kemasyarakatan. Beragam tuntutan tersebut dapat menimbulkan kelelahan fisik, kurangnya waktu istirahat, serta tekanan psikologis yang berdampak pada kesehatan mental. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk memberikan pemahaman dan dukungan terkait kesehatan mental bagi ibu dengan peran ganda melalui penerapan strategi self-care dan manajemen stres. Pelaksanaan kegiatan menggunakan metode kualitatif dengan pendekatan partisipatif melalui penyampaian materi edukatif, praktik meditasi dan terapi psikologis, serta sesi konseling. Hasil kegiatan menunjukkan adanya peningkatan kesadaran peserta terhadap pentingnya menjaga kesehatan mental serta terbentuknya kelompok dukungan sebaya yang berkelanjutan. Program ini dapat menjadi model intervensi berbasis komunitas yang efektif dalam menjaga dan meningkatkan kesehatan mental ibu dengan peran ganda.
KNN-Based Handwritten Digit Classification with Accuracy Analysis and Visualization Maulana, Muhammad Rizky; Nugroho, Adiv Prasetyo; Adinata, Ferdyan Candra; Haidar, Nova Briyan; Setiawan, Arif
Jurnal Ilmiah Sistem Informasi Vol. 4 No. 2 (2025): Mei : Jurnal Ilmiah Sistem Informasi
Publisher : LPPM Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/776j7727

Abstract

The rapid advancement of information technology has had a significant impact in various fields, particularly in pattern recognition and image processing. One of the ongoing challenges is accurately recognizing handwritten digits, which plays a crucial role in document digitization, automated form reading, and other intelligent systems. This study aims to implement and evaluate the K-Nearest Neighbors (KNN) algorithm, a simple yet effective classification technique, in recognizing handwritten digit images. The data used comes from the public dataset load_digits from Scikit-learn, which contains 1,797 grayscale images of handwritten digits sized 8x8 pixels. Each image is represented as a 64-dimensional feature vector. The dataset is split into training and testing data with an 80:20 ratio, and the model is trained using KNN with k=3. The experimental results show a classification accuracy of 96.94%, with minimal prediction errors that typically occur in digits with similar visual shapes, such as 5 and 9. This study demonstrates that KNN, despite its simplicity, can provide high accuracy in handwritten digit recognition when supported by proper preprocessing and parameter selection. The implications of this research highlight the potential for developing intelligent applications in education, data entry automation, and identity verification.