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All Journal Pendas : Jurnah Ilmiah Pendidikan Dasar
Vita Nurul Fathya
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PERAMALAN JUMLAH PERMOHONAN PASPOR : SYSTEMIC LITERATURE REVIEW Wibowo, Besar Tri; Vita Nurul Fathya; Okky Pratama Martadireja
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 10 No. 02 (2025): Volume 10, Nomor 02 Juni 2025 t
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v10i02.23499

Abstract

The mobility of society, influenced by globalization, continues to increase, with fewer limitations on travel distances. People around the world can travel to other countries easily and quickly. Cross-border movement requires a travel document in the form of a passport as an individual's identification when entering and leaving a country. The number of passport applications varies each year. Typically, public interest in obtaining a passport rises during certain seasons, such as the Hajj season or long holidays. To anticipate uncertainties in passport application numbers, this study aims to explore which forecasting methods can be used to predict the number of passport applications within a specific timeframe. This research employs a survey approach by reviewing scientific journals or articles published between 2020 and 2025. Through this study, we can identify the types of methods used in similar research. Based on the findings, the most commonly used approach is the Autoregressive Integrated Moving Average (ARIMA), while the approach with the highest research accuracy is the Fuzzy Time Series Model Cheng, achieving an accuracy of 99.55%.
SYSTEMATIC LITERATURE REVIEW: PENERAPAN K-MEANS CLUSTERING Albert Putra Pratama; Vita Nurul Fathya; Muhammad Fahrury Romdendine
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 10 No. 03 (2025): Volume 10 No. 03 September 2025
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v10i03.29785

Abstract

This study is a systematic literature review on the application of K-Means Clustering in various sectors using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach. The clustering technique, particularly K-Means, is widely used in big data analysis due to its simplicity and efficiency. Although this method is popular, the main challenges include determining the optimal number of clusters, handling outliers, and computational limitations when applied to large-scale data. This research analyzes sectors that apply K-Means Clustering, such as industry, education, healthcare, and finance. The findings of this study are expected to provide insights into the trends in the use of clustering methods and offer recommendations on the most suitable tools for applying clustering based on data characteristics .
Co-Authors Albert Putra Pratama Muhammad Fahrury Romdendine Okky Pratama Martadireja Wibowo, Besar Tri