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Edukasi Mitigasi Bencana Berbasis Masyarakat di Wilayah Rawan Risiko : Pengabdian Thika Marliana; Ivonne Fitri Mariay; Novaldi Laudi Angrianto; Christian Soleman Imburi; Liz Yanti Andriyani
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 4 (2026): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 4 April - Juni
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i4.5716

Abstract

Pengabdian ini bertujuan untuk mengetahui efektivitas edukasi mitigasi bencana berbasis masyarakat di wilayah Papua. Pelaksanaan kegiatan dilakukan melalui beberapa tahapan, meliputi tahap persiapan dan analisis kebutuhan lapangan, koordinasi dan kolaborasi dengan pemangku kepentingan lokal, penyusunan kurikulum dan modul edukasi, sosialisasi, pelaksanaan pelatihan partisipatif dan simulasi lapangan, pembentukan kelompok siaga bencana berbasis komunitas, serta monitoring dan evaluasi. Hasil kegiatan menunjukkan bahwa program edukasi mitigasi bencana berbasis masyarakat di wilayah Papua menunjukkan dampak yang signifikan terhadap penguatan kapasitas komunitas dalam memahami dan mengelola risiko bencana. Kegiatan ini tidak hanya meningkatkan pengetahuan warga mengenai ancaman dan kerentanan, tetapi juga mendorong perubahan cara pandang terhadap bencana sebagai risiko yang dapat dikelola melalui upaya terencana dan kolaboratif. Selain peningkatan pemahaman konseptual, kegiatan ini juga mendorong terbentuknya sikap proaktif, penguatan kelembagaan melalui kelompok siaga bencana, serta peningkatan keterampilan praktis melalui simulasi lapangan. Integrasi antara kearifan lokal dan pendekatan ilmiah memperkaya strategi mitigasi yang kontekstual dan berkelanjutan. Di sisi lain, terbangunnya jejaring kolaborasi dengan pemerintah daerah serta menguatnya solidaritas sosial menjadi fondasi penting bagi terciptanya budaya kesiapsiagaan yang berakar pada kesadaran kolektif. Secara keseluruhan, program ini berkontribusi dalam membentuk komunitas yang lebih tangguh, partisipatif, dan siap menghadapi potensi bencana secara mandiri dan terorganisasi.
A REVIEW OF NANOPARTICLE-BASED STRATEGIES FOR OVERCOMING THE BLOOD-BRAIN BARRIER IN NEURODEGENERATIVE DISEASE THERAPY Thika Marliana; Bina Magar; Samuel Denis
Journal of Biomedical and Techno Nanomaterials Vol. 2 No. 6 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jbtn.v2i6.2975

Abstract

Neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease, and related disorders, remain difficult to treat effectively due to the restrictive nature of the blood–brain barrier, which severely limits drug delivery to the central nervous system. Many therapeutic agents with proven molecular efficacy fail to achieve clinical success because they cannot reach target sites in the brain at sufficient concentrations. This review aims to critically analyze nanoparticle-based strategies developed to overcome the blood–brain barrier and to evaluate their potential in neurodegenerative disease therapy. A narrative-integrative review method was employed, drawing on peer-reviewed articles indexed in major scientific databases, including studies on lipid-based, polymeric, inorganic, and biomimetic nanoparticles. The reviewed evidence indicates that nanoparticle systems significantly enhance brain delivery through mechanisms such as receptor-mediated transcytosis, adsorption-mediated transport, and biomimicry, leading to improved pharmacokinetics and therapeutic efficacy in preclinical models. Lipid-based and biomimetic nanoparticles demonstrate the greatest translational promise due to favorable safety and biological compatibility, while polymeric systems offer high design flexibility. Despite these advances, challenges related to long-term safety, reproducibility, and clinical translation persist. In conclusion, nanoparticle-based delivery represents a pivotal strategy for overcoming the blood–brain barrier, and continued interdisciplinary research is essential to translate these technologies into effective therapies for neurodegenerative diseases. Keywords: blood–brain barrier; nanoparticles; neurodegenerative diseases; nanomedicine; targeted drug delivery
The Effect of Lean Six Sigma Implementation, Information Technology Utilization, and Bed Capacity on Length of Inpatient Stay at Karya Medika Hospital, Bantar Gebang, Bekasi, in 2025 Astri Gunardi; Atik Kridawati; Herawati Herawati; Thika Marliana
Journal of Ageing And Family Vol 4, No 2 (2024): Journal of Ageing And Family
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM Universitas Respati Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52643/joaf.v4i2.7229

