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A development of an IoT-based temperature-TDS monitoring system for shrimp cultivation pond Akhyar, Halil; Budianto, Arif; Rahayu, Susi; Alaydrus, Alfina Taurida; Anggriani, Ni Ketut; Wardi, Palaivia Harman; Pranahita, Dewa Dwi; Andini, Mira
ORBITA: Jurnal Pendidikan dan Ilmu Fisika Vol 11, No 2 (2025): November
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/orbita.v11i2.36423

High-quality water resources are important parameters for the sustainability of human civilization, the health of ecosystems, and the advancement of vital sectors. High-quality water is also needed for shrimp cultivation ponds. However, water-quality monitoring in the estuary is limited. In line with this, this study focuses on the design and implementation of an IoT-based TDS and temperature measurement system for estuarine water, aiming to develop an efficient, accurate, and automated prototype to support the fisheries sector in West Lombok regency. This study used a microcontroller, temperature and TDS (total dissolved solids) sensors, a wireless router, and a display. These elements were developed as a water-quality-level monitoring system based on TDS and temperature. The system was calibrated using a standard comparator before being examined under real conditions. The calibration procedure was conducted inside a controlled chamber at a water temperature of 25°C for 60 minutes, with a steady flow rate. All procedures were repeated three times and tested using a Student’s t-test. The IoT platform was tested using RSSI values with a 2s update interval. The calibration data were interpreted as a linear function between the standard and the developed system. The resulting design shows that the developed system can be installed at a shrimp cultivation pond with good performance. The designed system has a linearity of more than 90%. The system has a reliable accuracy level over 30 consecutive measurement days, resulting in the percentages of 85% to 93% (average = 91%). It can be concluded that IoT data communication via a wireless internet router performs well, with RSSI> -50 dBm for both sending and receiving. The IoT platform using ThingSpeak shows good performance (good stability), with a 2-second interval between data updates.

A Preliminary Study of Exhaled Breath Profiling of GERD-Asthma using an E-nose and Carbon Dioxide Concentration as Biomarkers Hadi, Kasnawi Al; Anggriani, Ni Ketut; Budianto, Arif; Nabilla, Dewi Alya; Farahin , Dewi Nor
Jurnal Penelitian Fisika dan Aplikasinya (JPFA) Vol. 15 No. 1 (2025)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jpfa.v15n1.p1-11

Carbon dioxide plays a vital role in the human body. Many studies confirm that changes in carbon dioxide concentrations can serve as biomarkers for various health problems. This biomarker can be detected using several techniques, including an electronic nose (e-nose). However, there is a limitation in the e-nose's function and development in specific health cases, especially in respiratory or other systems. In line with this, this study aims to develop an economical, simple e-nose based on a CO2 (carbon dioxide) gas sensor and to establish an exhaled breath profile related to asthma and GERD (gastroesophageal reflux disease), which are common daily health problems. For this purpose, 90 exhaled breath samples from three different health conditions were obtained as the primary breath profiling samples: healthy, GERD, and asthma. The samples were measured and analyzed using a simple e-nose based on a high-sensitivity carbon dioxide sensor. The e-nose was calibrated and tested under laboratory-scale procedures, including linearity, accuracy, and sensitivity examinations. Then, the collected samples were classified, analyzed, and interpreted to produce a profile prediction for those health problems. The results show that the e-nose system can measure CO2 gas concentrations in the range of 400-9700 ppm. There are three selective profiles of the exhaled breath samples: healthy (450 to 899 ppm), GERD (3327 to 5381 ppm), and asthma (6612 to 9706 ppm). It can be concluded that the developed e-nose can classify different health conditions. There is a significant difference between healthy, GERD, and asthma samples (p < 0.05). These differences were interpreted as breath profiles with an accuracy level of 84%. This research may contribute to a preliminary investigation of breath profiles for specific health problems, with a rapid response time and high accuracy.

