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All Journal JURIKOM (Jurnal Riset Komputer) Jurnal Pendidikan Non formal Jurnal Pengabdian Masyarakat ISEI
Putri, Rizki Amelia
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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Realitas Tantangan Tenaga Kerja Wanita di Sektor Informal: Kontribusi, Tantangan dan Dampak yang Terjadi Putri, Rizki Amelia; Wati, Evy Ratna Kartika; Nurrizalia, Mega; Anggelia, Ririn Desmita; Syakirin, Ahmad; Syawalludin, Syawalludin
Jurnal Pendidikan Non formal Vol. 1 No. 3 (2024): March
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/jpn.v1i3.367

Abstract

Penelitian ini bertujuan untuk mengetahui dan mengungkapkan realitas yang terjadi terhadap tenaga kerja wanita yang ada di sektor informal. Studi ini juga dimaksudkan untuk menyelidiki masalah apa saja yang sering dihadapi oleh pekerja wanita dalam sektor yang tidak terorganisir. Pendekatan artikel ini menggunakan pendekatan penelitian deskriptif dan kualitatif yang lebih terfokus pada permasalahan atas dasar fakta. Sektor informal ini merupakan salah satu sektor ekonomi yang tidak terstruktur serta tidak terdaftar secara resmi oleh pemerintah. Sektor informal biasanya ditandai dengan ciri-ciri seperti usaha berskala kecil milik pribadi dengan modal terbatas, tenaga kerja yang kurang terampil atau memiliki Tingkat Pendidikan yang rendah, tidak memiliki jaminan sosial dan perlindungan tenaga kerja, dan produktifitas rendah karena keterbatasan modal, teknologi dan keterampilan. Realitas tantangan yang sering diterima oleh tenaga kerja wanita di sektor informal contohnya seperti diskriminasi gender, eksploitasi pekerja, dan adanya keterbatasan terhadap layanan publik (layanan kesehatan, jaminan sosial dan tunjangan pendidikan).
Pelatihan Penggunaan Sistem Informasi Akademik Berbasis Website (Profile Sekolah) Bakaruddin; Rahmi, Rahmiati; Putri, Rizki Amelia
Jurnal Pengabdian Masyarakat Isei Vol. 1 No. 2 (2023): Jurnal Pengabdian Masyarakat Isei
Publisher : ISEI Cabang Pekanbaru, Koordinator Provinsi Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46750/abdimasisei.v1i2.193

Abstract

Information technology has become an important part of all sectors, including the development of education. The school profile website is a new form of school identity in the current information era, so that information about the school can be easily found. By implementing a website application, it can help school administrators improve their abilities in the field of technology and information. This training method is felt to be very effective in delivering material, and then the administrators or school staff carry out the practice according to the directions.
Penerapan Algoritma K-Means Clustering untuk Segmentasi Kepadatan Penduduk Berbasis GIS Putri, Rizki Amelia; Safwandi, Safwandi; Fitri, Zahratul
JURIKOM (Jurnal Riset Komputer) Vol 12, No 3 (2025): Juni 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i3.8668

Abstract

This study aims to develop a clustering system using the K-means algorithm to analyze demographic data of sub-districts from 2020 to 2023. The system is designed to cluster sub-districts based on variables such as population size, population percentage, population density, and gender ratio. The clustering results reveal different grouping patterns each year, reflecting the dynamics of demographic data over time. Evaluation using the Davies-Bouldin Index (DBI) indicates that the clustering results are of reasonably good quality, with DBI values of 1.1492 in 2020, 0.6859 in 2021, 1.2470 in 2022, and 0.6805 in 2023. The best DBI value was recorded in 2023 at 0.6805, demonstrating that the clustering results in that year were the most optimal compared to other years. The system also facilitates Users with interactive map visualizations, supporting better data analysis and decision-making processes. This research is expected to contribute to the management of demographic data and support more accurate data-driven policy-making.
Penerapan Algoritma K-Means Clustering untuk Segmentasi Kepadatan Penduduk Berbasis GIS Putri, Rizki Amelia; Safwandi, Safwandi; Fitri, Zahratul
JURNAL RISET KOMPUTER (JURIKOM) Vol. 12 No. 3 (2025): Juni 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i3.8668

Abstract

This study aims to develop a clustering system using the K-means algorithm to analyze demographic data of sub-districts from 2020 to 2023. The system is designed to cluster sub-districts based on variables such as population size, population percentage, population density, and gender ratio. The clustering results reveal different grouping patterns each year, reflecting the dynamics of demographic data over time. Evaluation using the Davies-Bouldin Index (DBI) indicates that the clustering results are of reasonably good quality, with DBI values of 1.1492 in 2020, 0.6859 in 2021, 1.2470 in 2022, and 0.6805 in 2023. The best DBI value was recorded in 2023 at 0.6805, demonstrating that the clustering results in that year were the most optimal compared to other years. The system also facilitates Users with interactive map visualizations, supporting better data analysis and decision-making processes. This research is expected to contribute to the management of demographic data and support more accurate data-driven policy-making.
Co-Authors Anggelia, Ririn Desmita Bakaruddin MEGA NURRIZALIA, MEGA Rahmi, Rahmiati Safwandi Safwandi, Safwandi Syakirin, Ahmad Syawalludin, Syawalludin Wati, Evy Ratna Kartika Zahratul Fitri, Zahratul