Abstract

The Length of stay is a crucial indicator in hospital service systems. This study aims to analyze the influence of Lean Six Sigma implementation, the use of information technology, and bed capacity on the length of stay at RS Karya Medika Bantar Gebang. The research method used is a quantitative approach with a descriptive analytical design. Data were collected through questionnaires and analyzed using univariate, bivariate, and multivariate tests. The univariate analysis results show that the majority of respondents are aged 20-35 years (59.00%), female (64.10%), and work as nurses (56.40%). Bivariate analysis using Pearson correlation test shows that Lean Six Sigma implementation has a strong relationship with length of stay (r = 0.855, p = 0.000), the use of information technology has a very strong relationship (r = 0.906, p = 0.000), and bed capacity also has a strong relationship (r = 0.838, p = 0.000). Multivariate analysis results using multiple linear regression indicate that Lean Six Sigma implementation (β = 1.583, p = 0.000) and the use of information technology (β = 0.954, p = 0.043) significantly affect the length of stay, while bed capacity (β = 0.505, p = 0.243) does not have a significant effect. The regression model used has an R value of 0.944 and an R Square value of 0.892, indicating that 89.2% of variations in length of stay can be explained by the three independent variables. The conclusion of this study is that Lean Six Sigma implementation and the use of information technology significantly contribute to reducing the length of stay, while bed capacity does not have a direct impact. Therefore, hospitals are advised to further optimize the implementation of Lean Six Sigma and information technology to improve service efficiency.
The Influence Of Work Environment, Compensation, Workload, And Career Development On The Performance Of Nurses At Bethesda Hospital Wonosari, Special Region Of Yogyakarta In 2025 Widyaningsih Widyaningsih; Sumijatun Sumijatun; Nurcahyo Andarusito; Thika Marliana
Journal of Ageing And Family Vol 4, No 1 (2024): Journal of Ageing And Family
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM Universitas Respati Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52643/joaf.v4i1.7227

Abstract

The presence of nurses as human resources is a valuable asset for the sustainability of the hospital, which needs attention so they can work optimally. An initial survey at RS Bethesda Wonosari DIY found that very few nurses performed at a level categorized as competent according to the hospital's expectations. This research was conducted in December 2024, aiming to analyze the factors influencing nurse performance at RS Bethesda Wonosari DIY using a quantitative design and a cross-sectional approach. The respondents in this study are all 50 nurses. Primary data collection was conducted through the distribution of questionnaires that had been tested on 30 people at RS Panti Waluyo Solo. The univariate results show that the majority of respondents are female, have an Associate's degree in Nursing, are of productive age, and have less than 5 years of work experience. The lowest achievements obtained from the variables studied: work environment (73.5%), provision of new information (73%), performance bonuses for employees (46%), work for patient safety (79%), fully responsible nursing care (52.5%), completion of work according to targets (74.5%). Completion of work on time (76.5%) and communication with superiors (67.5%). The bivariate results show that the variables positively affecting nurse performance are workload (p: 0.002), work environment (p: 0.002), and career development (p: 0.005), each with a very weak influence, while the variable that does not have an effect is compensation (p: 0.173). The multivariate results indicate that workload, work environment, compensation, and career development collectively have a significant impact on nurse performance (p: 0.001), with the most influential factor being workload (β) 0.623 (p: 0.017). The recommendation from this study is that the workload of nurses needs to be balanced, fair, and evenly distributed to avoid fatigue, improve workspace layout, provide bonuses for outstanding nurses, increase responsibility in nursing care, and for management to allocate time for discussions with nurses regarding career development programs.
AI and Robotics in Elderly Care: Sustainable Solutions for Aging Populations Thika Marliana; Dilara Sert Kasim; Samsuni Samsuni; Ton Kiat
Journal of World Future Medicine, Health and Nursing Vol. 3 No. 5 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/health.v3i5.2565

Abstract

The global rise in aging populations poses urgent challenges to healthcare systems, social welfare, and labor sustainability. Traditional caregiving models are increasingly strained by workforce shortages and escalating medical costs. Artificial Intelligence (AI) and robotics have emerged as transformative technologies offering innovative and sustainable approaches to elderly care. This study aims to examine how AI-driven systems and assistive robots enhance healthcare delivery, autonomy, and quality of life among older adults. Using a mixed-method design, the research combines a systematic review of 120 peer-reviewed studies (2012–2024) with case analyses of robotic implementations in Japan, Sweden, and Singapore. Findings reveal that AI-enabled monitoring, predictive diagnostics, and social robots significantly improve health outcomes, emotional well-being, and caregiving efficiency. However, ethical concerns regarding privacy, human empathy, and digital inequality remain critical barriers to widespread adoption. The study concludes that sustainable elderly care requires integrating technological innovation with human-centered design and policy frameworks that ensure inclusivity, accountability, and data ethics.