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All Journal Jurnal Penelitian Pendidikan IPA (JPPIPA) Asean Journal of Science and Engineering (AJSE)
Afifi Mutiarani
Universitas Pendidikan Indonesia
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Education Engineering Materials Science & Nanotechnology Physics

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The Effectiveness of Mugwort Leaf Extract and Gotu Kola Leaf Extract against Acne Bacterial Activity Diah Puspita Sari; Shintya Yuniar; Siti Awalia Nur Fadillah; Afifi Mutiarani; Diah Kusumawaty
ASEAN Journal of Science and Engineering Vol 2, No 3 (2022): AJSE: December 2022
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (835.089 KB) | DOI: 10.17509/ajse.v2i3.39634

Abstract

Acne is a problem among teenagers generally caused by bacterial infections such as Propionibacterium acnes, Staphylococcus aureus, and Staphylococcus epidermidis. Mugwort (Artemisia vulgaris L.) and Gotu Kola (Centella asiatica L.) extracts have antibacterial activity formulated in anti-acne gel preparations. The purpose of this study was to test and obtain a gel formula of mugwort leaf extract and gotu kola leaf extract which effectively kills and controls the growth of acne-causing bacteria. The methods used in this study include simplicity making, leaf extraction, making anti-acne gel preparations, testing pH, homogeneity, inhibition, and data analysis. The extract obtained by maceration was made in three concentrations, namely 2.50; 5.00; and 10.00%. The results showed that the pH value of the gel preparations obtained was in the range of 8.08-9.96. Mugwort leaf extract, gotu kola leaf, and mugwort-gotu kola have a distinctive smells with a thick texture at a concentration of 2.50% and a liquid texture at a concentration of 10.00%. Inhibition tests showed that the mugwort extract sample had a value of 16-18 mm, while the gotu kola extract and mugwort-gotu kola had a value of 14 mm. Mugwort leaf extract is able to inhibit the growth of acne-causing bacteria. This success was obtained because the extracts of mugwort and gotu kola leaves contain flavonoids that can inhibit the growth of bacteria that cause acne. Mugwort leaf extract gel with a concentration of 2.50 and 5.00% had the largest zone of inhibition in inhibiting P. acnes bacteria compared to other concentrations.
Innovating Bacterial Cultivation Practicums to Promote Deep Learning: A Trial and Reconstruction of Student Worksheets (LKPD) Afifi Mutiarani; Amprasto; Kusnadi
Jurnal Penelitian Pendidikan IPA Vol 11 No 7 (2025): July
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i7.11220

Abstract

This study aims to evaluate and test the feasibility of a student worksheet (LKPD) on bacterial cultivation and observation from a Natural Science textbook for grade X senior high school as a means to foster deep learning in the context of the deep learning. Using the Vee Diagram approach, the analysis shows that the LKPD contains several fundamental shortcomings—particularly in its unclear learning objectives, unsystematic procedures, and minimal space for reflection and data transformation. Through a self-conducted practicum trial, these identified weaknesses were indeed reflected in field implementation. Although the practicum was conducted, it faced issues such as overly dense colony growth, contamination, and inappropriate inoculation techniques, which led to suboptimal observations. This confirms that the structure and instructions in an LKPD significantly influence the success of experimental learning. Nonetheless, the activity revealed potential for further development. The practicum offers students the opportunity to experience scientific processes firsthand and understand the connection between biological concepts and real-life phenomena. With improved structure and approach, the LKPD can serve as an effective tool to support deep learning.
Co-Authors Diah - Kusumawaty Diah Puspita Sari Kusnadi Mr Amprasto Shintya Yuniar Siti Awalia Nur Fadillah