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All Journal Al-Kimia Journal of Computer Networks, Architecture and High Performance Computing
Hazimah
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Chemistry Computer Science & IT Education

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Stigmasterol (Steroid) From Leaves of Solanum ferox L (Sour Eggplant) Plant Hazimah; Fadhli, Haiyul; Fitriyah, Dina
Al-Kimia Vol 11 No 1 (2023): JUNE
Publisher : Study Program of Chemistry - Alauddin State Islamic University of Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/al-kimia.v11i1.35337

Abstract

Solanum ferox L is a vegetable that is often used as a flavor in cooking that belongs to the Solanaceae family. Solanum ferox L contains terpenoids, steroids, flavonoids, alkaloids, and phenolic compounds. Solanum ferox has various bioactive compounds used as antirheumatic, antiasthma, antiviral, anticancer, and antibacterial. The aim of this study was to isolate and characterize the stigmasterol compound from the Solanum ferox plant. The compound was elucidated by UV, IR, and NMR spectroscopy and was named HSF. The HSF compound has the chemical formula C29H48O and the name is Stigmasterol.
IoT-Based Smart Air Quality System: A Real-Time Monitoring Solution for Indoor Air Quality Candra, Joni; Hazimah
Journal of Computer Networks, Architecture and High Performance Computing Vol. 8 No. 1 (2026): Call for Paper for Machine Learning / Artificial Intelligence, Januari 2026
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v8i1.7173

Abstract

Indoor Air Quality (IAQ) plays a crucial role in maintaining human health and comfort. This study aims to design and implement an Internet of Things (IoT)-based indoor air quality monitoring system integrated with a mobile application for real-time observation. The system employs sensors to measure environmental parameters such as temperature, humidity, and carbon dioxide (CO?) levels, with data transmitted wirelessly and visualized through the mobile app. The applied method includes hardware design, IoT-based software development, and system testing in several rooms with different activity conditions. The implementation results show that the system can accurately display air quality data and provide automatic notifications when pollutant levels increase. Based on seven days of measurement, the kitchen area indicated a “Poor Air” category, while the living room and bedroom were classified as “Fresh Air.” This system effectively delivers fast and accurate air quality information, enabling users to take preventive actions to maintain healthy indoor air conditions
Co-Authors candra, joni DINA FITRIYAH Haiyul Fadhli