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Tijaniyah
Nurul Jadid University

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Decision Support System Method for Selecting Formal Education Levels in a violation student based Microcontroller and IOT Sumantri; Ratri Enggar Pawening; Moh. Jasri; Ilmirrizki Imaduddin; Bambang; Tijaniyah; M. Fadhilur Rahman
Jurnal JEETech Vol. 7 No. 1 (2026): May
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32492/jeetech.v7i1.7106

Abstract

This study develops a decision support system to determine appropriate formal education levels based on student violations using the Multi Attribute Decision Making (MADM) method with the Simple Additive Weighting (SAW) technique. The system integrates a microcontroller and Internet of Things (IoT) technology for real-time data collection and monitoring. Several criteria, including violation frequency, type, behavior, and academic performance, are evaluated and weighted to produce ranking results. The result of the SAW method calculation shows that the third alternative (Senior High School or SLTA) obtained a score of 17.15. This value is the highest compared to the other alternatives. This means that the SLTA level becomes the primary category where smoking violations by students are strictly prohibited. This is because students at the SLTA level tend to exhibit more rebellious behavior and higher ego, causing rules to be sometimes ignored. The microcontroller functions as the control system for cigarette smoke. The sensor used for detection is the MQ-2 gas sensor, which is also highly sensitive to air quality, including CO₂, ammonia, benzene, and cigarette smoke. The Internet of Things (IoT) is used for remote monitoring of cigarette smoke detection in a room. This system utilizes notifications from the Telegram application connected to the principal’s mobile phone.
The Simple Additive Weighting(SAW) Method for Selecting Shrimp Types in a Microcontroller and SolarPanel-Based Shrimp Drying Control System Ahmad Muhtadi; Ahmad Hudawi AS; Ahmad Khairi; Abdul Karim; Honainah; Tijaniyah
Jurnal JEETech Vol. 7 No. 1 (2026): May
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32492/jeetech.v7i1.7110

Abstract

This study applies the Simple Additive Weighting (SAW) method to select shrimp types in a microcontroller and solar panel-based shrimp drying control system. The aim is to enhance drying efficiency by determining the most suitable shrimp type based on multiple criteria, including moisture content, shrimp size, drying time, temperature, and humidity. The system uses sensors to monitor environmental conditions in real time and a microcontroller to automate the drying process, while solar panels provide a sustainable energy source. The SAW method evaluates each alternative by normalizing criteria values and calculating preference scores to produce a final ranking. the solar panel-based shrimp drying control system provides an efficient and sustainable solution for the drying process. By integrating sensors, a microcontroller, and automatic actuators, the system can maintain optimal temperature, humidity, and airflow. The electrical energy generated from the solar panel reaches a maximum of 90 within 5 hours. Based on the SAW method calculation, the highest value is obtained by rebon shrimp (Acetes Shrimp) as Alternative 5, with a score of 18.16. Meanwhile, the lowest humidity value measured by the sensor is 10.5% RH, indicating that the drying chamber has reached optimal conditions, allowing the shrimp to dry properly without spoilage
Co-Authors Abdul Karim Ahmad Hudawi AS Ahmad Khairi Ahmad Muhtadi Bambang Honainah Ilmirrizki Imaduddin M. Fadhilur Rahman Moh. Jasri Ratri Enggar Pawening Sumantri