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Operations Research: International Conference Series

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Published by Indonesian Operations Research Association

ISSN : 27231739 EISSN : 27220974 DOI : https://doi.org/10.47194/orics

Core Subject : Economy, Science, Education, Engineering,

Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics

Operations Research: International Conference Series (ORICS) is published 4 times a year and is the flagship journal of the Indonesian Operational Research Association (IORA). It is the aim of ORICS to present papers which cover the theory, practice, history or methodology of OR. However, since OR is primarily an applied science, it is a major objective of the journal to attract and publish accounts of good, practical case studies. Consequently, papers illustrating applications of OR to real problems are especially welcome. In real applications of OR: forecasting, inventory, investment, location, logistics, maintenance, marketing, packing, purchasing, production, project management, reliability and scheduling. In a wide variety of environments: community OR, education, energy, finance, government, health services, manufacturing industries, mining, sports, and transportation. In technical approaches: decision support systems, expert systems, heuristics, networks, mathematical programming, multicriteria decision methods, problems structuring methods, queues, and simulation.

Arjuna Subject : Umum - Umum

Articles 5 Documents

Search results for , issue "Vol. 3 No. 3 (2022): Operations Research International Conference Series (ORICS), September 2022" : 5 Documents clear

Implementation of Back Tracking Algorithm in The Scheduling of Mathematics Study Program Faculty of MIPA Unsoed Amariesta, Tiara; Wardani, Amelia Kusuma; Adila, Raisa Naura; Nurshiami, Siti Rahmah
Operations Research: International Conference Series Vol. 3 No. 3 (2022): Operations Research International Conference Series (ORICS), September 2022
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v3i3.129

The complicated case of scheduling courses at the Mathematics and Natural Sciences Faculty of Mathematics Study Program, Universitas Jenderal Soedirman, is a topic that is quite interesting to discuss and find a solution to using a mathematical method. In fact, manual course scheduling without a method is prone to scheduling errors such as class schedule clashes, clashes in the use of lecture rooms and so on, so a more efficient method of scheduling courses is needed. Scheduling lectures with the backtracking algorithm is a systematic and efficient method of scheduling lectures with influencing factors such as the number of courses, number of sessions, number of rooms, and lecture time. Algorithm backtracking is an algorithm based on Depth First Search to find solutions to problems more efficiently. The back tracking algorithm performs a systematic search for solutions to all possible solutions at each node based on recursive Depth First Search. Depth First Search is a search method that is carried out at one node in each level from the far left. If a solution has not been found, then the search continues on the right hand node. And so on until a solution is found or if you find a dead end it will backtrack to the previous position. If a solution is found, the search will stop even if there are nodes that have not been traced. The implementation of the backtracking algorithm pays close attention to the factors that become obstacles in scheduling courses. The course schedule function with the backtracking algorithm can meet every influencing factor such as the number of courses, rooms, classes, and lecture time so that scheduling lectures with this method is very helpful because the method used is more efficient and can avoid errors in scheduling.

Mean-Variance Investment Portfolio Optimization Model Without Risk-Free Assets in Jii70 Share Gusliana, Shindi Adha; Salih, Yasir
Operations Research: International Conference Series Vol. 3 No. 3 (2022): Operations Research International Conference Series (ORICS), September 2022
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v3i3.185

In investing, investors will try to limit all the risks in managing their investments. Investor strategies to minimize investment risk are diversification by forming investment portfolios, one of which is the Mean-Variance without risk-free assets. The calculation results will show the composition of the optimum portfolio return for each stock that forms the portfolio. Optimum portfolio obtained with wT = (0.39853, 0.25519, 0.13644, 0.09788, 0.11196) sequential weight composition for TLKM, KLBF, INCO, HRUM, and FILM stocks. The composition of this optimal portfolio return is ðœ 0.04 with a return of 0.00209 and a portfolio variance of 0.00015. The formation of this portfolio optimization model is expected to be additional literature in optimizing the investment portfolio with the Mean-Variance.

