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Equiva
Published by Institut Teknologi Kalimantan
ISSN : -     EISSN : 30466792     DOI : -
Core Subject : Science, Education,
Computer Science & IT Mathematics
Equiva Journal merupakan jurnal yang diterbitkan oleh Jurusan Matematika dan Teknologi Informasi - Institut Teknologi Kalimantan. Equiva Journal dirintis sejak Tahun 2022 dan terbit dua kali dalam setahun dengan setiap terbitan berisi 8 artikel. Semua artikel yang terbit di Equiva Journal adalah milik Equiva Journal yang tidak boleh diterbitkan ulang di jurnal lain. Equiva Journal bersifat open access, sehingga seluruh artikel yang dibagi-bagikan atau disebar-luaskan harap merujuk kembali ke URL Equiva Journal.
Arjuna Subject : Matematika - Matematika Terapan
Articles 6 Documents
 1 
Search results for , issue "Vol 3 No 2 (2025)" : 6 Documents clear
Prediksi Harga Emas Antam menggunakan Metode Regresi Linear: Indonesia Yulianti; Bihablila; Rahmah, Siti; Lissa, Hermei
Equiva Journal Vol 3 No 2 (2025)
Publisher : Jurusan Matematika dan Teknologi Informasi

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Abstract

Gold is one of the most popular and considered safe investment instruments due to its long-term value stability. However, gold prices still experience fluctuations influenced by various economic and geopolitical factors. Therefore, the ability to predict gold prices is crucial for investors, traders, and jewelry industry players. This study aims to predict the selling price of Antam gold using a simple linear regression method based on historical data of buying and selling prices during the period of March 31 to April 7, 2025. The analysis shows a positive linear relationship between buying and selling prices, with the regression equation Y = 8.660,47 + 0,97X . The model yields predictions that closely approximate actual values, with a Mean Absolute Deviation (MAD) of Rp 2,328.91 and an accuracy rate of 99.86%. These findings indicate that simple linear regression can be an effective and accurate tool for short-term gold price forecasting and can serve as a basis for investment decision-making.
Solusi Optimal Transportasi Dengan Least-Looping Stepping-Stone-based ASM (LS-ASM): Optimal Transportation Solution with Least-Looping Stepping-Stone-based ASM (LS-ASM) Meylan; Affandi, Pardi
Equiva Journal Vol 3 No 2 (2025)
Publisher : Jurusan Matematika dan Teknologi Informasi

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Abstract

The Least-Looping Stepping-Stone-based ASM (LS-ASM) method is a transportation problem-solving approach aimed at achieving an optimal solution more efficiently than the classical method. It begins with row and column reductions to simplify the cost matrix, followed by stepwise allocation based on selecting the most advantageous cells, and then uses the formation of closed loops to evaluate cost changes and identify potential improvements to the current solution. Through this systematic process, LS-ASM is able to minimize the number of iterations required, using cost change values for optimality checks to ensure that the final allocation structure consistently meets source capacities and destination demands, ultimately resulting in a stable, directed, and optimal solution for minimizing distribution costs.
Penyelesaian Masalah Transportasi menggunakan Transportation Optimality Complementary Method (Tocm) Dengan Zero Point Minimum Method (Zpmm) Dan Uji Optimalitas Midofied Distribution (Modi): Transportation Problem Solving Using the Transportation Optimality Complementary Method (TOCM) with the Zero Point Minimum Method (ZPMM) and Modified Distribution Optimality Test (MODI) Hikmawati, Lia; Affandi, Pardi
Equiva Journal Vol 3 No 2 (2025)
Publisher : Jurusan Matematika dan Teknologi Informasi

