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Menggali manfaat Tanaman Obat Keluarga (TOGA) sebagai solusi kesehatan mandiri di Desa Rantau Langsat Mukhtar, Harun; Handayani, Fitri; Amran, Hasanatul Fuadah; Yordan, Gibril; Danillo, Amadel; Hartanto, Fizhra Dwi Putra; Benu, M. Rajib Owiendra; Maulana, Ade Irvan; Irawan, Eldi; Wijaya, Peter
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 9, No 4 (2025): Juli
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v9i4.32068

Abstract

Abstrak Pemanfaatan Tanaman Obat Keluarga (TOGA) merupakan salah satu upaya untuk meningkatkan kesehatan dan kesejahteraan masyarakat secara mandiri. Penelitian ini bertujuan untuk mendeskripsikan pelaksanaan kegiatan pengembangan TOGA di Desa Rantau Langsat melalui sosialisasi, pelatihan pengelolaan tanaman obat, simulasi penggunaan formularium ramuan obat tradisional, serta pendirian kebun TOGA. Kegiatan dilaksanakan oleh tim KKN dengan melibatkan masyarakat, khususnya kader PKK, dan mendapatkan dukungan dari pemerintah desa. Hasil kegiatan menunjukkan adanya peningkatan pengetahuan dan keterampilan masyarakat dalam mengenali, menanam, merawat, dan memanfaatkan tanaman obat secara mandiri. Sebuah kebun TOGA percontohan seluas 4 x 4 meter berhasil dibangun dan berfungsi sebagai pusat pembelajaran masyarakat. Keberlanjutan program ini ditunjang oleh pendampingan yang konsisten dan evaluasi efektivitas pemanfaatan tanaman obat sebagai terapi tradisional. Selain itu, kegiatan ini membuka peluang pemberdayaan ekonomi melalui pengembangan produk olahan dan pemanfaatan limbah tanaman obat. Secara keseluruhan, pemanfaatan TOGA berpotensi menjadi alternatif pengobatan yang efektif sekaligus sumber penghasilan tambahan bagi masyarakat Desa Rantau Langsat. Kata kunci: tanaman obat keluarga; pemanfaatan; pengabdian masyarakat; kesehatan; pemberdayaan ekonomi. Abstract The utilization of Family Medicinal Plants (TOGA) is one of the efforts to improve public health and welfare independently. This study aims to describe the implementation of TOGA development activities in Rantau Langsat Village through socialization, training on medicinal plant management, simulations of traditional herbal formulations, and the establishment of a TOGA demonstration garden. The activities were carried out by a community service team (KKN) involving local residents, particularly PKK women’s group members, with support from the village government. The results indicated an increase in community knowledge and skills in identifying, cultivating, maintaining, and independently utilizing medicinal plants. A 4 x 4 meter TOGA demonstration garden was successfully established and serves as a community learning center. The program's sustainability is supported by continuous mentoring and evaluation of the effectiveness of medicinal plant-based therapies. Furthermore, the initiative opens up opportunities for economic empowerment through the development of processed products and the use of medicinal plant waste. Overall, the utilization of TOGA has the potential to become an effective alternative treatment and a supplementary source of income for the residents of Rantau Langsat Village. Keywords: family medicinal plants; utilization, community service; health; economic empowerment.
Klasifikasi Penyakit Daun Kentang dengan Transfer Learning Menggunakan CNN optimalisasi Arsitektur MobileNetV2 Gunawan, Rahmad; Fauzan Salim; Wahyudhy, Adhe Indra; Wibowo, Angga Yudha; Yordan, Gibril; Filamori, Refly Fauzan
Computer Science and Information Technology Vol 6 No 2 (2025): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v6i2.8599

Abstract

Potatoes are a major food crop with high economic value, but they are susceptible to various Diseases impacting potato leaves can significantly influence their quality and productivity. This research focuses on identifying diseases in potato leaves through the Convolutional Neural Network (CNN) approach, leveraging transfer learning with the MobileNetV2 architecture. The dataset utilized comprises 4,072 images of potato leaves. categorized into three groups: non-infected leaves (healthy ), Early Blight-infected leaves, and Late Blight-infected leaves. The dataset is processed through data augmentation and normalization to enhance data quality. The resulting model demonstrates excellent performance, achieving an accuracy of 95.31%, a precision of 95.81%, a recall of 95.31%, and an F1-Score of 95.38%. These findings indicate the approach demonstrates its ability to identify the condition of potato leaves with a low classification error rate, especially in the healthy category. However, there are challenges in classifying between Early Blight and Late Blight that require further analysis and method improvement. This study contributes to the development of efficient and accurate plant disease detection systems.