Muhammad Fikry
Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Japan

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Optimizing Multi-Time Notifications Using Q-Learning Muhammad Fikry; Muhammad Iqbal
Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS) Vol. 3 (2022): Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MI
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/micoms.v3i.42

Abstract

In this research, we propose time optimization for notifications to assist users in remembering their actions by taking into consideration the amount of time it takes for them to respond and react. Using the Q-Learning algorithm, this proposal calculates when the best time to send notifications to users' smartphones in order to remind them of something important. The time at which the message is sent will be adjusted depending on the replies of prior users, which may be transformed into feedback at any time that is convenient. Notifications will be sent out, either repetitively or not, depending on the appropriate time for each individual, with the goal of ensuring that users do not forget about activities that they have planned. The results of testing our technique using the dataset show that it may be used to improve the time at which notifications are issued to recipients. It is possible to experiment with a variety of different times for the delivery of alerts in order to determine which of these periods is most successful for prompting users to take action. As a consequence of this, the algorithm is able to accommodate specific characteristics of individuals and find solutions to problems using a variety of standard operating procedures. Our proposal has the potential to successfully maintain the notification execution time at the intended level, which will prevent users from becoming concerned about the volume of notifications. Users who do not see the notification initially have the opportunity to do so at a later time step, which guarantees that activity data will still be collected.
Indoor Thermal Comfort Improvement of the Naturally Ventilated House in Tropical Climate, Indonesia Muhammad Iqbal; Muhammad Dastur; Muhammad Fikry
Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS) Vol. 3 (2022): Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MI
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/micoms.v3i.48

Abstract

Two types of houses in North Aceh, Indonesia, are investigated in this study. Even though the hot and humid conditions throughout the year, most Indonesian stay in a house that uses natural ventilation due to energy poverty and economic conditions. Commonly, they rely on natural ventilation by opening windows to achieve thermal comfort in the indoor environment. Therefore, an on-site survey and questionnaire were performed on more than 240 occupants and 115 naturally ventilated houses to investigate thermal comfort performance between two houses based on thermal sensation vote (TSV) and thermal comfort vote (TCV). In addition, some questions related to thermal preference and body response are employed. This study also examines thermal comfort with a numerical simulations program called THERB for HAM, a coupled analysis software for heat, moisture, and air. The results show that the room comfort level was not optimal, where most occupants' feelings were warm and hot. However, type 1 is more comfortable than type 2, and simulation results confirm indoor environmental conditions. Furthermore, this study presents the adaptive behavior, where most occupants utilize the windows openings in the morning until noon and operate the fans during the night to modify indoor environment conditions to be more comfortable.