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Undergraduate Theses

Permanent URI for this collectionhttps://hdl.handle.net/20.500.14578/5

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Subject: search.filters.lcsh.Web applications

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    Web-based agri-fisheries e-commerce market system
    Sentillas, Angelito Jr. (Davao del Sur State College, 2024-06)
    This study delves into the conceptualization, development, and implementation of such systems, exploring their potential to connect farmers, fishermen, and consumers directly which addresses the ease of product marketing using the system with map integration. Furthermore, the project sought to provide a user-friendly, buyer homepage which displays all the products, allows the buyer to add products to cart, provides a map which displays all the store location and the routing, and enable the user to create its own shop. Additionally, it allows the seller to add and manage products, and manage orders. It also enables the super admin to manage users, categories, products, and tract the user logs. Moreover, the system has utilized the rapid application development methodology to develop the project. The project achieved its goal of successfully implemented e-commerce system where seller can sell their products and buyers to buy products they want with integrated mapping system where user can view store location and its routing from buyer to the store. This implementation helped our local farmers, fishermen, and consumers by providing a website that allows the user to buy and sell their product online. In addition, this promote a wide range of marketing which give a lot of advantage for both users. The findings and insights gained from the study contribute to advancement of web-based Agri-fisheries e-commerce system, offering practical guidance and recommendation for stakeholders in the agriculture and fisheries sectors.
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    Spring onion disease detection and treatment recommendation
    Talaid, Nikko R. (Davao del Sur State College, 2024-06)
    Spring onion is a delicate crop that demands much attention during its cultivation; diseases such as the purple blotch and leaf blight affect spring onion crops and, in any case, prevention of these diseases is rather complicated to detect. Study aims to diagnose the diseases correctly and make suitable recommendations on the treatment needed. The researcher created an app that help in identifying the spring onion disease and would offer recommendations on how to treat such disease. In developing the app, the researcher used Android studio and Google Colab for datasets training. The technique used in choosing the survey participants is simple purposive random sampling and self-constructed checklist based on the ISO 9124 Likert scale to rate the app's functionality, reliability, and usability. The app is ideal for small and big farmlands, especially in regions without an internet connection, and during an experimental test, it gained an accuracy of 90% in the purple blotch and 93% in leaf blight-captured crop diseases within a 3-inch range. The significant results of this study include the application's ability to detect two types of diseases, namely purple blotch and leaf blight, and its ability to provide personalized treatments, such as recommendations, chemical treatments, and care tips, based on the specific disease detected. The app's contribution to the farming community is its ability to detect crop diseases early, simplify disease detection techniques, increase harvests, decrease chemical use, and prevent minor spring onion problems that could result in major outbreaks and damage large farmlands.