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All Journal Jurnal Teknologi Informasi dan Pendidikan Journal of Hypermedia & Technology-Enhanced Learning The Indonesian Journal of Computer Science
Rahmatika, Hayati
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Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Social Sciences Other

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Revealing The Advantages of the Best Cooking Oil Brand: A Case Study of Weighted Aggregated Sum Assessment (WASPAS) Method in Decision Support System Hendriyani, Yeka; Mariani, Mariani; Rahmatika, Hayati; Emelsy, Nalurry
Jurnal Teknologi Informasi dan Pendidikan Vol. 16 No. 2 (2023): Jurnal Teknologi Informasi dan Pendidikan
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jtip.v16i2.760

Abstract

The purpose of this research is to implement the Weighted Aggregated Sum Product Assessment (WASPAS) method in determining the best cooking oil brand. The research method used is the Weighted Aggregated Sum Product Assessment (WASPAS) method with the stages of determining criteria, weights, and alternatives, creating a decision matrix, calculating the normalization value of the matrix and WASPAS weights in decision making Calculating the Qi value of normalization and weights makes ranking from the highest Qi value. From the research it is known that alternative A4 with the description Bimoli has the highest Qi value of 0.9162, so it is concluded that alternative A4 or Bimoli was chosen as the best cooking oil among the eight alternatives or other cooking oil brands. The result of this study is that the WASPAS method is able to recommend the selection of the best cooking oil for consumers.
Design and Development of a Website for Improving Sales Efficiency of Horticultural Ornamental Plant SMEs in Lubuk Minturun Rahmatika, Hayati; Mursyida, Lativa; Kurniadi, Denny; Farell, Geovanne
Journal of Hypermedia & Technology-Enhanced Learning Vol. 1 No. 3 (2023): Journal of Hypermedia & Technology-Enhanced Learning—Book Haven
Publisher : Sagamedia Teknologi Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58536/j-hytel.v1i3.89

Abstract

This research aims to design and develop a dedicated website for managing Small and Medium-sized Enterprises (SMEs) specializing in ornamental plants in the Agrotourism area of Lubuk Minturun. The website focuses on the needs of SMEs and ornamental plant buyers. The development method employed is the MVC (Model, View, Controller) architecture using the Waterfall approach to provide an organized development structure. The website offers services such as SMEs event schedules and facilities for buying and selling ornamental plant products. The successful provision of these services is expected to promote and support SMEs in ornamental plants in the area. The utilization of technologies such as the PHP programming language, Yii Framework, and MySQL database provides a solid technological foundation, ensuring the efficiency and scalability of the website. In conclusion, the design of this website not only establishes a platform for SMEs and brings positive benefits to the business development and promotion of ornamental plants in the Agrotourism area of Lubuk Minturun. With the proper technological support, it is anticipated that this website will enhance the competitiveness of SMEs and add value to stakeholders in the horticultural ornamental plant sector.
Decision Support System for Determining the Best Online Learning Application Using the Weighted Product Method (WPM) Yeka Hendriyani; Mariani; Rahmatika, Hayati; Akbar Ilahi; Hardeyenti, Dessy
The Indonesian Journal of Computer Science Vol. 12 No. 4 (2023): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i4.3352

Abstract

This article discusses the use of the Weighted Product (WP) Method in a Decision Support System to determine the best online learning application. The goal is to help users choose a learning app that suits their needs and preferences. Relevant criteria, such as user interface, learning content, interactive features, difficulty level, and subscription price, are identified and assigned relative weights. This study uses data from various online learning apps to train the WP model and rank the apps based on the highest scores. The experimental results show that the WP method successfully identifies the best online learning apps with high accuracy, allowing users to have an effective and efficient learning experience according to their individual goals. Thus, this SDM can be an effective guide for users in making informed decisions to meet their education and learning needs
Co-Authors Akbar Ilahi Emelsy, Nalurry Geovanne Farell Hardeyenti, Dessy Kurniadi, Denny Mariani Mariani Mariani Mursyida, Lativa Yeka Hendriyani