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All Journal MILANG Journal of Mathematics and Its Applications
Elis Khatizah
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Mathematics

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KONSEP MATEMATIKA DI BALIK JARINGAN SARAF TIRUAN SEBAGAI FONDASI KECERDASAN BUATAN Elis Khatizah
MILANG Journal of Mathematics and Its Applications Vol. 20 No. 2 (2024): MILANG Journal of Mathematics and Its Applications
Publisher : School of Data Science, Mathematics and Informatics, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/milang.20.2.145-156

Abstract

Kecerdasan buatan (AI) telah menjadi salah satu teknologi yang berpengaruh di berbagai sektor, mulai dari kesehatan hingga industri otomotif. Di balik kemajuan ini, terdapat dasar matematika yang memainkan peran penting, khususnya dalam proses optimasi dan pembelajaran mesin, dua elemen utama pendukung kinerja AI. Artikel ini bertujuan untuk mengulas konsep dasar matematika, khususnya kalkulus turunan, yang berperan dalam pembelajaran jaringan saraf tiruan sebagai bagian dari konstruksi model AI. Dengan penjelasan teori dan contoh praktis, artikel ini memaparkan kontribusi matematika dalam mendasari dan membentuk model AI. Melalui pemahaman ini, diharapkan pembaca tidak hanya melihat matematika sebagai teori semata, tetapi juga sebagai alat esensial untuk membangun teknologi masa depan.
APPLICATION OF A GENETIC ALGORITHM FOR SOLVING TRAVELING SALESMAN PROBLEM IN ORGANIC PORRIDGE DISTRIBUTION Hauralia Rahmadanti Finan; Mochamad Tito Julianto; Elis Khatizah
MILANG Journal of Mathematics and Its Applications Vol. 21 No. 2 (2025): MILANG Journal of Mathematics and Its Applications
Publisher : School of Data Science, Mathematics and Informatics, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/milang.21.2.101-116

Abstract

This study focuses on determining an optimal distribution route for organic porridge products produced by a company and delivered to multiple outlets. Each outlet is visited exactly once, and the delivery process starts and ends at the same outlet. A total of 44 outlets are considered, which are initially divided into nine distribution routes. To improve distribution efficiency, this study proposes reorganizing the outlets into only three distribution routes. Each route formulation is modeled as a Traveling Salesman Problem (TSP). The optimization of the three TSP cases is carried out using a Genetic Algorithm (GA). In the GA implementation, the order of outlets along a route is encoded as a chromosome consisting of a sequence of genes. The fitness function is defined based on the total travel distance, where a smaller value indicates a better solution. The results show that increasing the number of iterations and the size of population, which is the number of candidate routes considered at each step, can reduce the total travel distance up to a certain point. The exact routes and their sequence of outlets can be visualized in a map depicting each of the three optimized paths. Keywords: Genetic Algorithm, distribution routing, total distance, Traveling Salesman Problem
Co-Authors Hauralia Rahmadanti Finan Mochamad Tito Julianto