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All Journal CCIT (Creative Communication and Innovative Technology) Journal Jurnal Abdimas Imigrasi (JaIM)
Fathya, Vita Nurul
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Humanities Computer Science & IT Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences

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ANALYSIS OF MASS SOCIALIZATION OF THE STATE POLYTECHNIC OF IMMIGRATION: A CASE STUDY OF CLASS I IMMIGRATION OFFICE TPI BANDA ACEH Fathya, Vita Nurul; Mastur, Anida Sri Rahayu; Gibran, Atsil Syah
Jurnal Abdimas Imigrasi Vol 4 No 2 (2023): Jurnal Abdimas Imigrasi
Publisher : Polteknik Imigrasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52617/jaim.v4i2.496

Abstract

Tulisan ini mendeskripsikan terhadap langkah sosialisasi Politeknik Imigrasi oleh Kantor Imigrasi Kelas I TPI Banda Aceh merupakan kegiatan yang bertujuan untuk memperkenalkan dan memberikan pemahaman mengenai Politeknik Imigrasi kepada masyarakat, khususnya para siswa. Kegiatan sosialisasi ini dilakukan melalui pendekatan sosialisasi massal melalui radio Meugah Fm. Melalui sosialisasi ini, diharapkan masyarakat, khususnya para siswa, dapat memahami pentingnya Politeknik Imigrasi dalam mengembangkan sumber daya manusia di bidang keimigrasian. Selain itu, sosialisasi ini juga bertujuan untuk meningkatkan minat para siswa untuk melanjutkan pendidikan di Politeknik Imigrasi. Dengan demikian, diharapkan Politeknik Imigrasi dapat menjadi pilihan yang menarik bagi para siswa yang ingin mengembangkan karirnya di bidang keimigrasian.
Systematic Literature Review: The Use of the K-Nearest Neighbor Algorithm in Data Classification for Government Policy Optimization Boru Manik, Maria Intan Parsaulian; Fathya, Vita Nurul; Wilonotomo, Wilonotomo
CCIT (Creative Communication and Innovative Technology) Journal Vol 19 No 1 (2026): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/ccit.v19i1.3835

Abstract

Along with the rapid advancement of technology and the progress of the digital era, the volume of data across various sectors has significantly increased, making it necessary to process this data to support policy optimization. Data processing is essential for simplifying complex data by grouping it according to specific characteristics. K-Nearest Neighbor (KNN) is a widely used classification algorithm in data mining implementation, applying the principle of class determination based on the proximity between data points, calculated using the Euclidean distance metric. In the governmental sector, this algorithm has been utilized to improve the efficiency of public policies and data-driven decision support systems. This study employs a Systematic Literature Review (SLR) to examine the use of the K-Nearest Neighbor algorithm in previous research for classifying government-related data as a foundation for formulating more effective and efficient policies. The information is gathered by collecting references from relevant journals and studies to provide a detailed understanding of the effectiveness of data processing as a means for optimizing government policies and offering well-targeted decision-making recommendations.
Co-Authors Akbar, Rasona Sunara Amrulloh, Adikara Akbar Boru Manik, Maria Intan Parsaulian Gibran, Atsil Syah Mastur, Anida Sri Rahayu