Using Analytic Hierarchy Process (AHP) to Define the Best Programming Language for Software in Agribusiness

Bibliographic Details
Main Author: Lários, Gustavo Bezerra
Publication Date: 2025
Other Authors: Santana, Guilherme Augusto Adams, Gulo, Carlos Alex Sander Juvêncio, Reis, João Gilberto Mendes dos, Toloi, Rodrigo Carlo
Format: Article
Language: eng
Source: GeSec
Download full: https://ojs.revistagesec.org.br/secretariado/article/view/5077
Summary: This study develops a specialized framework for evaluating programming languages for agribusiness software development using the Analytical Hierarchy Process (AHP). The decision model was structured using the criteria Efficiency, Complexity, and Maintainability, with seven subcriteria: Execution Time, Memory Consumption, Ease of Learning, Portability, Updates, Community, and Security. The framework was validated through a comprehensive evaluation involving eight domain experts with experience in agribusiness software development. Results demonstrate that Efficiency is the most critical criterion (0.527), with Security (0.250), Ease of Learning (0.209), and Memory Consumption (0.199) being the most influential subcriteria. The analysis reveals that Python (0.397) is the preferred programming language for agribusiness applications, followed by PHP (0.264) and TypeScript/JavaScript (0.175). This research contributes to agricultural technology literature by providing a structured approach to technology selection that accounts for the specific requirements of agribusiness software development, helping developers make more informed decisions when selecting programming languages for agricultural applications.
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spelling Using Analytic Hierarchy Process (AHP) to Define the Best Programming Language for Software in AgribusinessProgramming LanguageAgribusinessSoftwareThis study develops a specialized framework for evaluating programming languages for agribusiness software development using the Analytical Hierarchy Process (AHP). The decision model was structured using the criteria Efficiency, Complexity, and Maintainability, with seven subcriteria: Execution Time, Memory Consumption, Ease of Learning, Portability, Updates, Community, and Security. The framework was validated through a comprehensive evaluation involving eight domain experts with experience in agribusiness software development. Results demonstrate that Efficiency is the most critical criterion (0.527), with Security (0.250), Ease of Learning (0.209), and Memory Consumption (0.199) being the most influential subcriteria. The analysis reveals that Python (0.397) is the preferred programming language for agribusiness applications, followed by PHP (0.264) and TypeScript/JavaScript (0.175). This research contributes to agricultural technology literature by providing a structured approach to technology selection that accounts for the specific requirements of agribusiness software development, helping developers make more informed decisions when selecting programming languages for agricultural applications.Revista de Gestão e Secretariado2025-07-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://ojs.revistagesec.org.br/secretariado/article/view/507710.7769/gesec.v16i7.5077Revista de Gestão e Secretariado (Management and Administrative Professional Review); Vol. 16 No. 7 (2025): Revista de Gestão e Secretariado v.16, n.7, 2025; e5077Revista de Gestão e Secretariado; Vol. 16 Núm. 7 (2025): Revista de Gestão e Secretariado v.16, n.7, 2025; e5077Revista de Gestão e Secretariado; v. 16 n. 7 (2025): Revista de Gestão e Secretariado v.16, n.7, 2025; e50772178-9010reponame:GeSecinstname:Sindicato das Secretárias do Estado de São Paulo (SINSESP)instacron:SINSESPenghttps://ojs.revistagesec.org.br/secretariado/article/view/5077/3329Lários, Gustavo BezerraSantana, Guilherme Augusto AdamsGulo, Carlos Alex Sander JuvêncioReis, João Gilberto Mendes dosToloi, Rodrigo Carloinfo:eu-repo/semantics/openAccess2025-07-09T13:39:18Zoai:ojs2.revistagesec.org.br:article/5077Revistahttps://www.revistagesec.org.br/ONGhttps://ojs.revistagesec.org.br/secretariado/oaieditor@revistagesec.org.br | gestoreditorial@revistagesec.org.br | rf.sabino@gmail.com2178-90102178-9010opendoar:2025-07-09T13:39:18GeSec - Sindicato das Secretárias do Estado de São Paulo (SINSESP)false
