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All Journal Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Olandina Cahyani P
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Analisis Graph Mining dalam Penentuan Senyawa Dan Tanaman Obat Indonesia Sebagai Antihipertensi Lusi Agus Setiani; Deden Ardiansyah; Asep Saepulrohman; Arief Rachman Hakim; Olandina Cahyani P
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol 19, No 1 (2022): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v19i1.4284

Abstract

Hypertension, also known as high blood pressure, is a degenerative disease whose prevalence tends to increase every year. People in Indonesia generally treat this disease by using a mixture of several types of herbal plants or so-called herbs. This study aims to find out the potential of compounds and plants that have effectiveness as antihypertensives by combining the concept of multicomponent-multi-target with a bioinformatics approach. This study aims to find out the potential of compounds and medicinal plants in Indonesia that have effectiveness as antihypertensives using graph mining analysis. Graph tracing techniques can be applied to search for compounds and plants related to target proteins in a disease. Patikan kebo (Euphorbia factor Ti2, betaAmyrin, alpha-Amyrin), mango (3-Carene, L-Histidine), cayenne pepper (Capsanthin, Capsorubin, Solasonine), papaya (L-Histidine, Sterol, Caffeine), and fenugreek ( L-Histidine) is the best plant that acts as an antihypertensive agent by targeting 4 proteins or about 80% of the total 5 significant proteins in hypertension.
Co-Authors Arief Rachman Hakim Asep Saepulrohman Deden Ardiansyah Lusi Agus Setiani