Science, Technology & Innovation

DEVELOPMENT OF A LEGISLATIVE MANAGEMENT AND E-SESSION SYSTEM FOR THE SANGGUNIANG BAYAN OF LGU MOTIONG, SAMAR

['Niego', 'Escalante', 'Bathan', 'Jabinar']

This study presents the development of a Legislative Management and E-Session System for the Sangguniang Bayan of LGU Motiong, Samar, aimed at enhancing the efficiency, transparency, and accessibility of local legislative operations. The research addresses the limitations of traditional paper-based processes, which often result in delays, difficulty in tracking legislative measures, and challenges in document management. Using a system development approach, the study designed and implemented a web-based e-governance platform that integrates key functionalities including ordinance and resolution management, a legislative tracking system, session and agenda management, committee management, a centralized document repository or digital archives, and a public transparency portal. The system supports multiple user roles such as administrator, secretary, Sangguniang Bayan members, and staff, ensuring proper access control and workflow management. The developed system enables real-time monitoring of legislative documents, efficient scheduling and conduct of sessions, and secure storage and retrieval of official records. Additionally, the inclusion of a transparency portal promotes public access to approved ordinances and resolutions, supporting accountability and citizen engagement. The study employed user-centered design and iterative development to ensure usability and functionality aligned with the needs of the end users. Findings indicate that the system significantly improves operational efficiency, reduces reliance on paper-based processes, and enhances data organization and retrieval. The study concludes that the implementation of the Legislative Management and E-Session System can serve as a sustainable solution for modernizing local legislative processes and advancing digital governance in municipalities. In light of these findings, it is strongly recommended that the LGU of Motiong prioritize the immediate adoption and full implementation of the system to address existing inefficiencies and improve legislative operations without delay. The LGU should institutionalize its use through official policies, allocate the necessary resources for deployment and support, and ensure that all legislative personnel actively utilize the platform to maximize its benefits in promoting transparency, efficiency, and responsive governance.

Integration of CNN Model to Analyze UAV-based Collected Data in Agricultural Land Surveillance

['R Tabiongan', 'M Labrador']

This study explored the integration of convolutional neural network (CNN) models in analyzing unmanned aerial vehicle (UAV)-collected data for agricultural land surveillance. UAV technology has become widely used in agriculture for monitoring crop conditions, detecting plant health issues, and improving agricultural productivity. However, the large volume of image data captured through UAV sensors requires advanced analytical techniques for accurate interpretation. The study examined deep learning methods, particularly CNN-based models, to classify crops and analyze agricultural land characteristics. Results demonstrate that combining UAV imagery with deep learning algorithms improves crop detection accuracy and spatial analysis. The findings highlight the potential of artificial intelligence-driven surveillance systems to support agricultural monitoring, resource management, and precision farming initiatives.

Exploring Machine Learning Algorithms for Predicting Infectious Diseases

['SM Pacolor']

This study explored the application of machine learning algorithms in predicting infectious diseases using epidemiological data from Catbalogan City. The research analyzed datasets on diseases such as influenza, dengue, and malaria to identify patterns that could forecast potential outbreaks at the barangay level. Decision Tree, Random Forest, and Gradient Boosted Tree algorithms were tested to determine predictive accuracy. Evaluation metrics including RMSE, R², MSE, and MAE were used to assess model performance. Results showed that Gradient Boosted Trees produced the most accurate predictions. The study highlights the potential of machine learning to support public health planning, early disease detection, and improved management of infectious diseases in local communities.

Production and Acceptability of Rice Wine and Determination of Its Phytochemical Compounds

['Mendano', 'Amascual', 'Celmar', 'Echapare', 'Austero']

This study investigated the production and acceptability of rice wine using indigenous rice varieties, namely Ballatinao, Pilit, and Kalinayan, through controlled fermentation processes. Physico-chemical analyses were conducted to determine alcohol content, pH level, total soluble solids, and phytochemical compounds. Sensory evaluation using a hedonic scale assessed appearance, aroma, taste, mouthfeel, and overall acceptability of the products. Results revealed that Ballatinao rice wine obtained the highest acceptability and antioxidant activity among the samples. The findings demonstrate the potential of local rice varieties for value-added processing and livelihood development. The study recommends product refinement, safety testing, and commercialization to support sustainable community-based enterprises.

Establishing Network Performance Mapping for IoT Applications in Samar: Performance Evaluation of IoT Device in Catbalogan Samar

['Alcos', 'Macariola', 'Amante']

This study evaluated the network performance of Internet of Things (IoT) devices deployed in selected locations in Catbalogan City using LoRaWAN technology. It aimed to assess communication efficiency in different transmission modes through parameters such as Received Signal Strength Indicator (RSSI), Packet Delivery Ratio (PDR), time-on-air, and throughput. A prototype system consisting of sensor nodes, gateways, and servers was developed and tested in actual field environments. Results showed that network performance varied according to distance, spread factor, and environmental conditions. The findings highlight the importance of proper network configuration for reliable IoT deployment. The study recommends further testing in varied terrains and continuous optimization for large-scale implementation.

