Rahmi Andarini
Universitas Multimedia Nusantara

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Analisis Perhitungan Beban Pendinginan Ruang Dhammasala Vihara Padumuttara menggunakan Metode CLTD Ananda Karuna Jaya; Caesar Ondolan Harahap; Rahmi Andarini
Ultima Computing : Jurnal Sistem Komputer Vol 12 No 2 (2020): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v12i2.1709

Abstract

Dhammasala room of Padumuttara Temple has an indoor temperature of 28,56oC and relative humidity of 80,6%. According to SNI 03-6572-2001 and a previous literature study, this temperature is outside the thermal comfort zone for tropical climate. Aiming to improve thermal comfort of Dhammasala room with an HVAC system efficiently, the cooling load of the room is analyzed using the Cooling Load Temperature Difference (CLTD) method. The results are also compared with results from other cooling load calculation sofware. The recommended HVAC System for Dhammasala room of Padumuttara Temple is a chiller with a capacity of 30-40TR.
The Development of an IoT-based Indoor Air Monitoring System Towards Smart Energy Efficient Classroom Moeljono Widjaja; Dareen Kusuma Halim; Rahmi Andarini
Ultima Computing : Jurnal Sistem Komputer Vol 14 No 1 (2022): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v14i1.2565

Abstract

Indoor air quality has become a crucial issue, specifically during COVID 19 pandemic. The good indoor air quality will lead to occupants’ comfort condition, thus affecting their productivity. Indoor air temperature and relative humidity are two essential components of thermal comfort. This paper presents the development of a temperature and relative humidity monitoring system for the classroom using the Internet of Things (IoT). This system consists of three main components: logger nodes, a gateway logger, and an interconnected cloud server. The logger node (ESP8266 / ESP32 microcontroller and DHT22 sensor) is a device at the edge of the IoT system and is placed at the monitoring location. The logger gateway is built on a Raspberry Pi 4, which serves as an intermediate server. It receives periodic data (temperature and humidity) from the logger nodes through the publish-subscribe MQTT protocol and sends it to the MongoDB Atlas cloud database. The logger gateway saves all received logs into the SQLite database as temporary local storage and then uploads the data to the MongoDB Atlas cloud at a predefined interval. The MongoDB data is then displayed on a monitoring dashboard using MongoDB charts. The logger node with the DHT22 sensor has been adjusted using a linear model and successfully tested to monitor indoor and outdoor air conditions with satisfactory results. The recorded data has also been successfully modeled using the Gaussian Mixture Model and a simple Fuzzy model. These models can capture the dynamic of air condition in the room and predict the state of the cooling system.