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All Journal Majalah Kedokteran Scientific Journal of Informatics Kreasi: Jurnal Inovasi dan Pengabdian Kepada Masyaraka
Karina
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Computer Science & IT Environmental Science Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Social Sciences

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Effect of autologous stromal vascular fraction (SVF) for diabetes mellitus type-2 Remelia, Melinda; Novriandina, Shanaz; Karina; Panjaitan, Ani O.; Andriana, Jumaini; Sitohang, John; Batubara, Frisca; Wiyanto, Marwito; Sitompul, Yunita R.M.B
Majalah Kedokteran UKI Vol. 38 No. 1 (2022): JANUARI - APRIL
Publisher : Fakultas Kedokteran Universitas Kristen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33541/mk.v38i1.4188

Abstract

Autologous Stromal Vascular Fraction (SVF) is one of the alternative therapy for type 2 diabetes that might potentially regenerate pancreatic beta cells. HbA1c levels ≤7% is an efficacious indicator for type 2 diabetes mellitus treatment. The aim of this study is to analyze the effect of autologous SVF therapy on decreasing HbA1c levels of type 2 diabetes patients at Hayandra Clinic in 2016. This study uses observational analytics by obtaining 30 patients' medical records after autologous SVF therapy and analyzing by using paired t-test. The results showed a decrease in HbA1c levels in 24 patients (83.4%), increased HbA1c levels in 4 patients (13.3%), and two patients (3.3%) who had no changes in HbA1c levels after one month got autologous SVF therapy. Based on HbA1c levels as an efficacious indicator, there was an increase in the percentage of type 2 diabetes patients with controlled HbA1c levels from 37% to 47%. The percentage of type 2 diabetes patients with uncontrolled HbA1c levels decreased from 63% to 53%. There was a correlation between autologous SVF therapy and the decrease of HbA1c levels in type 2 diabetes patients (p=0,003). Keywords: Type 2 diabetes; HbA1c levels; Stromal Vascular Fraction
Upaya Peningkatan Pengetahuan Wanita Usia Subur (WUS) dalam Penggunaan IUD Melalui Pendidikan Kesehatan Nur Ramadani, Fikria; Azmi, Nurul; Siti Syarah, Eneng; Karina; Nita
KREASI : Jurnal Inovasi dan Pengabdian kepada Masyarakat Vol. 3 No. 2 (2023): Agustus
Publisher : BALE LITERASI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58218/kreasi.v3i2.611

Abstract

Intra Uterine Device (IUD) menjadi alat kontrasepsi yang paling di rekomendasikan dalam indikator program kesehatan masyarakat dalam rencana pembangunan nasional jangka menengah (RPJMN) karena efektif digunakan dalam jangka waktu lama, lebih dari dua tahun serta lebih efisien untuk tujuan pemakaian menjarangkan kelahiran lebih dari tiga tahun atau mengakhiri kehamilan pada PUS yang sudah tidak ingin menambah anak lagi. Dalam upaya peningkatan prevalensi IUD, perlu dilakukan kegiatan peningkatan pengetahuan, sharing, dan komunikasi, serta dukungan sehingga memberikan dampak yg positif dalam penggunaan IUD. Metode pelaksanaan pengabdian masyarakat dilaksanakan dengan memberikan pendidikan kesehatan tentang Pengetahuan terkait IUD dan keuntungan dari penggunaan IUD kepada Wanita Usia Subur (WUS). Alat peraga yang dugunakan berupa lembar balik dan leaflet. Terdapat peningkatan pengetahuan terhadap manfaat dan keuntungan penggunaan KB IUD sebesar 88% setelah dilakukan pendidikan kesehatan. Masyarakat mendukung dan terbuka terhadap informasi baru yang diberikan guna mendapatkan pelayanan KB yang berkualitas.
Analisis Perbandingan Prediksi Harapan Hidup Hepatitis Menggunakan Algoritma K-Nearest Neighbor dan C4.5 Karina; Hanum, Herlina; Desiani, Anita
Jurnal Ilmiah Informatika Vol. 8 No. 2 (2023): Jurnal Ilmiah Informatika
Publisher : Department of Science and Technology Ibrahimy University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/jimi.v8i2.98-111

Abstract

Hepatitis is an inflammatory disease of the liver caused by a virus that causes damage to the cells and function of the liver. This study compares the accuracy, precision, and recall results of the K-Nearest Neighbor (K-NN) and C4.5 algorithms using the Percentage Split and K-fold Cross Validation methods. Of the two algorithms, the best level of accuracy is obtained using the K-fold Cross Validation method. Based on the accuracy and error rate, the best algorithm for predicting life expectancy for hepatitis sufferers is the K-NN algorithm. Based on the special Precision and Recall values ​​on the Recall value to predict class zero the best algorithm is obtained using the C4.5 algorithm. To assess Precision and Recall, the other best algorithm in predicting the fixed response variable is obtained by using the K-NN algorithm. Overall, the best algorithm for predicting life expectancy for hepatitis sufferers is the K-Nearest Neighbor (K-NN) algorithm.
Co-Authors Andriana, Jumaini Anita Desiani Batubara, Frisca Herlina Hanum, Herlina Nita Novriandina, Shanaz Nur Ramadani, Fikria Nurul Azmi, Nurul Panjaitan, Ani O. Remelia, Melinda Siti Syarah, Eneng Sitohang, John Sitompul, Yunita R.M.B Wiyanto, Marwito