Formulation and Physical Evaluation of Natural Soaps Blended with Carrot (Daucus carota) Peel Extract Additives and Plant-Based Oils

['Mendaño', 'Albina']

This study formulated and evaluated three natural soaps using carrot peel extract additives, plant-based oils, and lye through cold saponification. Laboratory analysis and sensory evaluation were conducted to assess physicochemical properties such as pH, moisture content, foam height, and foam retention, as well as user acceptability. Results showed that all samples had pH values within the safe range of 8–10 and moisture contents within acceptable limits. Sample 3 exhibited superior hardness and foam stability, while Sample 2 obtained the highest overall acceptability rating. Participants found the soaps non-irritating and pleasant to use. The study recommends improving fragrance formulation and conducting further testing to support commercialization.

Innovating Tikog Product Verification with Blockchain-Based Authentication for Traditional Weaving

['Macariola']

This study focused on innovating Tikog production to improve the quality, durability, and market value of traditional woven products in Samar. Using developmental and experimental methods, the researchers introduced improved processing techniques, enhanced drying methods, and standardized weaving practices. Product evaluation was conducted through sensory testing, durability assessment, and user acceptability surveys. Findings revealed that the improved production process increased product strength, aesthetic quality, and consumer satisfaction. The study highlights the importance of integrating indigenous knowledge with modern innovation to sustain traditional livelihoods. It recommends continuous skills training, technology support, and stronger market linkages to enhance income generation, preserve cultural heritage, and promote sustainable community-based enterprises.

Development of Soap with Alagaw (Premna odorata) Shoot as the Main Ingredient

['Arteche', 'Quiano', 'Labrague']

This study aimed to develop a plant-based soap using Alagaw (Premna odorata) shoots as the main ingredient for treating minor skin problems, particularly scabies. Using a developmental research design, powdered Alagaw shoots were incorporated into soap formulation through laboratory analysis and controlled processing procedures. The product underwent sensory evaluation in terms of fragrance, foaming, rinsing, moisture, irritancy, and overall acceptability. Results indicated that the formulated soap was acceptable and safe for skin use. The study highlights the potential of herbal-based products as affordable alternatives for skin care. It recommends further clinical testing, safety validation, and feasibility studies to support commercialization and community utilization.

Identification, Diversity Assessment and Pharmaceutical Values of Ferns (Pteridophytes) in Samar Island: Phase I Development and Acceptability of Cyathea contaminans Lotion

['Dejarme', 'Lacaba', 'Gabon']

This study focused on the development and acceptability testing of a lotion derived from Cyathea contaminans, a tree fern commonly found in tropical forests of Samar Island. Using hydrosol steam distillation and formulation techniques, the researchers extracted bioactive compounds and combined them with oils and waxes to produce experimental lotion treatments. Laboratory analysis and sensory evaluation were conducted to assess color, texture, scent, irritation, drying effect, and overall absorption. Results showed that Treatment B obtained the highest acceptability ratings among respondents. Findings indicate that Cyathea contaminans has potential pharmaceutical and cosmetic value. The study recommends further safety testing, commercialization studies, and technology transfer for community-based utilization.

Advanced and Geared Honing Agricultural Management: Baseline for Andragogical Science and Technology Education

['Mustacia-Lacaba']

This study established a baseline assessment of the demographic, educational, and technological profiles of smallholder farmers in Barangays Marupangdan and Astorga, Daram, Samar, to support andragogical science and technology education programs. Using a descriptive-evaluative design, data were gathered through structured questionnaires, interviews, and field observations. Results revealed limited farm sizes, low levels of formal education, moderate familiarity with precision farming, and low adoption of modern technologies. Financial constraints, lack of training, and limited access to equipment hindered technology uptake. However, farmers demonstrated willingness to learn and adopt innovations. The study recommends strengthening extension services, providing accessible training programs, improving infrastructure support, and promoting farmer-centered technology education to enhance agricultural productivity and sustainability.

Moving Towards Technology-Based Barangay Local Government Unit in Samar: A Computer Literacy Assessment

['Candido', 'Mabulac', 'Payumo', 'Cano']

This study assessed the computer literacy of barangay officials and employees in selected municipalities in Samar as part of the Moving Towards Technology-Based LGU initiative. It evaluated respondents’ basic computer skills in Microsoft Word, Excel, and PowerPoint through pretest and posttest methods following a computer literacy training program. Findings revealed significant improvements in participants’ digital competencies after the intervention, indicating the effectiveness of the training project. Enhanced computer literacy contributed to more efficient administrative processes and improved public service delivery. The study recommends sustaining regular ICT training programs, upgrading technological infrastructure, strengthening digital support systems, and integrating e-governance practices to promote technology-driven governance in barangay operations.

Demographic Profiling: A Web-Based Predictive Analysis System with GIS for Local Government Unit (LGU) Policy Program Implementation

['Paculaba', 'Jabinar', 'Niego', 'Zosa']

This study developed a web-based demographic profiling and predictive analysis system integrated with Geographic Information Systems (GIS) to support Local Government Units in policy and program implementation. It analyzed population data to generate accurate, timely, and location-based information for evidence-based decision-making. Using developmental and descriptive-evaluative methods, the system was assessed in terms of functionality, reliability, usability, efficiency, maintainability, and portability. Findings indicate that the system is highly effective in generating demographic insights and facilitating service delivery. The study recommends continuous system upgrading, capacity-building for LGU personnel, data security enhancement, and integration with national databases to maximize sustainability and policy relevance.