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All Journal Mimbar Agribisnis: Jurnal Pemikiran Masyarakat Ilmiah Berwawasan Agribisnis
Santoso, Siswanto
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Agriculture, Biological Sciences & Forestry

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Analisis Pengaruh Produk, Harga, Promosi, dan Kualitas Pelayanan Terhadap Kepuasan Konsumen Melon Hidroponik di Indigen Farm Yogyakarta Prestasiani, Wanoja Aghisna; Budiraharjo, Kustopo; Santoso, Siswanto
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.v11i2.17739

Abstract

Market competition between conventional melons and hydroponic melons is increasingly becoming a challenge for Indigen Farm in achieving a larger market share because the level of market competition will influence consumers to choose a variety of choices and alternative products that can meet their needs in accordance with consumer desires and satisfaction. This research aims to analyze simultaneously or partially the influence of product, price, promotion and service quality on consumer satisfaction of hydroponic melons at Indigen Farm Yogyakarta. The research method used is a survey. The research was carried out at Indigen Farm during the melon picking tour. Respondents were determined using accidental sampling. The number of respondents taken was 100 respondents with the criteria being that the respondent was at least 17 years old and had previously purchased Indigen Farm hydroponic melons. The data analysis method used was multiple linear regression analysis which was analyzed using the SPSS (Statistical Product and Service Solution) For Windows program. The research results show that simultaneous multiple linear regression analysis of product, price, promotion and service quality has a significant effect on consumer satisfaction. Partially, products and promotions have an effect, while price and service quality do not have a significant effect. The coefficient of determination is 0.583, meaning that the independent is able to explain 58.3% of the dependent variable while the remaining 41.7% is explained by other variables outside the model.
Co-Authors Kustopo Budiraharjo Prestasiani, Wanoja Aghisna