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International Journal of Informatics and Data Science
Published by ADA Research Center
ISSN : -     EISSN : 30267315     DOI : -
Core Subject : Science,
Computer Science & IT
International Journal of Informatics and Data Science publishes manuscripts of Computer Science, but is not limited to the fields of: 1. Natural Language Processing Pattern Classification, 2. Speech recognition and synthesis, 3. Robotic Intelligence, 4. Big Data, 5. Informatics Techniques, 6. Image and Speech Signal Processing, 7. Data Mining 8. Decision Support System, 9. Experts System, and 10. Cryptography
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 2 Documents
 1 
Search results for , issue "Vol. 2 No. 1 (2024): December 2024" : 2 Documents clear
Decision Support System for Determining Subsidized Food Receipt for Poor Families with SAW Method Elvia Hariska
International Journal of Informatics and Data Science Vol. 2 No. 1 (2024): December 2024
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/ijids.v2i1.24

Abstract

In accordance with the regulations set by the Office of Kotasan Village, residents are entitled to receive subsidized food based on specific criteria. To determine who is selected to receive subsidized food and distribute it to low-income families will be conducted by the Kotasan Village Office. As a supporting tool to determine individuals eligible to receive subsidized food, a decision support system is required. Within the decision support system, there are several methods, one of which can be used is the Simple Additive Weighting (SAW) method. In this study, the author will address a case to find the best alternative from certain established criteria by comparing the alternatives using the Simple Additive Weighting (SAW) method. In this evaluation, the alternative Saidi ranks first with a Vi value of 0.910, followed by Zum in second place with a Vi of 0.820. In third position, Arju has a Vi value of 0.761. Meanwhile, the alternative with the lowest rank is Sri with a Vi of 0.425, followed by Supri with a Vi of 0.433 and Paiman with a Vi of 0.461.
Comparison of WSM and Weight Product Methods with WSM-Score and Vector Approaches Roziyani Setik; Asyahri Hadi Nasyuha; Sri Redjeki
International Journal of Informatics and Data Science Vol. 2 No. 1 (2024): December 2024
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/ijids.v2i1.63

Abstract

Fertilizer is a material that is given to the soil or plants to meet the nutritional needs of the plant. Fertilization needs to be carried out rationally according to the needs of the plant. In the supply of fertilizers, farmers have difficulty in determining the best fertilizer for their plants, making it difficult to choose which fertilizers are good for their plants. In determining the best fertilizer, the decision support system (DSS) can be used as an alternative to help someone make decisions more effectively and efficiently by utilizing certain data and models. To solve the existing problems, it is necessary to conduct research in decision making using the Weighted Sum Model (WSM) and Weight Product (WP) Methods which can produce decisions based on the best fertilizer criteria that will be purchased by customers. The Weighted Sum Model (WSM) method is one of the simplest and easiest methods to understand its application, this method is also part of the MCDM (Multi-Criteria Decision Making) method in evaluating the value of each alternative. The Weight Product (WP) method is a method using multiplication to relate the attribute rating, where the rating of each attribute must be ranked with the attribute weight in question. From the results of the implementation of this system, it can be concluded that using the Weighted Sum Model and Weight Product method can help customers in the decision-making process for choosing the best fertilizer to use on their plants.

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