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All Journal Jurnal Matematika Journal of Natural Sciences and Mathematics Research MAJAMATH: Jurnal Matematika dan Pendidikan Matematika
Maulani, Alfi
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Education Materials Science & Nanotechnology Mathematics Physics

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Implementasi Algoritma Dijkstra Menggunakan Adjacency Matrix Ismawati, Iis; Maulani, Alfi
Jurnal Matematika Vol 14 No 1 (2024)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2024.v14.i01.p167

Abstract

Abstract: Dijkstra's algorithm is an algorithm that can support finding the fastest route by mapping alternative trajectories in finding travel routes. The aim of this research is to find alternative travel routes by implementing the Dijkstra Algorithm using the Adjacency Matrix to pick up goods from the PT Drop Center Warehouse. Cisoka Express Technology Jet. Survey data in the form of customer names and addresses from two sub-districts was used. The results obtained with the Dijkstra Algorithm using the adjacency matrix obtained 4 routes in searching for the shortest path to pick up goods in Cisoka sub-district with the first route totaling 5 points with a distance of 9.35 km, the second route totaling 5 points with a distance of 9 km, the third route totaling 3 points with a distance of 3.95 km and the fourth route consists of 2 points with a distance of 3.6 km. and for Solear sub-district there are 3 routes, the first route is 7 points 14.9 km away, the second route is 9 points 14.72 km away and the third route is 2 points 5.85 km away. . Keywords: Dijkstra's Algorithm, Matrix, Shortest Path
American index exchange movement against IDX stochastic Flavianus, Muhammad; Maulani, Alfi
Journal of Natural Sciences and Mathematics Research Vol. 11 No. 1 (2025): June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/jnsmr.v11i1.18164

Abstract

A giant warehouse full of countless opportunities forms the foundation of this study, which aims to conduct stochastic modeling of the impact of the movement of the American stock index on the IDX (Indonesia Stock Exchange). This research discusses and emphasizes how the movement of the American stock index affects changes in the IDX over a certain period of time using a quantitative approach. The study employs a Hidden Markov Model (HMM) to identify latent market states. It utilizes the Viterbi method to determine the most probable sequence of state transitions based on the observed data. The model was trained using historical movements of the NASDAQ, NYSE, and DOW JONES indices, facilitating the discovery of significant trends in IDX changes. The research results show a trend in the movement of the IDX based on the movement of the American indices NASDAQ, NYSE, and DOW JONES, as follows: Bullish, bearish, bullish, bearish when NASDAQ is observed at 1, 2, 5, 6, and 8; NYSE is observed at 1, 3, 9, 11, and 15; and DOW JONES is observed at 1, 3, 4, 7, 9, 10, 11, 12, 13, 15, and 16. Bearish, bullish, bearish, bullish when NASDAQ is observed at 3, 9, 11, and 15; NYSE is observed at 2, 5, 6, and 8; and DOW JONES is observed at 2, 5, 6, 8, and 14. Bearish, bullish, bearish, bearish when NASDAQ is observed at 4, 12, and 16. Bullish, bearish, bullish, bullish when the NYSE is observed at 4 and 12. Bullish, bearish, bearish, bullish when NASDAQ is observed at seven and when NYSE is observed at 10. Bearish, bullish, bullish, bearish when NASDAQ is observed at 10. Bearish, bearish, bullish, bearish when NASDAQ is observed at 13 and 14. Bullish, bullish, bearish, and bullish when the NYSE is observed at 13, 14, and 16. The analysis indicates that IDX trends generally fluctuate in line with major U.S. indices (NASDAQ, NYSE, DOW JONES). Notably, specific observations 4, 12, 13, 14, 16 reveal a stronger correlation: a bearish NASDAQ movement tends to align with a bearish IDX stochastic, whereas a bearish NYSE movement is more likely to trigger a bullish response in the IDX.
Bilangan Keterhubungan Pelangi pada Graf Korona Berlian dan Lintasan Maulani, Alfi
MAJAMATH: Jurnal Matematika dan Pendidikan Matematika Vol. 4 No. 2 (2021): Vol. 4 No. 2 September 2021
Publisher : Prodi Pendidikan matematika Universitas Islam Majapahit (UNIM), Mojokerto, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36815/majamath.v4i2.1297

Abstract

Banyaknya warna minimum yang diperlukan dalam pewarnaan busur-busur di H sehingga setiap pasang simpul dapat dihubungkan oleh suatu lintasan yang warnanya berbeda disebut bilangan keterhubungan pelangi dari suatu graf H yang dilambangkan rc(H). Operasi korona menghasilkan graf baru Brn korona Pm yang strukturnya mengambil n salinan dari P1,P2,...,Pn dari Pm dan 1 (satu) salinan dari graf Brn dengan n simpul kemudian menghubungkan simpul dari Brn ke setiap simpul di Pi. Penelitian yang terkait dengan Br4 dan Pm ini mengkaji tentang bilangan keterhubungan pelangi pada graf korona Br4 korona Pm.
Co-Authors Flavianus, Muhammad Ismawati, Iis