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All Journal Hydrogen: Jurnal Kependidikan Kimia Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi
Ariyani, Helena Devi
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Chemistry Computer Science & IT Education Mathematics

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Alpha Amylase Inhibitory Activity of Curcumin Analogs and Its Synergy with Ferulic Acid in Vitro Nafillah, Khoirotun; Ariyani, Helena Devi; Asfirah, Lia Retian
Hydrogen: Jurnal Kependidikan Kimia Vol. 13 No. 3 (2025): June 2025
Publisher : Universitas Pendidikan Mandalika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/hjkk.v13i3.15683

Abstract

Curcumin analog compounds are α,β unsaturated compounds through simplifying the beta diketo group to monoketo, which has better bioavailability and a more stable structure than curcumin compounds. This study aims to determine the α-amylase inhibitory activity on symmetric curcumin analog compounds, namely the compounds 2,6-bis(3,4-dimethoxybenzylidine)cyclohexanone (A) and 2,6-bis(3,4-dimethoxybenzylidine)cyclopentanone (B). as well as testing its synergistic interaction with ferulic acid in vitro. The α-amylase inhibition test was carried out using an iodine reagent and a starch solution as a substrate. The absorbance value was measured using a UV-vis spectrophotometer (λ 568 nm), and the % inhibition was calculated. The average value of the optimum α-amylase inhibition percentage for compounds A, B, and ferulic acid, respectively is 58.17%; 22.95%, and 93.52%. Based on the synergistic interaction, it was concluded that compounds A and B showed synergistic activity with ferulic acid. The percentage of α-amylase inhibition in the concentration ratio of curcumin analog A: ferulic acid (1:8) was 98.65%, and curcumin analog B: ferulic acid (1:4) was 98.37%. This shows that combining compounds between symmetrical curcumin analogs and ferulic acid can increase the activity of antidiabetic drug candidate compounds compared to single compounds. This study offers a new approach by testing the potential combination of curcumin and ferulic acid analogues as α-amylase inhibitors in vitro, demonstrating a synergy that has not been widely explored and opening up opportunities for developing more effective natural antidiabetic therapies.
Pemodelan Graf Berarah Berbobot untuk Optimasi Penentuan Rute Terpendek Antar Kampus Polimarin Berbasis Algoritma Dijkstra Ariyani, Helena Devi; Nafillah, Khoirotun; Nindita, Kirtyana; Ngatmin, Ngatmin; Rahayu, Sri Tutie
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 14 Issue 1 April 2026
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v14i1.37524

Abstract

The mobility of academicians between the two geographically separated campuses of the Indonesian Maritime State Polytechnic (Polimarin), namely Campus 1 Ungaran and Campus 2 Bendan Duwur Semarang, creates travel efficiency issues due to numerous unmeasured route alternatives. This study aims to model the inter-campus road network as a weighted directed graph and apply the Dijkstra algorithm to determine the shortest route accurately and verifiably. The research employs an applied computational approach using actual distance data obtained from Google Maps (driving mode), collected on August 22, 2024, at 09:00 WIB to represent traffic conditions at that time. The process includes node identification (strategic locations), edge formation (connecting road segments), and weight assignment based on actual distances, resulting in a graph with 9 nodes and 10 edges. The iteration process is conducted in 8 steps by evaluating the minimum accumulated weight at each stage. The results indicate that the shortest path is A → B → E → G → H → I, passing through Jl. PTP Ngobo, Jl. Diponegoro–Jl. Slamet Riyadi, Jl. Moh. Yamin–Jl. Ahmad Yani, and Jl. Gatot Subroto, with a total distance of 25.80 km out of 11 possible routes. These findings demonstrate that the Dijkstra algorithm is effective for route optimization by eliminating inefficient paths through cumulative weight evaluation. Validation is performed by comparing the algorithm’s results with Google Maps recommendations based on travel distance. However, this study is limited to static data, and further development is required through the integration of dynamic traffic data.
Co-Authors Asfirah, Lia Retian Khoirotun Nafillah Kirtyana Nindita Ngatmin, Ngatmin Sri Tutie Rahayu