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All Journal Pendekar: Jurnal Pendidikan Berkarakter Bilangan: Jurnal Ilmiah Matematika, Kebumian dan Angkasa
Marshanda Suraya
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Arts Astronomy Education Mathematics Social Sciences

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Studi Literatur: Penerapan Persoalan Transportasi dalam Biaya Pengangkutan Barang di Pabrik-Pabrik yang Ada di Indonesia Icha Amelia; Fakhrezi, Ilham Achmad; Marshanda Suraya; Siti Salamah Br. Ginting
Bilangan : Jurnal Ilmiah Matematika, Kebumian dan Angkasa Vol. 3 No. 3 (2025): Juni: Bilangan : Jurnal Ilmiah Matematika, Kebumian dan Angkasa
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/bilangan.v3i3.601

Abstract

This study examines the application of transportation problems in an effort to minimize goods transportation costs in various factories in Indonesia, using a Systematic Literature Review (SLR) approach. Transportation problems, as a part of operations research, focus on optimizing distribution costs from sources to destinations. In the industrial context, good planning and strategy are essential to save transportation costs and increase profits. This study analyzes ten relevant journals published between 2017 and 2025, exploring various methods such as the transportation model, North West Corner, Stepping Stone, and Vogel's Approximation Method (VAM), including its modification (MVAM), to achieve efficiency in logistics distribution. The results of the study indicate that the application of these methods significantly contributes to reducing operational costs, accelerating distribution processes, and increasing overall logistics effectiveness in the Indonesian manufacturing sector.
Algoritma Pemograman : Kunci Efisiensi Dalam Pengelolaan Data Besar Marshanda Suraya; Yahfizham Yahfizham
Pendekar : Jurnal Pendidikan Berkarakter Vol. 2 No. 1 (2024): Februari : Jurnal Pendidikan Berkarakter
Publisher : LPPM Politeknik Pratama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/pendekar.v2i1.601

Abstract

This research aims to explain the key role of programming algorithms in improving the efficiency of big data processing. This abstract will discuss the methods used in the research, the results obtained, and the implications of the findings. This research uses an analytical and experimental approach to study various types of programming algorithms used in big data processing. Data collection methods involve literature review and experiments with representative datasets. The results show that selecting the right programming algorithm can significantly improve the efficiency of big data processing. Efficient sorting algorithms, such as merge sort and quick sort, can sort data with a time complexity of O(n log n). In addition, machine learning algorithms have also proven effective in analyzing and making decisions based on big data. The implications of these findings are that the use of the right programming algorithms can optimize big data processing in various fields, such as business, education, and research. By implementing efficient programming algorithms, organizations can save time, resources, and improve decision-making quality.
Co-Authors Fakhrezi, Ilham Achmad Icha Amelia Siti Salamah Br Ginting yahfizham yahfizham