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All Journal Jurnal Informatika JURNAL FARMASIMED (JFM) JISKa (Jurnal Informatika Sunan Kalijaga) Jurnal Farmanesia Jurnal Kesehatan dan Kebidanan Nusantara
Nurussakinah, Nurussakinah
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Computer Science & IT Electrical & Electronics Engineering Library & Information Science Medicine & Pharmacology

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MORINGA LEAF (Moringa Oleifera L.) ETHANOL EXTRACT CLAY MASK FORMULATION AS ANTI-AGING Nurussakinah, Nurussakinah; Fhitriana, Suzan; Khairani, Tetty Noverita; Utari, Sri
Jurnal FARMASIMED (JFM) Vol 6 No 1 (2023): Jurnal Farmasimed (JFM)
Publisher : Fakultas Farmasi Institut Kesehatan Medistra Lubuk Pakam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35451/jfm.v6i1.1193

Abstract

Aging is a human physical change caused by age, psychological, and social factors, especially on the face, neck, upper arms and hands. Aging is unavoidable and goes at different speeds, depending on one's genetics, environment and lifestyle. Synthetic antiocxidant products are many circulated in the market which have a negative impact on health. However Antioxidant compound are widely spread in nature expecially in plant. Moringa leaf is one of plants that contain abundant antioxidant, alkaloids, flavonoids, phenolics, triterpenoids/steroids and tannins. Many of people Switch to natural products. Mask from natural products are not causing irritation or less side effects. clay face mask are mostly used because of their skin rejuvenating abilities. Purpose: To know either Moringa leaf ethanol extract can be formulated in clay mask preparations and the optimal effect is to prevent aging or not. Methods: the research is including how to make clay mask with ethanol extract of Moringa leaves at concentrations of 6%, 8% and 10%. The evaluation of the physical quality of the preparation, testing the effectiveness of clay masks with ethanol extract of Moringa leaves as anti-aging. Result: the preparation is qualify the characteristic test, had a pH of 4.9-5.2, a drying time of 15-23.5 minutes, an o/w emulsion type, was stable for 12 weeks of storage, and was not caused irritation. The best result of anti-aging effectiveness test was at a concentration of 10% with 36.25 moisture content, 23.25 fineness content, 33.75 pores, 20.5 blemishes and 15.5 wrinkles. Conclusion: Moringa leaf ethanol extract can be formulated in clay mask , and is able to give the best anti-aging effect at 10% formula.
Klasifikasi Penyakit Diabetes Menggunakan Algoritma Decision Tree Nurussakinah, Nurussakinah; Faisal, Muhammad
Jurnal Informatika Vol 10, No 2 (2023): October 2023
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/inf.v10i2.15989

Abstract

Penelitian ini mengembangkan metode klasifikasi diabetes dengan menggunakan algoritma Decision Tree. Data klinis dari pasien diabetes dan non-diabetes dianalisis, termasuk atribut seperti usia, BMI, tekanan darah, dan tes gula darah. Algoritma Decision Tree berhasil mengklasifikasikan diabetes dengan akurasi tinggi, sehingga dapat membantu dokter dalam mendiagnosis dan mengelola penyakit tersebut. Pada penelitian ini menunjukkan bahwa metode klasifikasi dengan Decision Tree efektif dalam mengidentifikasi penyakit diabetes. Dalam pengujian menggunakan data uji, model klasifikasi mampu mengenali pasien diabetes dengan tingkat akurasi yang memuaskan. Metode ini memiliki potensi untuk meningkatkan diagnosis dini dan pengelolaan penyakit diabetes, tetapi perlu dilakukan penelitian lebih lanjut untuk memvalidasi dan memperluas penggunaannya dalam populasi yang lebih luas. This study developed a diabetes classification method using the Decision Tree algorithm. Clinical data from diabetic and non-diabetic patients were analyzed, including attributes such as age, BMI, blood pressure, and blood sugar tests. The Decision Tree algorithm successfully classifies diabetes with high accuracy, so it can assist doctors in diagnosing and managing the disease. This study shows that the classification method with the Decision Tree is effective in identifying diabetes. In testing using test data, the classification model is able to identify diabetic patients with a satisfactory level of accuracy. This method has the potential to improve the early diagnosis and management of diabetes, but further research is needed to validate and expand its use in a wider population. 
PENENTUAN KONSENTRASI HAMBAT MINIMUM (KHM) DARI EKSTRAK BUAH SAWO TERHADAP Salmonella typhi Nurbaya, Siti; Silalahi, Yosy Cinthya Eriwaty; Nurussakinah, Nurussakinah; Purba, Trionaldo
Jurnal Farmanesia Vol 4 No 2 (2017): Jurnal Farmanesia
Publisher : UNIVERSITAS SARI MUTIARA INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51544/jf.v4i2.2713

