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All Journal ELKHA : Jurnal Teknik Elektro Jurnal Keperawatan Muhammadiyah
Eka Budiarto, Eka
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Health Professions Industrial & Manufacturing Engineering Nursing

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Analisis Manajemen Stres Berbasis Aplikasi Smartphone untuk Meningkatkan Koping Adaptif dalam Asuhan Keperawatan Jiwa: Literature Review Budiarto, Eka; Afriani, Tuti
Jurnal Keperawatan Muhammadiyah Vol 2, No 1 (2017): JURNAL KEPERAWATAN MUHAMMADIYAH
Publisher : UNIVERSITAS MUHAMMADIYAH SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (205.052 KB) | DOI: 10.30651/jkm.v2i1.960

Abstract

Stres adalah respon seseorang terhadap stresor, baik secara fisik maupun psikologis dan bersifat subyektif. Manajemen stres merupakan sebuah cara untuk mengatasi stres dengan menggunakan strategi koping adaptif yang menurunkan tingkat depresi dan mencegah terjadinya masalah jiwa berat. Artikel ini bertujuan untuk menelaah potensi penggunaan smartphone untuk manajemen stres dalam meningkatkan koping adaptif  di Indonesia. Literature review dilakukan dengan menganalisa 15 artikel dari PubMed, EBSCO, ProQuest, Scopus, dan Google Scholar sejak tahun 2006-2017. Studi literatur ini mendapatkan hasil bahwa penerapan manajemen stres berbasis aplikasi smartphone perlu diterapkan karena dapat mencegah terjadinya penyakit jiwa yang semakin berat, menurunkan tingkat stres, mudah dilakukan dengan fitur yang sederhana, lebih efektif jika dibandingkan dengan intervensi tatap muka, dan dapat meningkatkan jangka waktu efek dari terapi. Mobile Web App merupakan salah satu aplikasi manajeman stres yang dapat diakses melalui smartphone dan dapat meningkatkan koping adaptif.
Upaya Peningkatan Penerimaan dan Kemampuan Ibu dalam Menstimulasi Bayi Melalui Terapi Kelompok Terapeutik Bayi Peka Budaya: Studi Kasus Budiarto, Eka; Kusuma, Nur Intan
Jurnal Keperawatan Muhammadiyah 2020: JKM EDISI KHUSUS SEPTEMBER 2020
Publisher : UNIVERSITAS MUHAMMADIYAH SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/jkm.v0i0.5888

Abstract

Mental nursing services are not limited to the patients with mental disorders and psychosocial problems, but the healthy peoples are included the patients. The method of service to healthy patients by giving the stimulation according to the range of age development. One of them is the age of the baby. Stimulation in infants aims to optimize the achievement of the task of developing trust. Stimulation in infants can be given in the form of group therapy, namely infants therapy of  therapeutic group. Therapy of  therapeutic group for infants is proven to increase parental knowledge and psychosocial development of infants. However, the care that given to a baby boy (13 month old ) shows that the family still adhere to a cultures that do not support the implementation of therapy of  therapeutic group. Busyness helps husbands work, individualistic culture and the perception of socialization in groups are just a waste of time and not useful, and the culture of utilization of health services is less a challenge for nurses in providing infants therapy of  therapeutic group. Based on these conditions, infants therapy of  therapeutic group is given by cultural approach. Infants therapy of  therapeutic group is carried out by integrating cultural values with cultural identification, negotiation, and strengthening of good culture. The results obtained were infants therapy of  therapeutic group with culturally considerate to infant increased maternal acceptance of therapeutic group therapy and mothers felt increasing in cognitive and psychomotor abilities in stimulating infants growth and development in order to achieve the task of developing infants trust.
Comparison and Analysis of Neural Solver Methods for Differential Equations in Physical Systems Sim, Fabio M; Budiarto, Eka; Rusyadi, Rusman
ELKHA : Jurnal Teknik Elektro Vol. 13 No. 2 October 2021
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v13i2.49097

Abstract

Differential equations are ubiquitous in many fields of study, yet not all equations, whether ordinary or partial, can be solved analytically. Traditional numerical methods such as time-stepping schemes have been devised to approximate these solutions. With the advent of modern deep learning, neural networks have become a viable alternative to traditional numerical methods. By reformulating the problem as an optimisation task, neural networks can be trained in a semi-supervised learning fashion to approximate nonlinear solutions. In this paper, neural solvers are implemented in TensorFlow for a variety of differential equations, namely: linear and nonlinear ordinary differential equations of the first and second order; Poisson’s equation, the heat equation, and the inviscid Burgers’ equation. Different methods, such as the naive and ansatz formulations, are contrasted, and their overall performance is analysed. Experimental data is also used to validate the neural solutions on test cases, specifically: the spring-mass system and Gauss’s law for electric fields. The errors of the neural solvers against exact solutions are investigated and found to surpass traditional schemes in certain cases. Although neural solvers will not replace the computational speed offered by traditional schemes in the near future, they remain a feasible, easy-to-implement substitute when all else fails.
Co-Authors Budi Anna Keliat Ice Yulia Wardani Kusuma, Nur Intan Mokhamad Arifin Pujiati Setyaningsih, Pujiati Rusman Rusyadi Sim, Fabio M Tuti Afriani