@article {10.3844/jcssp.2013.733.739,
article_type = {journal},
title = {The Development of Expert Mood Identifier System using Fuzzy Logic on Blackberry Platform},
author = {George, Octavia and Gorethi, Maria and Riswandi, Syerra and Budiharto, Widodo},
volume = {9},
number = {6},
year = {2013},
month = {Jun},
pages = {733-739},
doi = {10.3844/jcssp.2013.733.739},
url = {https://thescipub.com/abstract/jcssp.2013.733.739},
abstract = {In our daily life, deciding what caused the bad mood is not easy. This study will design an Expert Mood Identifier System for mobile application. We propose a model that uses 6 variables as the inputs, they are intensity of Sleep (SL), intensity of Eat (ET), hours of using Phone (PH), Spare Time (ST), intensity of Sensitive (SN), intensity of Confidence (CF). These inputs, using Sugeno fuzzy logic, are then fuzzificated to linguistic variables, so that they able to evaluated with the if-then rules. Result of the evaluation will show the highest possibility causes either in Love (LV) or density schedule. It will be defuzzificated to a crisp number showing the percentage of what causes it. The experiment results are presented and show the Mood Identifier system is running well on BlackBerry platform and can be used successfully to identify the causes of bad mood with a solution for each case.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}