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All Journal Contemporary Mathematics and Applications (ConMathA) Tensor: Pure and Applied Mathematics Journal Jurnal Abdiraja InEJ: Indonesian Engagement Journal

Asri Bekti Pratiwi, Asri Bekti

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Author-ID : 559369

Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Dentistry Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Nursing Public Health Social Sciences Other

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Penerapan Cuckoo Search Algorithm (CSA) untuk Menyelesaikan Uncapacitated Facility Location Problem (UFLP) Asri Bekti Pratiwi; Nur Faiza; Edi Edi Winarko
Contemporary Mathematics and Applications (ConMathA) Vol. 1 No. 1 (2019)
Publisher : Universitas Airlangga

The aim of this research is to solve Uncapacitated Facility Location Problem (UFLP) using Cuckoo Search Algorithm (CSA). UFLP involves n locations and facilities to minimize the sum of the fixed setup costs and serving costs of m customers. In this problem, it is assumed that the built facilities have no limitations in serving customers, all request from each customers only require on facility, and one location only provides one facility. The purpose of the UFLP is to minimize the total cost of building facilities and customer service costs. CSA is an algorithm inspired by the parasitic nature of some cuckoo species that lay their eggs in other host birds nests. The Cuckoo Search Algorithm (CSA) application program for resolving Uncapacitated Facility Location Problems (UFLP) was made by using Borland C ++ programming language implemented in two sample cases namely small data and big data. Small data contains 10 locations and 15 customers, while big data consists 50 locations and 50 customers. From the computational results, it was found that higher number of nests and iterations lead to minimum total costs. Smaller value of pa brought to better solution of UFLP.

Sistem Pakar Diagnosa Hipertiroid Menggunakan Certainty Factor dan Logika Fuzzy Rizkita Apriliana; Auli Damayanti; Asri Bekti Pratiwi
Contemporary Mathematics and Applications (ConMathA) Vol. 2 No. 1 (2020)
Publisher : Universitas Airlangga

Hyperthyroidism is a condition when the function of thyroid gland becomes excessive. The excess function of thyroid gland increases thyroid hormone production which affect body metabolism and physiological activity. This study aims to make an expert system diagnose hyperthyroidism with certainty factor and fuzzy logic. The stages of the process of diagnosing hyperthyroidism including problem identification, needs analysis of symptoms and types of hyperthyroidism, determination of rules, system design, case examples implementation, system testing, and evaluation. Variables used were systolic blood pressure, triiodothyronine (T3) levels, thyroxine (T4) levels, thyroid stimulating hormones (TSH) levels, goiter, tremors, and excessive sweating. All variables are processed using fuzzy logic with fuzzyfication stages, rule determination, min implications, max rule composition, and defuzzyfication which then proceed with certainty factor with sequential CF and CF stages. The system output is diagnosis the condition of hyperthyroidism such as hyperthyroidism, subclinical hyperthyroidism, and normal accompanied by a certainty factor. Based on the evaluation result, the accuracy of the expert system according to expert diagnostics is 86.7%

Penyelesaian Container Stowage Problem untuk Kontainer Ukuran 20 Feet menggunakan Whale Optimization Algorithm Quinn Nathania PJY; Asri Bekti Pratiwi; Herry Suprajitno
Contemporary Mathematics and Applications (ConMathA) Vol. 3 No. 2 (2021)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v3i2.29670

This paper has purpose to solve Container Stowage Problem (CSP) for 20 feet container using Whale Optimization Algorithm (WOA). CSP is a problem discussing about how to stowage a container on the ship where the purpose to minimize the unloading time. Moreover, 20 feet container is one of container types. WOA is a recently developed swarm-based metaheuristic algorithm that is based on the bubble net hunting maneuver technique of humpback whales for solving complex optimization problems. WOA had three procedures, first encircling prey, second bubble-net attacking method or exploitation phase, and third search for prey or exploration phase. WOA application program or resolving solve CSP for 20 feet container was made by using Borland C++ programming language which was implemented in three cases types of CSP data, first, the small data taking about nine containers with the number of bays, rows and tiers, respectively, are 4, 4, 4. The second and third data was medium data and big data with 62 containers and 95 containers each data, and had the number of bays, rows and tiers, respectively, are 14, 4, 5. After executing the program can be concluded the unloading time will be better if the number of whales is larger, while the number of iterations and the number of parameter control for shape of a logaritma spiral don’t affect the solution.

Penerapan Seagulls Optimization Algorithm untuk Menyelesaikan Open Vehicle Routing Problem Laula Ika Setya Rahman; Asri Bekti Pratiwi; Herry Suprajitno
Contemporary Mathematics and Applications (ConMathA) Vol. 4 No. 1 (2022)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v4i1.34549

This paper aims to solve the problem of Open Vehicle Routing Problem using Seagulls Optimization Algorithm. Open Vehicle Routing Problem (OVRP) is a variation of Vehicle Routing Problem (VRP) which will not return to the depot after visiting the last customer, is different from VRP which requires the vehicle to return to the depot because the company have insufficient number of vehicles for the distribution of products to customers so they must to rent vehicles and this OVRP aims to minimize the total cost of distributing products with the shortest optimal distance to meet the demands of each customer with private vehicles and rental vehicles. Seagulls Optimization Algorithm (SOA) is the algorithm inspired by the behaviour of seagulls in migrating and ways of attacking the pray of seagulls in nature. In general, the process begins with generating the initial position, evaluating the objective function, the migration process, the attacking process to get a new position, compare the objective function for the new position and the old position, update the position and save the best seagulls in each iteration until the maximum iteration is met. The program used to complete OVRP with Seagulls Optimization Algorithm is Borland C++ and implemented using 3 case examples, small data with 18 customers, medium data 50 customers and large data 100 customers. Based on the implementation results, it can be concluded that the higher number of seagulls, iterations and the smaller the control variable value tend to effect minimum cost gained.

Co-Authors Alfiniyah, Cicik Auli Damayanti Edi Winarko Herry Suprajitno Laula Ika Setya Rahman Millah, Nashrul Nur Faiza Quinn Nathania PJY Rizkita Apriliana Whardhana, Aisyah Fadhilah

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