The Influence of the Tide Levels on the Water Electrical Conductivity Parameter in the Estuary Area: In-Site and Real-Time Measurement Alaydrus, Alfina Taurida; Budianto, Arif; Rahayu, Susi; Andini, Mira; Akhyar, Halil; Anggriani, Ni Ketut
Jurnal Pendidikan Fisika dan Teknologi (JPFT) Vol 11 No 2 (2025): July - December
Publisher : Department of Physics Education, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpft.v11i2.10881

One area that requires attention in water quality studies is the estuarine ecosystem. Estuaries are transition zones connecting freshwater and marine waters, thus possessing unique environmental dynamics. However, there is limited information regarding the effect of sea tides in the area on local estuary water quality. Therefore, this study aims to identify the existing relationship between sea tide levels and EC values, using an IoT-based system that is portable, lightweight, and capable of operating in real time. This study was conducted over five days in Senggigi village, Batulayar, West Nusa Tenggara, Indonesia. The collected data focused on the EC parameter's water quality levels at different tide levels, which were monitored using the self-developed system. This system was developed using an EC sensor, a microcontroller, and a wireless internet router (for wireless data communication via ThingSpeak.com). This system was also equipped with a pH sensor, a TDS sensor, and a water temperature sensor. The recorded data show that the resulting data are valid and highly accurate, and that the system is ready for examination at the measurement area. The resulting data show that the correlation between tide level and EC value is logarithmic, with a regression coefficient of 0.934. The EC level was about 20.42 – 62.54 mS/cm, depending on the tide level. It can be concluded that the tide level indeed influences the EC parameter in the estuary area. Moreover, TDS plays an important role in regulating EC levels, underscoring the need to systematically measure this parameter in any estuarine water-quality study.

Integrating Artificial Intelligence into Science Education in Primary Schools: A Systematic Literature Review Apriyani, Paramita Putri; Anggriani, Ni Ketut
Indonesian Journal of Elementary and Childhood Education Vol. 6 No. 3 (2025): Edisi September 2025
Publisher : Indonesian Publication Center

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The development of artificial intelligence (AI) has driven significant transformations in learning through adaptive, personalized, and data-driven systems, including in primary education. In elementary science education, AI has the potential to support conceptual understanding and differentiated learning from early stages of cognitive development. This study aims to map research trends, dominant types of AI technologies, pedagogical impacts, and implementation challenges of AI in elementary science learning. A Systematic Literature Review (SLR) was conducted following PRISMA guidelines. Literature searches were carried out in the Scopus, Web of Science, and Google Scholar databases, covering articles published between 2016 and 2025. Of the 312 articles identified, 33 met the inclusion criteria and were analyzed qualitatively. The findings indicate a significant increase in research on AI in elementary science education in the post–COVID-19 period, with adaptive learning technologies and intelligent tutoring systems dominating the field and contributing to improvements in students’ cognitive learning outcomes and learning motivation. However, the use of AI to support higher-order science process skills remains limited. The main challenges include teachers’ pedagogical readiness, infrastructure disparities, and ethical issues related to student data protection. This review highlights the need for more contextual, pedagogically oriented, and sustainable approaches and policies in the integration of AI into elementary science education.

The Effectiveness of Project-Based Learning Models in Enhancing Critical Thinking Skills: A Literature Review Pratiwi, Nanda Aulia; Anggriani, Ni Ketut; Pranahita, Dewa Dwi
Indonesian Journal of Teacher Education Vol. 7 No. 1 (2026): Edisi Januari-Juni 2026
Publisher : Indonesian Publication Center

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Critical thinking skills are essential competencies in the 21st century that students must possess. The Project-Based Learning (PjBL) model is believed to be an effective pedagogical approach to develop these skills. This study aims to describe the trends and effectiveness of the PjBL model in enhancing students' critical thinking skills based on a literature review. This study employs a descriptive literature review approach by analyzing relevant scientific publications from the last ten years. A bibliometric analysis using VOSviewer was also conducted to map research topic trends. The analysis results indicate that research on PjBL and critical thinking has significantly increased. The PjBL model, whether implemented purely or integrated with other approaches such as STEM, is consistently proven effective in enhancing critical thinking skills across various educational levels and subjects. This effectiveness is driven by the PjBL syntax that emphasizes real project-based learning, collaboration, and problem-solving, which directly trains students' metacognitive and analytical aspects.

