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All Journal Journal of Food and Pharmaceutical Science Jurnal Mandala Pengabdian Masyarakat Journal of Food and Pharmaceutical Sciences
Anggriani Syafrie, Firhani
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Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Immunology & microbiology Materials Science & Nanotechnology Medicine & Pharmacology Neuroscience Public Health Social Sciences

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Pelatihan Pembuatan Teh Herbal Kombinasi daun Kelor Dan Kulit Jeruk Nipis Di Desa Puasana, Kec.Moramo Utara, Kab.Konawe Selatan rahmaniar, dian; Hasanuddin, Silviana; Yuliastri, Wa Ode; Anggriani Syafrie, Firhani; Putri, Tenri Zulfa Ayu Dwi; Kadrina, Desi; Asri, Nur Ainun
Jurnal Mandala Pengabdian Masyarakat Vol. 5 No. 2 (2024): Jurnal Mandala Pengabdian Masyarakat
Publisher : Progran Studi Farmasi Universitas Mandala Waluya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35311/jmpm.v5i2.412

Abstract

Pemanfaatan tanaman sekitar sebagai produk herbal merupakan salah satu kegiatan yang penting dilakukan guna pemanfaatan tanaman dari bahan alam. Pelatihan pembuatan teh herbal dari daun kelor dan kulit buah jeruk dilakukan oleh tim pengabdian masyarakat program studi farmasi kepada ibu Pemberdayaan Kesejahteraan Keluarga di Desa Desa Puasana, Kecamatan Moramo Utara, Kabupaten Konawe Selatan. Tujuan dari pengabdian ini adalah memberikan informasi tentang manfaat daun kelor (Moringa oleifera Lam) dan Kulit jeruk nipis (Citrus aurantifolia) dan meningkatkan keterampilan tentang cara mengolah daun kelor (Moringa oleifera Lam) dan Kulit jeruk nipis (Citrus aurantifolia) menjadi bahan baku pembuatan teh herbal. Metode yang digunakan pada pelatihan ini yaitu diawali dengan proses diskusi mengenai tanaman dan produk dari tanaman serta dan tes baik sebelum maupun sesuah penuluhan. tertulis sebelum edukasi kemudian penyuluhan dan pelatihan pembuatan teh herbal Pada tahap penyuluhan dan edukasi tim pengabdian mendeskripsikan tentang pentingnya teh herbal bagi kesehatan, manfaat teh herbal dari daun kelor dan kulit buah jeruk, keunggulan produk dan cara pembuatan teh herbal ini. Hasil pelatihan tersebut adalah masyarakat memperoleh pengetahuan dan pengalaman mengenai cara mengolah dan mengemas teh secara benar melalui pemaparan materi, diskusi, dan sesi tanya jawab selama sesi edukasi. Berdasarkan hasil uji tanya jawab melalui kuesioner menunjukkan peningkatan pengetahuan dan pemahaman masyarakat yaitu dari 34% menjadi 94%.
Application of Clustering Analysis with Unsupervised Technique on Fish Oil Samples Miftahul Jannah, Nadia; Primatyas Ningrum, Karina; Anggriani Syafrie, Firhani
Journal of Food and Pharmaceutical Sciences Vol 13, No 2 (2025): J.Food.Pharm.Sci
Publisher : Integrated Research and Testing Laboratory (LPPT) Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jfps.21517

Abstract

Fish oil contains many fatty acids (FAs) important for human health. Each fish oil tends to have a different fatty acid content. This study aims to group the fish oil content profile in several samples, such as keting fish oil (KFO), catfish oil (CFO), and pomfret fish oil (PFO), based on GC-MS analysis data with unsupervised techniques. GC-MS is a method that can be used to identify the fatty acid content in fish oil. Fish oil is extracted using the dry rendering method combined with a hydraulic press to obtain the oil, then derivatised before being analysed on the GC-MS instrument. Due to the multivariate data from GC-MS, multivariate statistical techniques are required to effectively group the fish oil samples based on their Fatty Acid profiles. Principal Component Analysis (PCA) and Cluster Analysis (CA) chemometrics are unsupervised techniques that can group multivariate data by displaying plot scores and dendrograms of sample analysis results. The fatty acid content of keting fish, catfish, and pomfret fish oil has three dominant compounds in sequence, namely oleic acid, palmitic acid, and stearic acid, with different percentages. Thegrouping profile of fish oil was successfully determined by PCA, total variance explained by the first four components (PC4) of 99.4%, and CA, which produced three groups based on the fatty acid content of fish oil.
Application of Clustering Analysis with Unsupervised Technique on Fish Oil Samples Miftahul Jannah, Nadia; Primatyas Ningrum, Karina; Anggriani Syafrie, Firhani
Journal of Food and Pharmaceutical Sciences Vol 13, No 2 (2025): J.Food.Pharm.Sci
Publisher : Integrated Research and Testing Laboratory (LPPT) Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jfps.21517

Abstract

Fish oil contains many fatty acids (FAs) important for human health. Each fish oil tends to have a different fatty acid content. This study aims to group the fish oil content profile in several samples, such as keting fish oil (KFO), catfish oil (CFO), and pomfret fish oil (PFO), based on GC-MS analysis data with unsupervised techniques. GC-MS is a method that can be used to identify the fatty acid content in fish oil. Fish oil is extracted using the dry rendering method combined with a hydraulic press to obtain the oil, then derivatised before being analysed on the GC-MS instrument. Due to the multivariate data from GC-MS, multivariate statistical techniques are required to effectively group the fish oil samples based on their Fatty Acid profiles. Principal Component Analysis (PCA) and Cluster Analysis (CA) chemometrics are unsupervised techniques that can group multivariate data by displaying plot scores and dendrograms of sample analysis results. The fatty acid content of keting fish, catfish, and pomfret fish oil has three dominant compounds in sequence, namely oleic acid, palmitic acid, and stearic acid, with different percentages. Thegrouping profile of fish oil was successfully determined by PCA, total variance explained by the first four components (PC4) of 99.4%, and CA, which produced three groups based on the fatty acid content of fish oil.
Co-Authors Asri, Nur Ainun Dian Rahmaniar, Dian Hasanuddin, Silviana Kadrina, Desi Nadia Miftahul Jannah Ningrum, Karina Primatyas Putri, Tenri Zulfa Ayu Dwi Yuliastri, Wa Ode