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Interdisciplinary Research Integration in Higher Education: A Case Study on the Development of an AI-Based Non-Invasive Hemoglobin Detection System Sri Wiji Lestari; Nurdina Widanti; Wike Handini; Ahmad Raafi Haqq; Aditya Alamsyah
Jurnal Penelitian Pendidikan IPA Vol 11 No 11 (2025): November
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i11.12961

Abstract

This study examines the effectiveness of Project-Based Learning (PBL) in the development of a non-invasive hemoglobin detection system using photoplethysmography (PPG) integrated with artificial intelligence. A quasi-experimental design was applied to 26 Electrical Engineering students enrolled in Big Data Analysis, Sensor Design, and Embedded Systems courses. Students worked in groups to design, implement, and test prototypes. Data were collected through project rubrics, questionnaires, observations, and reflections, and were analyzed to determine the effectiveness index. The results revealed an overall effectiveness index of 3.8, categorized as good. The highest score was achieved in the affective aspect (4.2), reflecting strong motivation, proactive attitudes, and teamwork. Cognitive (3.9) and reflection (3.8) aspects also showed positive outcomes, while psychomotor (3.6) and product quality (3.5) remained weaker due to technical issues, including prototype accuracy and troubleshooting difficulties. The study demonstrates that PBL effectively integrates theory and practice, enhances 21st-century skills, and fosters meaningful learning experiences. Additionally, the findings highlight the potential of incorporating advanced technologies into engineering education while contributing to innovative health technology solutions for addressing malnutrition.
Design Smart Farming in Rice Field for Monitoring Soil Fertility and Pest Rate Using Internet of Things Nurdina Widanti; Aditya Alamsyah; Actor Albus; Ahmad Nur Ikhsan; Sri Wiji Lestari; Wike Handini; Sasmito Adi Raharjo
Jurnal Penelitian Pendidikan IPA Vol 10 No 8 (2024): August
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v10i8.8288

Abstract

Rice fields in Indonesia have a strategic role in providing food for the Indonesian population. The Central Statistics Agency (BPS) noted that domestic rice consumption also continues to increase, 98.35% of households in Indonesia consume rice. There are many influencing factors for production rice such as pest, climate change. The aim to optimize rice production by monitoring soil moisture and soil pH and adding protection features to detect rat pests. This tool was built using an Internet of Things-based system integration method, where the system output can be monitored on the blynk and email applications for the reading history of rat pests if they are caught on camera. The results obtained from the system are Soil moisture sensor readings have a system accuracy of 99% with an error value of 0.01. And the pH sensor reading has an accuracy of 99% with an error of 0.015. The most optimal PIR sensor reading is 1 meter and this data is sent simultaneously with the camera sensor via email. Monitoring data on rice agricultural land by adding rat pest protection features, as well as historical data can be captured wellcan provide a strong basis for the development of more effective and sustainable.