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

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Systematic Literature Review : Penerapan Metode Branch and Bound dalam Optimalisasi Produksi Sherly Putri Revika; Jamiah Nurhakiki; Bulan Naysabilla; 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.v3i3.596

Abstract

This study presents a Systematic Literature Review (SLR) focusing on the application of the Branch and Bound (B&B) method in production optimization. In modern industry, achieving operational efficiency and profitability is essential, yet optimization often yields fractional solutions that are unrealistic for indivisible entities. The Branch and Bound method, as part of Integer Programming, has proven effective in addressing these constraints by converting fractional solutions into optimal integer values. This SLR analyzed 12 scientific articles published between 2016 and 2024, sourced from databases such as Google Scholar, Scopus, and SINTA. The analysis reveals that B&B is widely utilized to maximize production profit across various sectors, including spring beds, woven fabrics, bread, and furniture, often formulated as Integer Linear Programming (ILP) problems. Furthermore, this method is also applied to minimize production time and determine the shortest routes. Overall, B&B is a flexible and efficient tool that assists companies in managing resources and achieving maximum profit with realistic integer solutions.
Studi Kepustakaan: Pengenalan 4 Algoritma Pada Pembelajaran Deep Learning Beserta Implikasinya Jamiah Nurhakiki; 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.v2i1.598

Abstract

In the past few years, deep learning has been very popular among IT users. Deep learning is one of the machine learning parts of artificial intelligence (AI). Deep learning has several algorithms in it. So in this paper, we will explain basically about four algorithms owned by deep learning, namely: CNN, RNN, LSTM and SOM along with an explanation of the application of the algorithm. With the explanation, it is hoped that some IT users can understand deep learning algorithms and their implications for work or applications.
Co-Authors Bulan Naysabilla Sherly Putri Revika Siti Salamah Br Ginting yahfizham yahfizham