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All Journal International Journal of Engineering and Emerging Technology Jurnal Indonesia : Manajemen Informatika dan Komunikasi
I Putu Arich Arthawan
Universitas Pendidikan Nasional
Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering

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Implementation of Data Mining To Predict Period of Students Study Using Naive Bayes Algorithm Ida Bagus Adisimakrisna Peling; I Nyoman Arnawan; I Putu Arich Arthawan; I Gusti Ngurah Janardana
International Journal of Engineering and Emerging Technology Vol 2 No 1 (2017): January - June
Publisher : Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University

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Abstract

The quality of universities, especially study programs in Indonesia is measured based on accreditation conducted by BAN PT. According to BAN PT the quality is measured based on 7 main standards, one of them is Student and Graduate. One of the problems that still be the subject of discussion related to student failure is about the students who graduated not on time. Students graduating not on time are students who can not complete their studies in accordance with the provisions of time given. The existence of a graduate student is not timely of course cause problems and potentially drop out that affect the quality of education and accreditation. A system that predicts students' graduation is required by evaluating their learning outcomes. The timeliness of graduating students can be done with data mining techniques to find graduation patterns of students who have graduated which then used as a basis to predict students' graduation in the next year. This study showed that Naïve Bayes was able to classify the correct data testing on average by 86.16% and 13.84% error. In addition, other information obtained from the data testing used that the students who entered from the PMDK Pass graduated on time as much as 40%, other paths graduated on time by 26.7%, and pass filter exam on time 13.3%.
Sistem IoT Berbasis Edge untuk Pemantauan Kualitas Udara Perkotaan Real-Time I Putu Arich Arthawan; Anak Agung Adi Wiryya Putra
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 7 No. 2 (2026): Mei
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v7i2.1873

Abstract

Air pollution in urban areas has become a serious issue due to rapid urbanization, industrial activities, and the increasing number of motor vehicles, which directly impact human health and the environment. Conventional monitoring systems that rely on cloud-based processing often face challenges such as high latency and limitations in providing real-time information. This study aims to develop an Internet of Things (IoT)-based air quality monitoring system integrated with edge computing to improve data processing efficiency and reduce latency. The proposed system utilizes sensors for PM2.5, carbon monoxide (CO), temperature, and humidity, which are connected to an edge device to perform local data processing before being transmitted to the cloud. The research methodology includes system architecture design, hardware and software implementation, and performance evaluation based on latency, data accuracy, and system responsiveness. The results indicate that the edge-based approach significantly reduces latency compared to cloud-based systems while maintaining high data accuracy. In addition, the system is capable of providing real-time data visualization through a dashboard, enabling faster and more effective decision-making. Therefore, the integration of IoT and edge computing offers an efficient, scalable, and promising solution for urban air quality monitoring and supports the development of smart city applications.
Co-Authors Anak Agung Adi Wiryya Putra I Nyoman Arnawan Ida Bagus Adisimakrisna Peling l Gusti Ngurah Janardana