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Abstract

The transportation problem is a special type of linear programming that aims to minimize the total distribution cost from several sources to multiple destinations while satisfying supply and demand constraints. This study applies a combination of the Transportation Optimality Complementary Method (TOCM) and the Zero Point Minimum Method (ZPMM) to obtain an efficient initial solution, followed by an optimality test using the Modified Distribution Method (MODI). Three types of cases were analyzed: balanced transportation, excess supply (supply > demand), and excess demand (demand > supply). The results indicate that the TOCM–ZPMM method can produce an initial solution that is very close to the optimal result, making the optimization phase with the MODI method require fewer iterations. Therefore, this combination improves computational efficiency and provides accurate solutions, making it an effective alternative for solving transportation problems in logistics and distribution systems.
Penyelesaian Model Masalah Transportasi menggunakan Maximum Range Method (MRM) dan AH Method (AHM) Faturrahman, Muhammad; Affandi, Pardi
Equiva Journal Vol 3 No 2 (2025)
Publisher : Jurusan Matematika dan Teknologi Informasi

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Abstract

Transportation models are a specific type of linear programming used to determine optimal distribution patterns by considering the balance between total supply and total demand. Through mathematical formulations involving transportation costs C_{ij}, distribution allocations X_{ij}, supply a_i, and demand b_j, these models provide an effective analytical framework for evaluating the efficiency of a distribution system. This study applies two solution methods, namely the Maximum Range Method (MRM) and the AH Method (AHM), to a balanced transportation model without linking it to a specific industrial context. The MRM calculation process is carried out by identifying the largest cost difference in each row and column to determine the allocation location that has the potential to provide the highest savings. On the other hand, AHM works as a direct optimization method by selecting the smallest global cost at each stage of calculation. The results of the study show that MRM produces a total cost of 2070, which is lower than AHM, which produces a total cost of 2100. This difference indicates that MRM is more efficient for the transportation data model in this study. These two methods provide different computational perspectives but can complement each other in the analysis of transportation problem solving based on cost optimization.
Penerapan Metode SS (Sheethalakshmy–Srinivasan) dalam Optimasi Masalah Transportasi untuk Meminimalkan Biaya Distribusi Yazid Halim, Ahmad; Affandi, Pardi
Equiva Journal Vol 3 No 2 (2025)
Publisher : Jurusan Matematika dan Teknologi Informasi

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Abstract

The transportation problem is one of the important problems in operations research related to the distribution of goods from several sources to several destinations at minimum cost. This problem aims to determine the number of goods that must be shipped from each source to each destination so that all demand is met with the lowest possible total distribution cost. This study applies the SS Method (Sheethalakshmy–Srinivasan) as a direct approach to solving transportation problems without the need to determine a feasible initial solution. The SS Method offers systematic steps through row and column reduction processes and cost reduction calculation to obtain optimal solutions for both balanced and unbalanced transportation cases. The results of the application of this method show that the SS Method is able to provide optimal solutions efficiently with a shorter calculation time compared to conventional methods such as North West Corner, Least Cost, and Vogel's Approximation. Thus, the SS Method can be used as an effective alternative in optimizing distribution costs in modern logistics systems.
Masalah Transportasi menggunakan Kombinasi Distribusi Normal dengan Root Mean Square (RMS) untuk Solusi Layak Awal dan Sirisha-Viola Method (SVM) untuk Solusi Optimal Saadah, Miftahus; Affandi, Pardi
Equiva Journal Vol 3 No 2 (2025)
Publisher : Jurusan Matematika dan Teknologi Informasi

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Abstract

The objective of this research is to find the best logistics solution for various purposes at minimal cost. The development of a new initial feasible solution (IBFS) algorithm is the first step toward finding the optimal solution. This new method for initial feasible solutions reduces the number of iterations and produces the best solution for transportation problems at an early stage. The literature review covers various IBFS methods. The new IBFS was discovered using statistical techniques such as normal distribution and root mean square techniques. A transportation problem is converted into a normal distribution, and the penalty is determined using the root mean square method. The normal distribution value can be calculated using Excel Solver. In the second step, a step-by-step method is used to find the optimal solution. Numerical calculations are used to calculate the research results and compared with the Sirisha-Viola method in determining a feasible optimal solution.

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