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Pengaruh Brand Equity dan Gaya Hidup Sehat terhadap Keputusan Pembelian Produk Plant-Based Meat Merek Meatless Kingdom Pratiwi, Kusuma Ratna; Santoso, Siswanto Imam; Nurfadillah, Suryani
Mimbar Agribisnis : Jurnal Pemikiran Masyarakat Ilmiah Berwawasan Agribisnis Vol 11, No 2 (2025): Juli 2025
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/ma.v11i2.18350

Abstract

Plant-based meat is a vegetable process made with the texture, taste, and nutrition as similar to meat as possible. The plant-based meat focus in this study was focusing on the Meatless Kingdom brand. This study aims to analyze the influence of brand equity consisting of brand awareness, brand association, perceived quality, and brand loyalty as well as a healthy lifestyle on the decision to purchase plant-based meat products from Meatless Kingdom. This study was conducted from October 2024 to January 2025. The determination of the sample is purposively sampling, which is for consumers who have purchased the product at least once and are at least 17 years old. The number of samples was determined by Lemeshow's formula, which was 96 respondents. Primary data were obtained from questionnaires distributed online and secondary data were obtained from journal literature and books. This study used a case study method using a quantitative approach. Instrument tests were conducted on 32 respondents with a validity and reliability test. A normality test and a classical assumption test were conducted to test the regression model used. Analysis of data to determine the effect using multiple linear regression analysis which includes the coefficient of determination test, F test, and t test. The results of the study found that brand awareness, brand association, perceived quality, brand loyalty, and healthy lifestyle influenced the decision to purchase plant-based meat products from Meatless Kingdom both simultaneously and partially.
Detection and prediction of rice plant diseases using convolutional neural network (CNN) method Pahlawanto, Reyhan Dzaki Sheva; Salsabila, Halimah; Pratiwi, Kusuma Ratna
Journal of Student Research Exploration Vol. 2 No. 1: January 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/josre.v2i1.254

Abstract

Rice is a basic staple food in many Asian countries and is generally irreplaceable. Rice accounts for almost half of Asia food expenditure. Rice is too a crop that is prone to plant disease. It can appear and cause a decline in the quality of rice. However, constant monitoring of the rice fields can prevent the infection of the disease. Therefore, detection and prediction of rice plant diseases is one of the topics that will be discussed in this research. The purpose of this research is to help farmers to quickly pinpoint the disease of rice plants and take care of it properly. The methods used in this paper is researching and redesigning the previous attempt to hopefully make it better and more accurate. We will be using Convolutional Neural Network (CNN) models VGG16 as our algorithm. The results are that our proposed method has more accuracy than previous research using a similar dataset. The novelty of this paper is the increased accuracy of rice plant disease detection.