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All Journal Journal of Tropical Life Science : International Journal of Theoretical, Experimental, and Applied Life Sciences EKSAKTA : Jurnal Penelitian dan Pembelajaran MIPA Pendas : Jurnah Ilmiah Pendidikan Dasar Jurnal Basicedu TESLA: Jurnal Teknik Elektro Science Education and Application Journal Studies in Learning and Teaching BIOCHEPHY: Journal of Science Education Jurnal Basicedu JIPI (Jurnal IPA dan Pembelajaran IPA)
Fasih Bintang Ilhami, Fasih Bintang
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Education Electrical & Electronics Engineering Energy Engineering Environmental Science Mathematics Physics Social Sciences Other

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Phytochemical Screening and In Silico Prediction of Gynura divaricata Ethanolic Extract as A Potential PIM-1 Inhibitor: Phytochemical and In Silico Prediction of Gynura divaricata Puspitarini , Sapti; Hermanto, Feri Eko; Rohim, Abd; Dliyauddin, Moh; Hendratmoko, Ahmad Fauzi; Budiyanto, Mohammad; Ilhami, Fasih Bintang
Journal of Tropical Life Science Vol. 16 No. 01 (2026)
Publisher : Journal of Tropical Life Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/jtls.16.01.06

Abstract

The pharmacological properties and traditional uses of medicinal plants often correlate with their bioactive constituents, which contribute to diverse therapeutic effects, including anticancer activity. Cancer remains one of the leading causes of mortality worldwide, and the discovery of novel anticancer agents from natural sources continues to be an important research focus. Gynura divaricata is a medicinal herb widely used in traditional Asian medicine for treating diseases. Recent studies have reported that G. divaricata contains several bioactive compounds. such as flavonoids, phenolic acids, terpenoids, and alkaloids, which are known for their antioxidant and anticancer properties. However, despite its traditional use and pharmacological potential, the molecular mechanisms underlying the anticancer activity of G. divaricata remain poorly understood. This study aimed to screen the phytochemical content of the ethanolic leaf extract of G. divaricata and to predict its potential anticancer activity through computational analysis targeting the PIM-1 protein. The DPPH inhibition, total flavonoid content, and total phenolic content of the extract were evaluated. Phytochemical profiling was performed using LC-HRMS. Molecular docking and molecular dynamics simulations were conducted to predict the interactions between the active compounds of G. divaricata and the PIM-1 protein. The extract exhibited 50% DPPH inhibition at a concentration of 2071.01 ppm, with total flavonoid and total phenolic contents of 107.44 ± 4.41 mg QE/g and 10.96 ± 0.49 mg GAE/g, respectively. Identified bioactive compounds, including curcumin, (+)-ar-turmerone, and 4-coumaric acid, were further analyzed through molecular docking to assess their interactions with the PIM-1 kinase. The docking results revealed that these compounds showed favorable binding affinities to the active site of PIM-1, suggesting their potential as anticancer agents. This study is the first to report the potential of G. divaricata active compounds as PIM-1 inhibitors, warranting further validation through both in vitro and in vivo studies.  
DEEP LEARNING DALAM PEMBELAJARAN INKUIRI: STRATEGI EFEKTIF DALAM MENGEMBANGKAN KEMAMPUAN BERPIKIR ABDUKTIF SISWA SMP PADA PEMBELAJARAN IPA Aisy, Azzah Rohadatul; Ilhami, Fasih Bintang
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 11 No. 02 (2026): Volume 11 No. 2, Juni 2026 Publish
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v11i02.45281

Abstract

This study aims to analyze the effectiveness of deep learning-based inquiry learning in improving students' abductive thinking skills at SMP Negeri 2 Sidoarjo on mixed materials. This study applies a quantitative research method with a quasi-experimental type with a one-group pretest and posttest design. In this study, one group was observed as a subject that began with a pretest before learning, then given treatment in the form of the application of deep learning-based inquiry learning and ended with a posttest. The results of the study indicate that deep learning-based inquiry learning has a positive impact on improving higher-order thinking skills, in this case students' abductive thinking skills. The results of the paired t-test showed a significant difference between the pretest and posttest when before and after the implementation of deep learning-based structured inquiry learning. The effect size results on all abductive indicators also showed that the increase was in the "large" category. The highest effect size value was found in the indicator of formulating problems & determining objectives, and formulating conclusions with the "large" category. The lowest effect size value was found in the analogy indicator which was in the "small" category.
Co-Authors Ahmad Fauzi Hendratmoko Aisy, Azzah Rohadatul Arbiana, Barika Arrayan, Hamdi Dliyauddin, Moh ERMAN ERMAN Fatimatuz Zahro Hermanto, Feri Eko Khasanah, Khilyah M Munasir MOHAMMAD BUDIYANTO Mulyaningrum, Harnis Sekar Nadi Suprapto Prayogi, Ananda Puspitarini , Sapti Rohim, Abd Rohmah, Asna Aisiyah Lailatul Sihombing, Rizky Agassy Uyuni, Qurrotul Widodo*, Wahono Yuniswara, Riga Agnes ZAINUL ARIFIN IMAM SUPARDI