Sri Mulyati
JTRR Health Polytechnic Semarang

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PENDAMPINGAN PEMBENTUKAN BANK SAMPAH DI KELURAHAN METESEH KECAMATAN TEMBALANG SEMARANG Sri Mulyati; Emi Murniati; Jeffri Ardiyanto; Gatot Murti Wibowo
Jurnal LINK Vol 15, No 1 (2019): MEI 2019
Publisher : Pusat Penelitian dan Pengabdian kepada Masyarakat, Poltekkes Kemenkes Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1214.626 KB) | DOI: 10.31983/link.v15i1.4109

Abstract

Kelurahan Meteseh adalah salah satu Kelurahan yang berada di wilayah Kecamatan Tembalang Semarang. Secara demografis memiliki banyak potensi, diantaranya bidang peternakan sapi, perikanan, pertanian dan kewirausahaan yang dapat dioptimalkan dalam usaha untuk pembangunan Kelurahan untuk meningkatkan perekonomian masyarakat Kelurahan tersebut. Masyarakat memandang masalah sampah menjadi hal yang patut diprioritaskan mengingat pengelolaan sampah melalui bank sampah dapat berimbas baik secara ekonomi, kesehatan maupun lingkungan pada masyarakat sekitar. Salah satunya adalah Prodi D-IV Teknik Radiologi Jurusan Teknik Radiodiagnostik Dan Radioterapi Politeknik Kesehatan Kemenkes Semarang yang memiliki tanggung jawab dalam pelaksanaan tri Dharma Perguruan Tinggi dalam wujud pengabdian kepada masyarakat.Kegiatan ini merupakan stimulan yang dilakukan melalui pemberdayaan kepada masyarakat melalui pembentukan dan pendampingan pentingnya Bank Sampah sebagai salah satu wadah untuk pengelolaan sampah yaitu dengan terbentuknya Bank Sampah Mulia sejahtera di Kelurahan Meteseh Kecamatan Tembalang Kota Semarang. Dengan slogan mengubah sampah menjadi Berkah. Harapan kami, nantinya kegiatan ini dapat ditindaklanjuti oleh warga untuk pemilahan dan pengolahan sampah. Sehingga, dapat terwujud masyarakat yang bersih, sehat dan sejahtera. 
Informasi Anatomi MSCT Sinus Paranasal pada Suspek Sinusitis dengan Variasi Rekonstruksi Algorithma Sri Mulyati; Gatot Murti Wibowo; Jeffri Ardiyanto; Sylvia Ishlahul Ummah
Jurnal Imejing Diagnostik (JImeD) Vol 10, No 1: JANUARY 2024
Publisher : Poltekkes Kemenkes Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31983/jimed.v10i1.11075

Abstract

Background: The standard operating procedure with the bone window technique and bone reconstruction algorithm is referred to the MSCT protocol for paranasal sinuses in Hospital. However, the majority of radiologists select a protocol that implements the algorithm reconstruction, which is still trial and error without an organized protocol development study. There is a chance that the accuracy of the MSCT SPN and the quality of the picture data may become crucial problems. This study set out to assess and examine the algorithmic reconstruction method that can yield more accurate SPN anatomical data in sinusitis suspects.Methods: A quasi-experimental technique was taken in conducting the research. Three filters (bone, boneplus, and edge) of the reconstruction method were used to get thirty SPN images from ten patients. The images were  assessed by the two expert radiologist.Results: The results of non-parametric was obtained based on statistical tests using the  Friedman test ρ-value  of anatomy, namely 0.00 less than 0.05. These results indicate that H0 is rejected and Ha is accepted,  meaning that there are differences in anatomical information between variations of bone, boneplus, and  edge reconstruction algorithms on the MSCT scan examination of the paranasal sinuses with sinusitis suspect. The Friedman test results using the mean rank values of each anatomy show that Boneplus is  superior in terms of visualizing anatomy. The Friedman test's mean rank value of the entire anatomy  yielded the result that the boneplus reconstruction algorithm is superior to the bone and edge reconstruction algorithm in displaying anatomical information on the MSCT scan of the paranasal  sinuses with sinusitis suspect.Conclusions: Based on value mean rank For each Friedman test anatomy and the results of the frequency distribution, variations of the bone plus reconstruction algorithm are more optimal in displaying anatomical information on the MSCT Scan of the paranasal sinuses compared with the edge and bone reconstruction algorithms.