Garuda - Garba Rujukan Digital

Pengembangan Pemasaran Produk Bibit Tanaman di Dusun Baringin Gadut Dengan Digitalisasi Fajri Rinaldi Chan; Muhammad Imam Dwi Maulana
BALQIS : Journal of Business Innovation and Digital Marketing Vol. 1 No. 1 (2025): June 2025
Publisher : Program Studi Bisnis Digital - Fakultas Ekonomi dan Bisnis Islam

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This study explores the development of seedling product marketing in Baringin Gadut Hamlet through the implementation of digitalization strategies aimed at overcoming the limitations of conventional marketing practices. Despite the area’s significant potential in the plant nursery sector, its market reach and competitiveness have remained low due to reliance on traditional distribution methods. This research seeks to design and implement a digital marketing model that not only enhances economic outcomes but also empowers the local community. A qualitative descriptive approach was employed, involving interviews, field observations, surveys, and document analysis with plant seed entrepreneurs, local communities, and related stakeholders. The research process included community needs assessment, digital marketing training, the implementation of an online store platform, and evaluation of its effectiveness. Findings reveal that the OpenCart-based BITO online store, complemented by intensive training in social media and e-commerce use, successfully expanded market access and improved sales efficiency. Within the first month, BITO recorded multiple out-of-region transactions, indicating increased competitiveness of local products. Challenges such as limited digital literacy and internet infrastructure were addressed through stepwise training, mentoring, and technical adaptations of the platform, including features designed for low connectivity. Beyond improving income, the initiative contributed to building community confidence and skills in digital technology, fostering long-term empowerment. Overall, this study demonstrates that integrating digitalization with community capacity-building provides a sustainable model for rural agribusiness development and offers a replicable strategy for similar regions

Pengembangan Pemasaran Produk Bibit Tanaman di Dusun Baringin Gadut Dengan Digitalisasi Fajri Rinaldi Chan; Muhammad Imam Dwi Maulana
BALQIS : Journal of Business Innovation and Digital Marketing Vol. 1 No. 1 (2025): June 2025
Publisher : Program Studi Bisnis Digital - Fakultas Ekonomi dan Bisnis Islam

Show Abstract | Download Original | Original Source | Check in Google Scholar

This study explores the development of seedling product marketing in Baringin Gadut Hamlet through the implementation of digitalization strategies aimed at overcoming the limitations of conventional marketing practices. Despite the area’s significant potential in the plant nursery sector, its market reach and competitiveness have remained low due to reliance on traditional distribution methods. This research seeks to design and implement a digital marketing model that not only enhances economic outcomes but also empowers the local community. A qualitative descriptive approach was employed, involving interviews, field observations, surveys, and document analysis with plant seed entrepreneurs, local communities, and related stakeholders. The research process included community needs assessment, digital marketing training, the implementation of an online store platform, and evaluation of its effectiveness. Findings reveal that the OpenCart-based BITO online store, complemented by intensive training in social media and e-commerce use, successfully expanded market access and improved sales efficiency. Within the first month, BITO recorded multiple out-of-region transactions, indicating increased competitiveness of local products. Challenges such as limited digital literacy and internet infrastructure were addressed through stepwise training, mentoring, and technical adaptations of the platform, including features designed for low connectivity. Beyond improving income, the initiative contributed to building community confidence and skills in digital technology, fostering long-term empowerment. Overall, this study demonstrates that integrating digitalization with community capacity-building provides a sustainable model for rural agribusiness development and offers a replicable strategy for similar regions

Pengembangan Pemasaran Produk Bibit Tanaman di Dusun Baringin Gadut Dengan Digitalisasi Fajri Rinaldi Chan; Muhammad Imam Dwi Maulana
BALQIS : Journal of Business Innovation and Digital Marketing Vol. 1 No. 1 (2025): June 2025
Publisher : Program Studi Bisnis Digital - Fakultas Ekonomi dan Bisnis Islam

Show Abstract | Download Original | Original Source | Check in Google Scholar

This study explores the development of seedling product marketing in Baringin Gadut Hamlet through the implementation of digitalization strategies aimed at overcoming the limitations of conventional marketing practices. Despite the area’s significant potential in the plant nursery sector, its market reach and competitiveness have remained low due to reliance on traditional distribution methods. This research seeks to design and implement a digital marketing model that not only enhances economic outcomes but also empowers the local community. A qualitative descriptive approach was employed, involving interviews, field observations, surveys, and document analysis with plant seed entrepreneurs, local communities, and related stakeholders. The research process included community needs assessment, digital marketing training, the implementation of an online store platform, and evaluation of its effectiveness. Findings reveal that the OpenCart-based BITO online store, complemented by intensive training in social media and e-commerce use, successfully expanded market access and improved sales efficiency. Within the first month, BITO recorded multiple out-of-region transactions, indicating increased competitiveness of local products. Challenges such as limited digital literacy and internet infrastructure were addressed through stepwise training, mentoring, and technical adaptations of the platform, including features designed for low connectivity. Beyond improving income, the initiative contributed to building community confidence and skills in digital technology, fostering long-term empowerment. Overall, this study demonstrates that integrating digitalization with community capacity-building provides a sustainable model for rural agribusiness development and offers a replicable strategy for similar regions

IMPLEMENTASI HYBRID INTELLIGENCE SYSTEM UNTUK KLASIFIKASI BIJI-BIJIAN DENGAN ALGORITMA PCA DAN KNN Fajri Rinaldi Chan; Agung Ramadhanu
INTI Nusa Mandiri Vol. 19 No. 2 (2025): INTI Periode Februari 2025
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v19i2.6397

Food security has become a pressing global issue with the increasing population and food consumption needs. Red kidney beans, peanuts, and sunflower seeds play a crucial role in meeting the nutritional needs of society and serving as raw materials for various industries. This study aims to develop a seed classification system based on the Principal Component Analysis (PCA) and K-Nearest Neighbor (KNN) algorithms. The system is designed to recognize three types of seeds—red kidney beans, peanuts, and sunflower seeds—to improve the efficiency and accuracy of the classification process compared to manual methods. The dataset consists of 58 seed image samples, divided into training data (48 samples) and test data (10 samples). The research stages include image preprocessing (cropping, background removal, and thresholding segmentation), feature extraction using PCA to reduce data dimensionality, and classification with KNN based on Euclidean distance. A value of K=3 is used in the KNN algorithm to determine the proximity between data points. The test results show a classification accuracy of 90%, with 9 out of 10 test data correctly classified. PCA successfully simplified high-dimensional data into two main components without significant information loss, while KNN demonstrated strong capability in distinguishing the three types of seeds. This research contributes to the development of an AI-based automatic classification system for the food industry, with broader potential applications in high-dimensional data processing across various fields.

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