Abstract

Sapodilla fruit (Manilkara zapota) belongs to the Sapotaceae family. Sapodilla fruit is traditionally used in traditional medicine to cure typhoid and sapodilla fruit is not only made medicine but also the sap is taken as raw material for making chewing gum. The purpose of the examination was to determine the minimum inhibitory concentration (MIC) of sapodilla fruit extract against Salmonella typhi bacteria. The method used is the agar diffusion method using Mueller Hinton Agar (MHA) as a growth medium and paper backing. The results of the examination of the effective inhibition at a concentration of 300mg/ml with a diameter of 15.4 mm while the minimum inhibitory concentration (MIC) was at a concentration of 50mg/ml against Salmonella typhi with the smallest inhibitory diameter of 11.5 mm. From the data above, sapodilla fruit extract has a great inhibitory power against Salmonella typhi
Pentingnya Dukungan Emosional untuk Orang Tua Anak Autisme di SLB: Pembelajaran dari Pengalaman Kecemasan Nurussakinah, Nurussakinah; Suzana Mediani, Henny; Purnama, Dadang
Jurnal Kesehatan dan Kebidanan Nusantara Vol. 2 No. 1 (2024): Jurnal Kesehatan dan Kebidanan Nusantara
Publisher : CV. Utility Project Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69688/jkn.v2i1.82

Abstract

Kecemasan merupakan respons yang umum dialami oleh orang tua yang memiliki anak dengan autisme. Studi ini bertujuan untuk memberikan gambaran yang komprehensif tentang tingkat kecemasan orang tua yang memiliki anak dengan autisme di Sekolah Luar Biasa (SLB). Metode penelitian yang digunakan adalah penelitian kualitatif dengan pendekatan studi kasus di beberapa SLB. Data dikumpulkan melalui wawancara mendalam dengan 10 orang tua yang memiliki anak dengan autisme di SLB. Analisis data dilakukan dengan menggunakan pendekatan tematik. Hasil penelitian menunjukkan bahwa orang tua mengalami tingkat kecemasan yang bervariasi, mulai dari kecemasan ringan hingga kecemasan yang parah. Faktor-faktor yang mempengaruhi tingkat kecemasan ini meliputi ketidakpastian tentang masa depan anak, kesulitan dalam memahami dan mengelola perilaku anak, perasaan terisolasi atau tidak didukung oleh lingkungan sekitar, serta beban finansial dan perawatan yang tinggi. Orang tua juga mencari dukungan dari berbagai sumber, termasuk keluarga, teman, dan profesional kesehatan mental, namun seringkali merasa kurangnya akses atau dukungan yang memadai. Pentingnya memperkuat jaringan dukungan sosial bagi orang tua dalam menghadapi kecemasan terkait autisme anak di SLB diakui sebagai hal yang krusial. Kesimpulannya, kecemasan adalah pengalaman yang umum dialami oleh orang tua anak dengan autisme di SLB. Pemahaman yang mendalam tentang faktor-faktor yang mempengaruhi kecemasan ini dapat membantu institusi SLB dalam menyediakan layanan dan dukungan yang lebih baik bagi orang tua dan anak-anak mereka. Upaya-upaya untuk meningkatkan akses dan ketersediaan dukungan harus diperkuat untuk meningkatkan kesejahteraan mental orang tua dan keluarga yang memiliki anak dengan autisme.
Algoritma Random Forest dan Synthetic Minority Oversampling Technique (SMOTE) untuk Deteksi Diabetes Nurussakinah, Nurussakinah; Faisal, Muhammad; Santoso, Irwan Budi
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 10 No. 2 (2025): May 2025
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2025.10.2.221-234

Abstract

Diabetes is one of the challenges in global health. Indonesia ranks 5th in the world with the highest rate of diabetes. This research uses the Random Forest algorithm for diabetes detection. The purpose of the study is to detect diabetes with the Random Forest algorithm that provides accurate and efficient results in the early diagnosis of diabetic patients. The data used is secondary data "Diabetes Dataset" which consists of 952 data and has 17 features. The test scenario in this study divides the data consisting of 3 parts, namely scenario 1 90%:10% ratio, scenario 2 70%:30% ratio, scenario 3 50%:50% ratio. In each scenario, a comparison between using SMOTE and not using SMOTE is applied. The best performance results are obtained in scenario 1 which uses SMOTE, which produces 97% accuracy, 100% precision, 94% recall and the last is F1-Score which produces 97%.
Co-Authors Dadang Purnama Fhitriana, Suzan Irwan Budi Santoso Khairani, Tetty Noverita Muhammad Faisal Purba, Trionaldo Siti Nurbaya Suzana Mediani, Henny Utari, Sri Yosy Cinthya Eriwaty Silalahi