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All Journal G-Tech : Jurnal Teknologi Terapan Andalasian International Journal of Applied Science, Engineering, and Technology Journal Of Therapeutic
Puspitasari, Rahma Ajeng
Unknown Affiliation
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Mechanical Engineering Neuroscience Nursing Public Health

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TEKNOLOGI CRISPR/CAS9 SEBAGAI MASA DEPAN TERAPI Puspitasari, Rahma Ajeng
Journal Medical Kuningan Vol 1 No 2 (2025): Journal of Therapeutic
Publisher : Politeknik Kesehatan Kuningan Medical Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70476/jmk.v1i204

Abstract

Teknologi CRISPR/Cas9, yang awalnya ditemukan sebagai sistem pertahanan bakteri terhadap virus, telah berkembang pesat sebagai alat untuk editing genom pada organisme eukariotik, termasuk manusia. CRISPR/Cas9 memungkinkan pemotongan dan modifikasi DNA secara tepat pada lokasi yang ditargetkan, menjadikannya alat yang sangat menjanjikan untuk terapi penyakit genetik, seperti hemofilia, kanker, dan berbagai kelainan genetik lainnya. Artikel ini mengulas mekanisme kerja CRISPR/Cas9, dari pengenalan dan pemotongan DNA target oleh enzim Cas9 yang dipandu oleh RNA guide (gRNA), hingga proses perbaikan DNA yang dapat diarahkan untuk terapi. Salah satu tantangan utama dalam penerapannya adalah metode penghantaran (delivery) CRISPR/Cas9 yang aman dan efisien. Penggunaan vektor virus seperti adenovirus, lentivirus, dan adeno-associated virus (AAV) telah banyak diteliti, meskipun terdapat potensi masalah imunogenik. Alternatif lain menggunakan teknologi nanoteknologi berbasis polimer, lipid, dan nanopartikel juga menunjukkan potensi besar dalam meningkatkan efisiensi pengiriman CRISPR/Cas9. Meskipun CRISPR/Cas9 memiliki potensi besar, penggunaannya, terutama untuk editing genom manusia, menghadapi tantangan etik yang perlu dipertimbangkan dengan hati-hati. Teknologi ini diharapkan menjadi terapi masa depan yang efektif untuk berbagai penyakit genetik dan kanker, namun penggunaan untuk perubahan garis keturunan manusia harus diatur secara ketat.
A Histopathology Grading of Breast Cancer Using Visual Geometry Group Method Hyperastuty, A. Santika; Setiawan, Fachruddin Ari; Pradana, Dio Alif; Puspitasari, Rahma Ajeng; Inayah, Lailatul; Winarti, Eko
Andalasian International Journal of Applied Science, Engineering and Technology Vol. 5 No. 2 (2025): July 2025
Publisher : LPPM Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/aijaset.v5i02.255

Abstract

Breast cancer continues to rank among the world's leading causes of death for women. Developing successful treatment plans requires a timely and accurate diagnosis. Although histopathological image analysis is still the gold standard for evaluating malignancy, it is prone to inconsistencies and human error. The objective of this research is to use the Visual Geometry Group's (VGG16) deep learning technique to automate the evaluation of breast cancer histology. A collection of breast cancer histopathology images spanning 85 epochs was used to train the VGG16 model, which is well-known for its excellent performance in image classification tasks. For training and testing, the model uses batch sizes of 33 and 64, respectively, and a Stochastic Gradient Descent (SGD) optimizer with a learning rate of 0.01. With an F1 score of 0.98, 89.3% training accuracy, and 98% validation accuracy, the experimental findings show excellent performance. These results indicate that VGG16 is highly effective in distinguishing between different tissue grades of breast cancer. Despite its high performance, challenges remain regarding computational efficiency and interpretability for clinical use. Future research should focus on exploring lightweight architectures, improving model explanations, and validating more diverse and larger datasets to enhance real-world applicability in digital pathology.
Design and Evaluation of Automated Fluid-Transfer Suction Pump Based on Arduino for Thoracic Trauma Applications Afandi, Fuad; Mukromin , Radian Indra; Mukhammad, Yanuar; Puspitasari, Rahma Ajeng
G-Tech: Jurnal Teknologi Terapan Vol 10 No 1 (2026): G-Tech, Vol. 10 No. 1 January 2026
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v10i1.8965

Abstract

Thoracic trauma frequently leads to the accumulation of air or fluid within the pleural cavity, compromising pulmonary expansion and requiring immediate evacuation through suction systems. Conventional suction pumps rely heavily on continuous manual monitoring to prevent container overflow, creating potential risks of backflow, contamination, or device malfunction. This study aims to design and evaluate an automated dual-container suction pump prototype capable of maintaining stable suction pressure while minimizing manual supervision during fluid evacuation. The proposed system employs an Arduino Uno microcontroller and integrates an MPX5700DP pressure sensor for suction monitoring, an E18-D80NK infrared sensor for full-container detection, a 12 V solenoid valve for automated flow diversion, a 25DA Solid State Relay (SSR) for safe power switching, and a buzzer alarm for emergency shutdown. Experimental results indicate that all electrical outputs remain within acceptable tolerance ranges (1.2–4.7%), and suction pressure is consistently maintained at 70 cmHg before and after system modification. The accuracy of infrared sensor achieved a detection accuracy of only 30%, highlighting its limited suitability for reliable medical fluid-level monitoring and underscoring the need for alternative sensing technologies in future implementations. Despite this limitation, the prototype demonstrates the feasibility of automated fluid-transfer control and provides a practical foundation for the development of safer and more reliable suction systems for thoracic trauma applications.
Co-Authors Afandi, Fuad Hyperastuty, A. Santika Inayah, Lailatul Mukromin , Radian Indra Pradana, Dio Alif Setiawan, Fachruddin Ari winarti, eko Yanuar Mukhammad