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Novycha Auliafendri
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Dentistry Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Veterinary

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Uji Karakteristik Sediaan Salep Ekstrak Etanol Daun Sambung Nyawa (Gynura Procumbens (Lour.) Merr.) Novycha Auliafendri; Agnes Kris Darna Ningsi Gee
INSOLOGI: Jurnal Sains dan Teknologi Vol. 2 No. 5 (2023): Oktober 2023
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v2i5.2763

Abstract

The leaves of the lifeless tree (Gynura procumbens (Lour.) Merr.) have been widely used as traditional medicine and show that they can treat various diseases and infections with simple processing. However, the use of life-giving leaves as an ointment to treat wounds is very rare. The aim of this research was to produce ointment and assess the characteristics of ointments made with ethanol extract of sambungjiwa leaves. The ointment used in this research was made with ethanol extract of sambungjiwa leaves, adeps lanae, vaseline album, distilled water. Data was observed descriptively and using qualitative research methods. This study used three ointment concentrations, namely 5%, 10%, 15%, tested three times for each characteristic evaluation (organoleptic test, pH test, spreadability test, homogeneity test). The results of the research showed that the ethanol extract of the succinct leaves can be formulated as an ointment and the evaluation of the characteristics of the ointment showed that in the organoleptic test it appeared to be green in color with a semi-solid form and had a distinctive odor of the ethanol extract of the succinct leaves; the pH test shows a pH value of 5; the spreading power test shows a spreading power value of 5; and the homogeneity test showed that there were no coarse or fine grains and no color change at the beginning or end so that from the results of the characteristic test it could be concluded that the ethanol extract ointment preparation of sambungjiwa leaves met the standard requirements of the ointment characteristic test.
Application of Artificial Intelligence in Medical Diagnostics: Applications and Implications in the Healthcare Sector Arnes Yuli Vandika; Dadang Muhammad Hasyim; Devi Rahmah Sope; Legito; Novycha Auliafendri
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.674

Abstract

Artificial Intelligence (AI) has emerged as a transformative innovation in the medical diagnostic sector. This study explores the application and implications of AI in healthcare services at RSUD Dr. H. Abdul Moeloek, Bandar Lampung. Using a qualitative case study method, data were obtained through in-depth interviews and participatory observation. The results show that AI contributes significantly to improving diagnostic accuracy and speed, particularly in radiological imaging. However, limitations in technological infrastructure and system integration were found to hinder its optimal use. Furthermore, the readiness of human resources remains a critical factor. Although there is optimism among medical staff, a lack of technical training has led to gaps in understanding and utilization. Ethical and legal concerns also emerged, especially regarding responsibility in case of misdiagnosis and the protection of patient data. The absence of specific regulations and digital ethics protocols presents a major barrier to AI adoption. This research concludes that while the implementation of AI in medical diagnostics shows promising outcomes, it still faces institutional and regulatory challenges. Strengthening digital literacy among healthcare workers, developing standard operating procedures, and building a secure infrastructure are essential. Collaboration between hospitals, academic institutions, and government bodies is needed to create an inclusive and ethical AI-based healthcare ecosystem.
Analisis Polimorfisme Genetik sebagai Prediktor Respons Imun dan Efektivitas Terapi Standar pada Pasien Diabetes Melitus Tipe 2 Novycha Auliafendri; Sinaga, Alex Handani
INSOLOGI: Jurnal Sains dan Teknologi Vol. 4 No. 5 (2025): Oktober 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v4i5.6488

Abstract

Type 2 diabetes mellitus (T2DM) is a chronic disease with high prevalence and significant public health impact. This study aimed to analyze the association of IL-6 gene polymorphism (−174G>C) with serum IL-6 levels and the effectiveness of standard therapy assessed through HbA1c and Random Blood Glucose (RBG) in T2DM patients. A cross-sectional design was employed, involving 40 patients at Imelda Hospital. The polymorphism was examined using Polymerase Chain Reaction (PCR), serum IL-6 levels were measured with Enzyme-Linked Immunosorbent Assay (ELISA), while HbA1c and RBG were determined through standard laboratory analysis. The results indicated that IL-6 genotypes (GG, GC, CC) were not significantly associated with serum IL-6 levels, HbA1c, or RBG. In contrast, type of therapy showed a significant relationship with HbA1c, where patients receiving combination therapy achieved better glycemic control compared to those on monotherapy. These findings highlight that therapeutic regimen remains the primary determinant of glycemic control, whereas the role of IL-6 polymorphism in this study population appears limited. Further studies with larger sample sizes and broader genetic analyses are required to strengthen the application of precision medicine for diabetes management in Indonesia.
Co-Authors Abdul Rosid Agnes Kris Darna Ningsi Gee Arief Budi Pratomo Arnes Yuli Vandika Dadang Muhammad Hasyim Devi Rahmah Sope Legito Ramson Rikson Maruwahal Sijabat Sinaga, Alex Handani