Article Per Year (5 Year)
p-Index From 2020 - 2025
0.751
P-Index
This Author published in this journals
All Journal Cakrawala: Jurnal Pengabdian Masyarakat Global Inovasi Kesehatan Global Modem : Jurnal Informatika dan Sains Teknologi Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika
Purnamasari Purnamasari
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Medicine & Pharmacology Nursing Public Health Social Sciences

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
Analisis K-Means Clustering pada Sistem Presensi Mobile dengan Fitur GPS Radius dan Foto Selfie untuk Pegawai Non-PNS di Puskesmas Kosambi Adih Adih; Wahyu Aji Dwi Pangestu; Muhamad Fauzi Akbar; Purnamasari Purnamasari; Saprudin Saprudin
Modem : Jurnal Informatika dan Sains Teknologi. Vol. 3 No. 1 (2025): Januari : Modem : Jurnal Informatika dan Sains Teknologi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/modem.v3i1.324

Abstract

Puskesmas Kosambi employs Non-PNS staff whose discipline, particularly regarding attendance and work location, needs to be evaluated. The previous manual attendance system was found to be ineffective in monitoring staff discipline. This study aims to develop a mobile-based attendance system equipped with GPS radius and selfie photo features to improve the accuracy and management of attendance. The GPS radius feature ensures that staff can only clock in within the designated area, such as the Puskesmas area, while the selfie photo feature verifies the identity of the staff member clocking in. This study involved 24 Non-PNS staff members and used the K-Means Clustering algorithm to group staff based on their discipline levels. The results showed that the system was effective in improving staff discipline, with 11 employees categorized as highly disciplined, 10 as moderately disciplined, and 3 as lowly disciplined. The implications of this study suggest that the implementation of a mobile-based attendance system can improve attendance monitoring and enhance work discipline at Puskesmas Kosambi.
Sosialisasi dan Edukasi Penggunaan Aplikasi Presensi Berbasis Mobile Bagi Pegawai Non PNS di Lingkungan Puskesmas Kosambi untuk Meningkatkan Kedisiplinan Kerja Adih Adih; Bagas Syahputra; Obay Sobarnas; Farlin Wabula; Valentino Liu; Ade Irma Nizar; Sukron Anggara; Muhammad Azhar Prasetyo; Fashya Mulya; Purnamasari Purnamasari; Abdullah Muhajir
Cakrawala: Jurnal Pengabdian Masyarakat Global Vol. 3 No. 4 (2024): Cakrawala: Jurnal Pengabdian Masyarakat Global
Publisher : Universitas 45 Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30640/cakrawala.v3i4.3332

Abstract

This community service activity aims to improve the discipline and efficiency of non-civil servant employees at Kosambi Public Health Center (Puskesmas) through the implementation of a mobile attendance application. Currently, the manual attendance system used at Kosambi Puskesmas has numerous limitations, such as susceptibility to record errors, lack of transparency, and inability to monitor attendance in real time. To address this, socialization and educational activities were conducted on the use of the mobile attendance application, which is expected to enhance employees’ understanding and encourage attendance discipline. The methods used in this activity include socialization, discussion, and hands-on training. The results indicate that implementing this application can help improve discipline and transparency in managing employee attendance and has the potential to enhance the quality of healthcare services provided to the community at Kosambi Puskesmas.
Literature Review : Penggunaan Machine Learning Berbasis SVM untuk Klasifikasi Penyakit Diabetes Adih Adih; Wahyu Aji Dwi Pangestu; Muhamad Fauzi Akbar; Purnamasari Purnamasari; Farlin Wabula; Ines Heidiani Ikasari
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 1 (2025): Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i1.616

Abstract

Diabetes is one of the diseases that poses a significant global health challenge, with a considerable impact on quality of life and mortality rates. This study examines the use of the Support Vector Machine (SVM) algorithm for diabetes classification through a literature review. SVM was chosen due to its ability to handle imbalanced and complex data. The aim of this study is to assess the effectiveness of SVM compared to other machine learning methods in detecting diabetes. The results of the literature review indicate that SVM achieves higher accuracy than other methods such as Naïve Bayes and Decision Tree, with some studies showing accuracy above 90%. This study is expected to provide deeper insights into the development of machine learning-based diagnostic systems for diabetes.
Anastesi Inhalasi pada Tikus (Rattus Norvegicus) Menggunakan Eter dan Kloroform Haryanto Haryanto; Alfani Zahrah Suci; Ahni Elena Aprilia; Ainun Mutia Putri; Sahratul Wilda; Harianti Harianti; Purnamasari Purnamasari
Inovasi Kesehatan Global Vol. 2 No. 3 (2025): Agustus : Inovasi Kesehatan Global
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/ikg.v2i3.2228

Abstract

This study aimed to compare the inhalation anesthetic profiles of ether and chloroform in white rats (Rattus norvegicus) using a modern pharmacological approach. Five healthy male rats (8–10 weeks old) were randomly divided into three groups: ether, chloroform, and control (ketoprofen). The main parameters observed were the onset time of loss of the righting reflex and the duration until its recovery. In theory, ether works by enhancing GABAergic transmission and inhibiting NMDA channels, thus having a slow but stable induction effect (IKAPI, 2009; Arqom, 2023). In contrast, chloroform works by stabilizing the neuronal membrane through activation of the K₂P TREK-1 channel and inhibition of Na⁺/Ca²⁺ currents, resulting in rapid induction with a short duration (Pavel et al., 2020). The experimental results support this theory: chloroform showed an average onset of 167.83 seconds and an anesthesia duration of 84.67 seconds, while ether had a slower onset (307.17 seconds) but a longer duration (169.33 seconds). The difference between the two was statistically significant (ANOVA, p<0.05). The coefficient of variation for chloroform was nearly four times higher than that of ether, indicating that ether provides a more consistent anesthetic effect across individuals. These findings are consistent with previous studies, such as Fathiyah & Anretha's (2023) report on the variability of chloroform effects and the results of in vivo amethyst anesthesia studies (Aprira, 2022; Genta et al., 2021). Overall, ether is more suitable for medium-term procedures requiring stable anesthesia, while chloroform is suitable for short interventions requiring rapid induction. This study emphasizes the importance of controlled inhalation environments, adequate sample sizes, and chamber standardization to enhance the external validity of the results.
Co-Authors Abdullah Muhajir Ade Irma Nizar Adih Adih Ahni Elena Aprilia Ainun Mutia Putri Alfani Zahrah Suci Bagas Syahputra Farlin Wabula Fashya Mulya HARIANTI Harianti Haryanto Haryanto Ines Heidiani Ikasari Muhamad Fauzi Akbar Muhammad Azhar Prasetyo Obay Sobarnas Sahratul Wilda Saprudin Saprudin Sukron Anggara Valentino Liu Wahyu Aji Dwi Pangestu