Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal RABIT: Jurnal Teknologi dan Sistem Informasi Univrab
Petra Erlangga Ardy Wibowo
Universitas Semarang
Computer Science & IT Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
PEMILIHAN USAHA SEKTOR PERTANIAN UNGGULAN DI WILAYAH PULAU JAWA MENGGUNAKAN METODE MOORA Irfan Hanafi; Petra Erlangga Ardy Wibowo; Agusta Praba Ristadi Pinem
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 1 (2025): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i1.5540

Abstract

The agricultural sector plays a crucial role in supporting regional economies, particularly in providing food supplies, creating employment opportunities, and reducing poverty levels. However, identifying priority agricultural sectors often poses challenges due to the lack of comprehensive analysis and sufficient data. This study aims to develop a Decision Support System (DSS) utilizing the Multi-Objective Optimization by Ratio Analysis (MOORA) method to identify the leading agricultural enterprises in a specific region. MOORA was selected for its advantages in efficiently and straightforwardly managing multiple criteria. The research incorporates seven key criteria: regional suitability, types of superior commodities, productivity levels, land area, seasonal or annual patterns, labor requirements, and funding sources. The findings indicate that the best alternative is Food Crops, achieving the highest Yi value of 0.5104, followed by Horticulture and Plantations. Although there are similarities between the input data and the rankings produced, the validity of this research has been further analyzed using Spearman’s rank correlation test. The results show a correlation value of 0.300, indicating a weak relationship between the two variables compared. This weak correlation underscores the need to enhance data quality and integrate information on the number of enterprises to make the ranking system more effective and relevant in supporting the development of the agricultural sector.
Co-Authors Agusta Praba Ristadi Pinem Irfan Hanafi