Application of Metaheuristic Algorithm for Solving Fully Fuzzy Linear Equations System Puspita Sari, Merysa; Pradjaningsih, Agustina; Ubaidillah, Firdaus
Operations Research: International Conference Series Vol. 3 No. 3 (2022): Operations Research International Conference Series (ORICS), September 2022
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v3i3.170

A linear equation is an equation in which each term contains a constant with a variable of degree one or single and can be described as a straight line in a Cartesian coordinate system. A Linear equations system is a collection of several linear equations. A system of linear equations whose coefficients and variables are fuzzy numbers is called a fully fuzzy linear equation system. This study aims to apply a metaheuristic algorithm to solve a system of fully fuzzy linear equations. The objective function used is the minimization objective function. At the same time, the metaheuristic algorithms used in this research are Particle Swarm Optimization (PSO), Firefly Algorithm (FA), and Cuckoo Search (CS). The input in this research is a fully fuzzy linear equation system matrix and parameters of the PSO, FA, and CS algorithms. The resulting output is the best objective function and the variable value of the fully fuzzy linear equations system. The work was compared for accuracy with the Gauss-Jordan elimination method from previous studies with the help of the Matlab programming language. The results obtained indicate that the Particle Swarm Optimization (PSO) algorithm is better at solving fully fuzzy linear equation systems than the Firefly Algorithm (FA) and Cuckoo Search (CS). This case can be seen from the value of the resulting objective function close to the value of the Gauss-Jordan elimination methodKeywords: Mathematics, investation

Performance Comparison of Covariance Function to Interpolate Unsampled Points with Simulation Data in Manado City Soleman, Claudya; Weku, Winsy; Salaki, Deiby
Operations Research: International Conference Series Vol. 3 No. 3 (2022): Operations Research International Conference Series (ORICS), September 2022
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v3i3.169

The covariance function measures the strength of statistical correlation as a function of distance. This follows Tobler's law which states that everything is usually related to all else but those which are near to each other are more related when compared to those that are further away. The correct weight of the basic covariance structure will produce the optimal kriging predictor. One interesting way to evaluate the strength of a kriging interpolation is to perform a simulation using a spatial structure. The simulation technique is executed in Manado City. The data is then applied to the variogram model using the spherical and matern covariance functions. The type of kriging method used in this simulation is ordinary kriging. The result shows that the suitable model to use is the matern model. Residual results from cross-validation show that the matern model has a lower biased estimation on both data. According to the RMSE and MAE criteria, the matern model outperforms the spherical model on data A and data B. The results of the interpolation are then visualized in the form of a map. Through this research, it can be concluded that the accuracy of the selection of the covariance function in the variogram model will provide a good estimate for the kriging method, and the most appropriate model for this case is the matern model.

Profit and Loss Report of DSH Meat Stalls in Panumbangan Market Zahra, Ami Emilia Putri; Subartini, Betty
Operations Research: International Conference Series Vol. 3 No. 3 (2022): Operations Research International Conference Series (ORICS), September 2022
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v3i3.186

DSH Meat Kiosk is a kiosk that sells one of the foodstuffs, namely Beef. This DSH Meat Stall has been established for more than 20 years. However, as long as the kiosk has been standing, the manager still finds it challenging to analyze profits from sales. Therefore, the Preparation of a Profit - Loss Financial Report is intended to assist traders in managing the profits generated. This report makes a financial analysis of November 2021 and February 2022. The method used in preparing this report is using primary data by collecting data in the form of interviews with kiosk owners regarding matters needed in preparing profit and loss reports such as assets held and owned, total income, operational costs and others. The results of this report show that sales in February 2022 decreased by 17.88% compared to November 2021. It is hoped that this report will help and make it easier to manage the profit generated and make decisions to make the best profit.

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Contact Email orics.iorajournal@gmail.com

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Editorial Address Jl. Merkuri Timur VI No. 1, RT. 007, RW. 004, Manjahlega, Rancasari, Kota Bandung, Jawa Barat, INDONESIA

Location Kota bandung, Jawa barat INDONESIA

Abstract

Abstract

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Abstract

Contact Name
-

Contact Email
orics.iorajournal@gmail.com

Phone
+6285841953112

Journal Mail Official
orics.iorajournal@gmail.com

Editorial Address
Jl. Merkuri Timur VI No. 1, RT. 007, RW. 004, Manjahlega, Rancasari, Kota Bandung, Jawa Barat, INDONESIA

Location
Kota bandung,

Jawa barat

INDONESIA