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The effect of genitri (Elaeocarpus ganitrus) in leukocytes profile of wistar rats as a prospective immunomodulatory agent Primiani, Cicilia Novi; Pujiati, Pujiati; Bhagawan, Weka Sidha; Waris, Waris; Krisnamurti, Gabriella Chandrakirana
Jurnal Biolokus : Jurnal Penelitian Pendidikan Biologi dan Biologi Vol 8, No 1 (2025): June
Publisher : Universitas Islam Negeri Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30821/biolokus.v8i1.3987

Abstract

Immunomodulator is an agent to activate and modulate the immune response. It is one of the approaches to prevent chronic disease and maintain homeostasis. Recently,  plant phytochemicals have been developed as prospective immunomodulatory agents. Genitri (Elaeocarpus ganitrus), a local plant cultivated in Indonesia, exhibited various biological properties and potential as an immunomodulatory agent. This study aims to identify the potency of genitri as immunomodulatory agent through leukocyte profiling. Genitri leaf (P1), seed (P2), and fruit (P3) were prepared as powder and administered to male wistar rats weighted 250-300 g twith six replications for 28 days. The total leukocytes were  counted and leukocytes were being  profiled following the treatment with genitri powder then  compared with control treatment (P0). The immunomodulatory activity of genitri was shown by the increased leukocytes count following treatment. Based on data from the treatment group (P2), genitri seeds were able to increase leukocytes by 10595.83 cells/µl. The highest total leukocytes were found in treatment P2 with total leukocytes 10595.83 cells/µl. Based on the leukocyte profile, lymphocytes and monocytes were found to be the highest in all treatments. Treatment with genitri was able to stimulate an increase in lymphocytes and monocytes. An increase in total leukocytes given genitri is an indication of an increased immune response.
Class Balancing and Parameter Tuning of Machine Learning Models for Enhancing Aphrodisiac Herbal Plant Classification Jayadi, Puguh; Bhagawan, Weka Sidha; Aldida, Jofanza Denis
Journal of INISTA Vol 7 No 2 (2025): May 2025
Publisher : LPPM Institut Teknologi Telkom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/inista.v7i2.1832

Abstract

Herbal plants with aphrodisiac claims are an important part of traditional medicine that continues to evolve within the modern scientific context. However, the classification process for these plant claims is often done manually and subjectively, necessitating a more objective, data-driven approach. Artificial Intelligence (AI) and its various derivatives, such as Machine Learning, present a reliable solution for several related classification studies. The primary challenge in classification lies in data class imbalance and selecting the optimal model parameters. This study proposes an integrated approach that utilizes machine learning algorithms, including Random Forest, Support Vector Machine (SVM), and XGBoost, combined with SMOTE class balancing techniques and hyperparameter tuning through Grid Search, Random Search, and Bayesian Optimization. Experiments were conducted on a dataset of herbal plants with attributes and labels of aphrodisiac claims, and the results were evaluated based on accuracy, precision, recall, and execution time. The findings indicated that the combinatorial approach significantly improved model performance compared to the basic approach. Among the hyperparameter tuning results, the SVM method achieved the best accuracy (0.889) and precision (0.889). This research contributes to the development of an AI-based classification system in the field of ethnopharmacology. It can serve as a reference for creating scientifically validated databases of herbal plants.
Co-Authors . Waris Agnis Pondineka Ria Aditama Aissyah Nurfatma Aldida, Jofanza Denis Amaranto, Jennifer Anik Listiyana Annisa, Rahmi Arum Suproborini Arum Suproborini Asri Wido Mukti Asti Rahayu Atiqah, Sri Nur Atiza Fajrin Maulidya Bhagawan, Weka Burhan Ma'arif Burhan Ma’arif Cicilia Novi Primiani Cicilia Novi Primiani Devi Safrina Dewi Ratih Tirto Sari Dian Susanti Donato, Percival Faisal Akhmal Muslikh Fidia Rizkiah Inayatilah Firsta Roisatul Islamiyah Hadya, Chorida Muhjatul Heni Pujiastuti Hison, Jade Huwaida, Fadhila Isma Irawati, Santia Izza Nailia Shirvi Jauhar Maknun Septaza Rahmandika Jayadi, Puguh Krisnamurti, Gabriella Chandrakirana Kurniawan Hidayat Perdana Putra Lestari, Nia Ayu Lisniawati Lisniawati M Bakti Samsu Adi Ma'arif Z.A, Burhan Ma'arif, Burhan Ma'arif, Burhan Mandalawati, Titin Maritha, Vevi Mochammad Amrun Hidayat Muhammad Evy Prastiyanto Norachuriya, Zedny Nur Rahmawati Wijaya Nurfatma, Aissyah Octavia, Nur Ika Peria, Jo Prasetyo, Yona Primiani, Cicilia Novi Primiani, Cicilia Novi Primiani Pujiati Pujiati Pujiati Putra, Aditya Dwi Permana Rahmawati, Eka Diana Rahmi Annisa Ramadhani D.A., Ria Ramdhani, Alfina Widya Retno Susilowati Ria Ramadhani Dwi Atmaja Rina Nurmaulawati Rivera, Alice Rizal Maarif Rukmana, Rizal Maarif Rizkiah, Fidia Roihatul Mutiah Roihatul Mutiah Safitri, Rusiana Yulia Santos, Gema Silfarohana, Rantika Suproborini, Arum Tanghal, Analiza Taufik, Imam Teguh Pamungkas, Rizki Putra Ubaidillah Abdel Barsyaif Yanuar Ashari Cahyaningrum Yaya Sulthon Aziz Yen Yen Ari Indrawijaya Zatalini, Dioni Zatalini, Dioni Fadia