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All Journal Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal Ilmiah Dan Karya Mahasiswa Pandawa : Pusat Publikasi Hasil Pengabdian Masyarakat
Siti Muawwanah
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Other

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Sosialisasi Identitas Kependudukan Digital Dalam Meningkatkan Partisipasi Masyarakat Kota Samarinda Pada Revolusi Digital Muhammad Khumaidi Nursyarif; Muhamad Wahyu Tirta; Tri Wahyudi; Siti Patimah; Siti Muawwanah; Arbansyah Arbansyah
Pandawa : Pusat Publikasi Hasil Pengabdian Masyarakat Vol. 2 No. 1 (2024): Januari : Pandawa : Pusat Publikasi Hasil Pengabdian Masyarakat
Publisher : Asosiasi Riset Ilmu Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/pandawa.v2i1.426

Abstract

The Digital Revolution is driving the transformation of population administration in the city of Samarinda through the Integration of Digital Population Identity (IKD). This study evaluates the socialization strategies of IKD and their impact on community participation. Through collaboration in Kaltim Fest, hospitals, and campuses, the program focuses on the activation of IKD and engagement with relevant institutions. The enthusiasm of the community in participating in activities highlights awareness and acceptance of IKD. The research results provide a foundation for further development, strengthening the role of IKD in population services
Penerapan Metode AHP-TOPSIS Dalam Menentukan Mahasiswa Lulusan Terbaik Pada Prodi Keperawatan UMKT Berbasis Web Raenald Syaputra; Hamada Zein; Ari Ahmad Dhani; Bulan Suci Cahayawati; Faldy Alfareza Pambudi; Siti Muawwanah; Raihan Nabil; Bima Satria; Hery Kurniawan; Vito Junivan Rivaldo; Manda Rela Istiantoko
Jurnal Ilmiah Dan Karya Mahasiswa Vol. 2 No. 1 (2024): FEBRUARI : JURNAL ILMIAH DAN KARYA MAHASISWA
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jikma.v2i1.1407

Abstract

This study utilizes the AHP-TOPSIS method to determine the best graduating students in the nursing program. Evaluation criteria include GPA, duration of study, achievements, and final projects. The results indicate that GPA and achievements significantly influence the assessment of graduates. The use of the AHP-TOPSIS method demonstrates consistency, yet it's important to note that similar results don't always guarantee equivalence between the two methods. This study confirms the reliability of the method in evaluation, however, suggestions for future research include expanding the sample size and considering additional factors to enhance validity and reliability.
Model Optimasi SVM-GSBE dalam Menangani High Dimensional Data Stunting Kota Samarinda Siti Muawwanah; Taghfirul Azhima Yoga Siswa; Wawan Joko Pranoto
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 3 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i3.41545

Abstract

Stunting has become a widely discussed health issue in Indonesia, par-ticularly in Samarinda City, which recorded a prevalence of 12.7% in 2023, making it the highest in East Kalimantan Province. The use of data mining techniques becomes crucial in overcoming the challenges of high dimensional data, such as computational complexity, the risk of overfitting, and visualization difficulties. This study aims to enhance the accuracy of Support Vector Machine optimization models using Grid Search and Backward Elimination feature selection (SVM-GSBE) to handle high-dimensional data related to stunting in Samarinda City. The dataset used is sourced from Samarinda City Health Office in 2023, covering 26 community health centers with 21 attributes and a total of 150,466 records. The research methodology includes data collection, pre-processing, data partitioning using K-Fold Cross Validation, feature selection using Backward Elimination, and SVM model optimization with Grid Search. Features such as BB/U, ZS TB/U, ZS BB/U, ZS BB/TB, Height, and LiLA have proven to increase accuracy in stunting data classification. Evaluation results show that Grid Search successfully increased accuracy for Linear from 99.59% to 99.78%, Polynomial from 90.92% to 99.40%, RBF from 89.80% to 98.36%, and Sigmoid from 75.29% to 86.84%. This indicates that the SVM-GSBE model can effectively be used as a tool for early detection of stunting and to support health policies in Samarinda City.
Co-Authors Arbansyah Arbansyah Ari Ahmad Dhani Bima Satria Bulan Suci Cahayawati Faldy Alfareza Pambudi Hamada Zein Hery Kurniawan Manda Rela Istiantoko Muhamad Wahyu Tirta Muhammad Khumaidi Nursyarif Raenald Syaputra Raihan Nabil Siti Patimah Tagfirul Azima Yoga Siswa, Muspidar Mulyadi Tri Wahyudi Vito Junivan Rivaldo Wawan Joko Pranoto