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DETEKSI gen Cat P PENYANDI RESISTEN ANTIBIOTIK KLORAMFENIKOL PADA Salmonella typhi DENGAN MENGGUNAKAN TEKNIK PCR Sri Anggarini Rasyid; Sugireng; Adelia Pratiwi
Jurnal MediLab Mandala Waluya Vol. 4 No. 2 (2020): Jurnal MediLab Mandala Waluya
Publisher : Prodi D4 Teknologi Laboratorium Medis, Universitas Mandala Waluya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54883.4.2.1

Abstract

Demam tifoid merupakan infeksi sistemik yang disebabkan oleh bakteri Salmonella typhi. Antibiotik yang sering digunakan dalam terapi demam tifoid adalah klorampenikol. Penggunaan antibiotik diketahui menyebabkan masalah baru yaitu munculnya resistensi terutama pada pemakaian antibiotik yang tidak prosedural dan tidak terkontrol. Resistensi terhadap kloramfenikol (Cm) diperantarai oleh enzim yang terletak pada plasmid yang disebut Acetyltransferase kloramfenikol (CAT). Penelitian ini dilakukan untuk mengetahui Deteksi Gen Cat P Penyandi Resisten Antibiotik Kloramfenikol Pada Salmonella typhi dengan Menggunakan Teknik PCR. Jenis penelitian adalah penelitian deskriptif dengan desain penelitian cross sectional yakni untuk menganalisi Deteksi Gen Cat P Penyandi Resisten Terhadap Antibiotik Kloramphenikol Pada Salmonella thypi dengan Menggunakan Metode PCR. Sampel yang digunakan dalam penelitian ini adalah darah penderita demam tifoid yang disajikan dalam bentuk kultur berjumlah 10 sampel. Hasil pemerikaan gen Cat P dari 10 sampel penelitian didapatkan hasil negatif pada semua sampel yang ditandai dengan tidak ditemukan pita DNA gen Cat P sesuai target yaitu dengan target DNA 436 bp. Untuk peneliti selanjutnya disarankan agar meneliti variabel pemeriksaan gen Cat P sebagai penanda resistensi antibiotik Kloramfenikol pada penderita demam tifoid stadium lanjut dengan menggunakan sampel feces dan urin.
Hubungan Tingkat Pengetahuan Pasien Hipertansi Terhadap Kepatuhan Minum Obat Pada Pasien Rawat Jalan Di Rumah Sakit Royal Prima Adelia Pratiwi; Muhammad Yunus; Roy Indrianto Bangar
Jurnal Sains Farmasi Dan Kesehatan Vol. 3 No. 2 (2025): September - Desember
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62379/jfkes.v3i2.3416

Abstract

Hypertension s a chronic condition with a high prevalence that can lead to cardiovascular complications if patients do not adhere to medication regimens and the medication adherence is on of the primary key to therapeutic success. However, low adherence rates remain a significant challenge, often linked to insufficient patient understanding. This study aimed to analyze the relationship between the level of knowledge of hypertensive patients and their medication adherence at Royal Prima Hospital. This research method employed a quantitative correlational design with a cross-sectional approach involving 78 outpatient respondents selected through purposive sampling. Demographic data were analyzed using the Chi-Square Test, while the relationship between the main variables was tested with Spearman Correlation. The results showed that the majority of respondents had a sufficient level of knowledge (52.6%) and moderate adherence (48.7%). The Spearman Correlation test yielded a coefficient value (rₛ) of 0.803 with p < 0.001, indicating a very strong and significant positive relationship between the level of knowledge and medication adherence. Conversely, the Chi-Square Test results showed no significant association between demographic characteristics and adherence. It is concluded that knowledge is a crucial determinant influencing treatment adherence among hypertensive patients.
Segmentasi Produk Fashion Berdasarkan Harga, Ukuran, dan Merek Menggunakan K-Means di Rapidminer Sanjaya, Ival; Nitami Evita Inonu; Muhammad Fahmi Fudholi; Adelia Pratiwi; Heni Sulistiani
Journal of Informatics Management and Information Technology Vol. 5 No. 3 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v5i3.651

Abstract

Tight competition and product diversity are the hallmarks of the fashion industry, especially in terms of price variation, size, and brand. To help the process of making more accurate business decisions, product segmentation is needed to identify the characteristics of each group. This study utilizes the K-Means Clustering algorithm to group fashion products based on these attributes. The implementation is carried out using the RapidMiner platform, starting with the data normalization stage and the transformation of categorical attributes into numeric form. The optimal number of clusters is determined through the elbow method approach, which shows a significant decrease in the average distance between data in the cluster. The clustering results show the formation of product groups with different characteristics, which can be utilized in stock planning and marketing strategies. This study confirms that the K-Means algorithm is effective in analyzing the distribution of fashion products based on the main attributes they have.