dc.title.none.fl_str_mv Using Analytic Hierarchy Process (AHP) to Define the Best Programming Language for Software in Agribusiness
title Using Analytic Hierarchy Process (AHP) to Define the Best Programming Language for Software in Agribusiness
spellingShingle Using Analytic Hierarchy Process (AHP) to Define the Best Programming Language for Software in Agribusiness
Lários, Gustavo Bezerra
Programming Language
Agribusiness
Software
title_short Using Analytic Hierarchy Process (AHP) to Define the Best Programming Language for Software in Agribusiness
title_full Using Analytic Hierarchy Process (AHP) to Define the Best Programming Language for Software in Agribusiness
title_fullStr Using Analytic Hierarchy Process (AHP) to Define the Best Programming Language for Software in Agribusiness
title_full_unstemmed Using Analytic Hierarchy Process (AHP) to Define the Best Programming Language for Software in Agribusiness
title_sort Using Analytic Hierarchy Process (AHP) to Define the Best Programming Language for Software in Agribusiness
author Lários, Gustavo Bezerra
author_facet Lários, Gustavo Bezerra
Santana, Guilherme Augusto Adams
Gulo, Carlos Alex Sander Juvêncio
Reis, João Gilberto Mendes dos
Toloi, Rodrigo Carlo
author_role author
author2 Santana, Guilherme Augusto Adams
Gulo, Carlos Alex Sander Juvêncio
Reis, João Gilberto Mendes dos
Toloi, Rodrigo Carlo
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Lários, Gustavo Bezerra
Santana, Guilherme Augusto Adams
Gulo, Carlos Alex Sander Juvêncio
Reis, João Gilberto Mendes dos
Toloi, Rodrigo Carlo
dc.subject.por.fl_str_mv Programming Language
Agribusiness
Software
topic Programming Language
Agribusiness
Software
description This study develops a specialized framework for evaluating programming languages for agribusiness software development using the Analytical Hierarchy Process (AHP). The decision model was structured using the criteria Efficiency, Complexity, and Maintainability, with seven subcriteria: Execution Time, Memory Consumption, Ease of Learning, Portability, Updates, Community, and Security. The framework was validated through a comprehensive evaluation involving eight domain experts with experience in agribusiness software development. Results demonstrate that Efficiency is the most critical criterion (0.527), with Security (0.250), Ease of Learning (0.209), and Memory Consumption (0.199) being the most influential subcriteria. The analysis reveals that Python (0.397) is the preferred programming language for agribusiness applications, followed by PHP (0.264) and TypeScript/JavaScript (0.175). This research contributes to agricultural technology literature by providing a structured approach to technology selection that accounts for the specific requirements of agribusiness software development, helping developers make more informed decisions when selecting programming languages for agricultural applications.
publishDate 2025
dc.date.none.fl_str_mv 2025-07-09
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://ojs.revistagesec.org.br/secretariado/article/view/5077
10.7769/gesec.v16i7.5077
url https://ojs.revistagesec.org.br/secretariado/article/view/5077
identifier_str_mv 10.7769/gesec.v16i7.5077
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://ojs.revistagesec.org.br/secretariado/article/view/5077/3329
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Revista de Gestão e Secretariado
publisher.none.fl_str_mv Revista de Gestão e Secretariado
dc.source.none.fl_str_mv Revista de Gestão e Secretariado (Management and Administrative Professional Review); Vol. 16 No. 7 (2025): Revista de Gestão e Secretariado v.16, n.7, 2025; e5077
Revista de Gestão e Secretariado; Vol. 16 Núm. 7 (2025): Revista de Gestão e Secretariado v.16, n.7, 2025; e5077
Revista de Gestão e Secretariado; v. 16 n. 7 (2025): Revista de Gestão e Secretariado v.16, n.7, 2025; e5077
2178-9010
reponame:GeSec
instname:Sindicato das Secretárias do Estado de São Paulo (SINSESP)
instacron:SINSESP
instname_str Sindicato das Secretárias do Estado de São Paulo (SINSESP)
instacron_str SINSESP
institution SINSESP
reponame_str GeSec
collection GeSec
repository.name.fl_str_mv GeSec - Sindicato das Secretárias do Estado de São Paulo (SINSESP)
repository.mail.fl_str_mv editor@revistagesec.org.br | gestoreditorial@revistagesec.org.br | rf.sabino@gmail.com
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