Claim Missing Document
Check
Articles

Found 33 Documents
Search

Familiar Edible Flowers in Indonesia I Nyoman Bagus Aji Kresnapati; Muhammad Eka Putra Ramandha; Nurul Indriani
PCJN: Pharmaceutical and Clinical Journal of Nusantara Vol. 1 No. 01 (2022): PCJN: Pharmaceutical and Clinical Journal of Nusantara
Publisher : CV. Nusantara Scientific Medical

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (381.802 KB) | DOI: 10.58549/pcjn.v1i01.7

Abstract

Flowers besides being used as ornamental plants, they can also be consumed. Flowers that can be consumed are called Edible Flowers. Edible flowers in general can be consumed directly, usually in tea or can be served in the form of processed food. Edible flowers contain phytochemical compounds such as anthocyanins, flavonoids, phenolics, carotenoids which are useful as antioxidants. Indonesia is rich in biodiversity with a variety of plant species that can grow, including edible flowers. There is diversity, but only a few edibles that can grow and are familiar to Indonesian people will be reviewed in this article.
Aktivitas Antibakteri Ekstrak Daun Kelor (Moringa oleifera Lam.) terhadap Staphylococcus epidermidis Penyebab Jerawat: Antibacterial Activites Cream Extracts of Kelor Leaves (Moringa oleifera Lam.) against Staphyloccus Epidermidis Cause of Acne Novitarini; Muhammad Eka Putra Ramandha; Baiq Yulia Hasni Pratiwi
Jurnal Kolaboratif Sains Vol. 7 No. 5: MEI 2024 - Jurnal Kolaboratif Sains (JKS)
Publisher : Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/jks.v7i5.5075

Abstract

Prevalensi jerawat dalam masa remaja dan resistensi antibiotik yang tinggi mendorong eksplorasi alternatif antibiotik berbasis herbal. Daun kelor (Moringa oleifera Lam.) merupakan tanaman yang memiliki aktivitas antibakteri karena mengandung senyawa flavonoid, alkaloid, tanin, dan saponin yang dapat dijadikan sebagai antibiotik berbasis herbal. Penelitian ini bertujuan untuk menguji aktivitas antibakteri dari ekstrak daun kelor (5, 10, dan 15%) terhadap Staphylococcus epidermidis penyebab jerawat. Pengujian ini menggunakan metode difusi sumuran untuk melihat aktivitas antibakteri (zona hambat) dari ekstrak daun kelor berbagai konsentrasi terhadap Staphylococcus epidermidis. Data dianalisis menggunakan One Way ANOVA dengan program SPSS. Hasil yang diperoleh berupa diameter zona hambat ekstrak etanol daun kelor konsentrasi 5, 10, 15% yaitu: 23,01 mm, 23,34 mm dan 23,68 mm. Pengujian ini mempunyai nilai Sig = 0,000 yang berarti rata rata antar kelompok terdapat perbedaan yang signifikan. Dapat disimpulkan bahwa zona hambat ekstrak daun kelor tergolong mempunyai daya hambat kuat terhadap Staphylococcus epidermidis.
AI Literacy in Chemistry Education: Rasch Analysis of Pre-Service Chemistry Teachers’ Ability To Evaluate The Conceptual Accuracy of AI-Generated Answers Muhammad Eka Putra Ramandha; Fitri, Andi Mutia
Jurnal Ilmiah Mandala Education (JIME) Vol 12 No 3 (2026): Jurnal Ilmiah Mandala Education (Agustus)
Publisher : Lembaga Penelitian dan Pendidikan Mandala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58258/1agh6950

Abstract

Generative artificial intelligence (AI) has increasingly entered higher education, including chemistry education. Although AI can provide rapid and apparently coherent explanations, its outputs may contain factual, conceptual, representational, and reasoning errors. This study examines pre-service chemistry teachers’ ability to evaluate the conceptual accuracy of AI-generated answers to chemistry problems using the Rasch measurement model. The study was designed as a quantitative descriptive evaluation involving 120 pre-service chemistry teachers and 30 scenario-based items. Each item presented a chemistry problem followed by an AI-generated response containing different levels and types of accuracy. Rasch analysis was used to estimate person ability, item difficulty, reliability, separation, and item fit. The descriptive interpretation focused on the occurrence of response patterns and the characteristics of the most difficult and easiest items. The simulated analysis produced person reliability of 0.87 and item reliability of 0.96, with person and item separation indices of 2.56 and 4.89, respectively. The most difficult items involved organic structure, chemical equilibrium, and acid-base reasoning, whereas factual errors and simple calculation errors were more readily identified. The findings indicate that the ability to use AI should not be equated with the ability to critically evaluate AI outputs. Domain-specific AI literacy in chemistry requires students to mobilize conceptual knowledge and chemical reasoning to verify apparently plausible AI-generated explanations.