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Journal : SKANIKA: Sistem Komputer dan Teknik Informatika

IMPLEMENTASI WEB FILTERING FIREWALL UNTUK KEAMANAN PADA JARINGAN INTERNET DI PONDOK PESANTREN AL HIDAYAH KEBUMEN Ma'mun, Ahmad Sukron; Muflih, Ghufron Zaida
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 8 No 1 (2025): Jurnal SKANIKA Januari 2025
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v8i1.3298

Abstract

In the digital era, unrestricted internet access can have both positive and negative impacts, particularly in educational settings such as Islamic boarding schools (pondok pesantren). This study aims to implement a web filtering firewall system based on Mikrotik RouterOS to enhance internet network security at Al Hidayah Islamic Boarding School in Kebumen. Utilizing the Mikrotik RB951Ui-2HnD device to manage network access and winbox for router configuration, this research applies a web proxy approach to restrict access to negative content such as pornography, online gambling, and online games, which may interfere with students' learning processes. The development process follows the Waterfall model, encompassing the stages of analysis, design, implementation, testing, and maintenance. Results from the implementation indicate that the system effectively blocks unwanted websites, thereby fostering a safer and more conducive internet environment for educational activities. This research can provide an effective solution in managing and controlling internet access at the Al Hidayah Islamic Boarding School, Kebumen.
PENGELOMPOKAN WILAYAH INDONESIA BERDASARKAN KOMPONEN INDEKS PEMBANGUNAN MANUSIA DENGAN PENDEKATAN ALGORITMA K-MEANS CLUSTERING Saputra, Nur Rukhan; Muflih, Ghufron Zaida
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 8 No 1 (2025): Jurnal SKANIKA Januari 2025
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v8i1.3318

Abstract

The Human Development Index (HDI) plays a crucial role in measuring the well-being of a region's population, offering a comprehensive perspective through various indicators, including economic factors such as Gross Domestic Product (GDP). This study focuses on clustering regions in Indonesia based on HDI components using the K-Means Clustering method. The clustering divides the regions into three groups: low, medium, and high clusters, considering dimensions of education, health, and standard of living. The data used includes indicators such as expected years of schooling, mean years of schooling, life expectancy, average monthly income, and per capita expenditure. The Davies-Bouldin Index (DBI) is employed as an evaluation method to measure the quality of cluster separation. The study reveals that K-Means successfully categorizes the regions into three clusters with a DBI value of 1.17, reflecting good cluster separation. This clustering provides valuable insights into the distribution of human development across Indonesia and is expected to assist policymakers in devising effective strategies to improve well-being in each identified cluster.