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THE INFLUENCE OF COLLABORATION BRANDING ON PURCHASING DECISIONS (Case Study On Aice Blueberry Cookies Ice Cream Products) Kusumadewi, Intan
Jurnal Mekanika dan Manufaktur Vol 4 No 2 (2025)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/jmm.v4i2.14063

Abstract

The rapid business competition in Indonesia results in business challenges for a company. In the current era, consumers are very careful in finding, buying, and using a product that suits what they want. Therefore, a company is required to find what kind of marketing strategy so that the products they offer can become the main choice of consumers to make purchasing decisions. This study aims to determine how co-branding influences purchasing decisions for consumers of Ice Cream Aice Blueberry Cookies. This research is included in survey research using a verification description. The population used in the study were consumers of Aice Blueberry Cookies in Majalengka with a sample size of 100 respondents. The data collection technique in this study was the distribution of questionnaires using a Likert scale. The results of this study indicate that co-branding is in the very good category, and purchasing decisions are in the high category.
ANALISIS SENTIMENT MASYARAKAT TERHADAP PABRIK DI JAWA BARAT SEBAGAI DASAR STRATEGI PENINGKATAN CITRA INDUSTRI DI MAJALENGKA Kusumadewi, Intan
J-ENSITEC Vol. 11 No. 02 (2025): June 2025
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/j-ensitec.v11i02.14526

Abstract

The rapid development of the new industrial estate in Majalengka requires the support of a good image from the local community. This study aims to assess public sentiment towards factories in West Java as a basis for formulating strategies to improve the image of industry in Majalengka. The Support Vector Machine (SVM) method was applied to classify the sentiment of YouTube comments relating to the factory, after a process of data collection, text preprocessing, and lexicon-based sentiment labelling. The main findings indicated that people's sentiments were distributed in proportions of approximately 30% negative, 35% neutral, and 35% positive. The accuracy of the SVM model was recorded at 78.48%, while the confusion matrix indicated adequate classification performance of the sentiments. matrix indicates adequate classification performance for negative, neutral, and positive sentiments. negative, neutral, and positive sentiments. This finding indicates that there is a significant negative sentiment towards the significant negative sentiment towards the industry, although it is not dominant. In conclusion, sentiment analysis conducted through social media can serve as a basis for formulating public relations and Corporate Social Responsibility (CSR) strategies. Corporate Social Responsibility (CSR) strategies in an effort to improve the industry's image. The industry and the government are advised to improve clear communication and responsive CSR programmes, with the aim of reducing negative sentiment and strengthening public trust. strengthen public trust.