Critical Thinking and Literacy in the Digital Era: A Literature Review on Essential Skills for 21st Century Learners Anggriani, Ni Ketut; Pratiwi, Nanda Aulia; Pranahita, Dewa Dwi; Apriyani, Paramita Putri; Lestari, Sintya Dewi
Indonesian Journal of Teacher Education Vol. 7 No. 1 (2026): Edisi Januari-Juni 2026
Publisher : Indonesian Publication Center

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The rapid development of digital technology has transformed the way individuals access, process, and utilize information in various aspects of life, including education. In the context of 21st-century learning, students are required to possess digital literacy and critical thinking skills to evaluate information effectively in an increasingly complex digital environment. This study aims to analyze the relationship between digital literacy and critical thinking as essential skills for 21st-century learners. This research employed a Systematic Literature Review (SLR) method by examining 30 scholarly articles published between 2016 and 2025. The data were collected from several academic databases, including Google Scholar, DOAJ, ERIC, and ScienceDirect, using the keywords critical thinking, digital literacy, digital learning, and 21st-century skills. The article selection process followed the PRISMA approach, while thematic analysis was used to identify research patterns and key themes. The results indicate that digital literacy plays a significant role in enabling students to access, understand, and critically evaluate digital information. Furthermore, the integration of digital technology in learning environments can enhance students’ critical thinking skills through activities such as information analysis, online discussions, and collaborative learning. The findings also reveal that digital literacy and critical thinking are closely interconnected and mutually reinforcing competencies that support effective learning in the 21st century. Therefore, integrating these competencies into educational curricula is essential to prepare students for the challenges of the digital era.

Artificial Intelligence in Primary Science Education: A Systematic Literature Review Apriyani, Paramita Putri; Anggriani, Ni Ketut; Gunawan, Gunawan
Indonesian Journal of Innovation and Educational Technology Vol. 1 No. 1 (2026): Edisi Januari-Juni 2026
Publisher : Indonesian Publication Center

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

The development of artificial intelligence (AI) has driven significant transformations in learning through adaptive, personalized, and data-driven systems, including in primary education. In elementary science education, AI has the potential to support conceptual understanding and differentiated learning from early stages of cognitive development. This study aims to map research trends, dominant types of AI technologies, pedagogical impacts, and implementation challenges of AI in elementary science learning. A Systematic Literature Review (SLR) was conducted following PRISMA guidelines. Literature searches were carried out in the Scopus, Web of Science, and Google Scholar databases, covering articles published between 2016 and 2025. Of the 312 articles identified, 33 met the inclusion criteria and were analyzed qualitatively. The findings indicate a significant increase in research on AI in elementary science education in the post–COVID-19 period, with adaptive learning technologies and intelligent tutoring systems dominating the field and contributing to improvements in students’ cognitive learning outcomes and learning motivation. However, the use of AI to support higher-order science process skills remains limited. The main challenges include teachers’ pedagogical readiness, infrastructure disparities, and ethical issues related to student data protection. This review highlights the need for more contextual, pedagogically oriented, and sustainable approaches and policies in the integration of AI into elementary science education.

STEM Integration in 21st-Century Science Education: A Systematic Literature Review Apriyani, Paramita Putri; Anggriani, Ni Ketut; Gunawan, Gunawan
Indonesian Journal of Applied Science and Technology Vol. 6 No. 2 (2025): Edisi Juli-Desember 2025
Publisher : Indonesian

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Technological developments, digitalization, and the demands of 21st-century skills necessitate science education to be more innovative, contextual, and integrative. International reports, such as PISA, underscore the need to enhance students' higher-order thinking skills (HOTS) and scientific literacy. The integration of Science, Technology, Engineering, and Mathematics (STEM) has emerged as a relevant and effective approach. This study aims to analyze the models, strategies, trends, and challenges of implementing STEM integration in science learning through a Systematic Literature Review (SLR) of articles published between 2015 and 2025. The methodology followed the PRISMA guidelines, encompassing identification, screening, and inclusion of articles retrieved from Scopus, Web of Science, ERIC, and Google Scholar databases. From a total of 762 articles, 27 met the inclusion criteria. The results indicate that the Engineering Design Process (EDP), Project-Based Learning STEM (PjBL-STEM), Problem-Based Learning STEM (PBL-STEM), and Integrated STEM models are the most dominantly implemented and have been proven to enhance HOTS, creativity, technological literacy, scientific literacy, and problem-solving skills. Key challenges include teacher competence, limited facilities, and curriculum integration. STEM integration holds significant potential to improve the quality of 21st-century science education. These findings provide practical implications for science teachers in designing contextual, collaborative, and 21st-century skill-oriented STEM learning through the effective utilization of EDP, PjBL-STEM, and digital technologies.

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