Personalized medication reminder in m-health environment using rule-based expert system / Tengku Azuani Tengku Mohd Zabri

Tengku Mohd Zabri, Tengku Azuani (2015) Personalized medication reminder in m-health environment using rule-based expert system / Tengku Azuani Tengku Mohd Zabri. Degree thesis, Universiti Teknologi MARA.


People have an intention to take medication as instructed, but failing to do so because of forgetful and careless. This is the major problem with unintentional medication non-adherence. Besides that, this problem will lead to slower recovery process and skew the clinical therapy. Moreover, non-adherence attitudes may increase when patient slowly lose their trust in medication and doctors because a patient may start to think that the diagnosis is wrong or prescribed medication is not effective on them.
In addition, people with chronic illness where have to deal with multiple dosage at the different time everyday tends to have this kind of problem. Thus, in order to promote medication adherence among chronic illness patient, this project is going to build a personalized medication reminder in Malay language on Android mobile application. This application will provide a monitor or remind the user about medication time within safe interval time. Meanwhile, a rule-based expert system method is going to be used for implementing this project with emphasis on personalized medication reminder. Agile approach is used in the project framework because of the flexible adjustment in the future. As the result, the application is able to remind users on medication time intake together with instruction details. This application hopefully may be able to strengthen medication adherence among user. It
also might helpful for users to sort medication schedule and easier to handle since it is on their smartphone. As for future work, there are several enhancements could be done like flexible in frequency intake not just for daily medicine, support timecritical scheduled medication, available in other native language and other mobile
platform, associated with user daily activity to support event-based on memory and last but not least provide audio or visual guiding that friendly to senior and disable people.


Item Type: Thesis (Degree)
Email / ID Num.
Tengku Mohd Zabri, Tengku Azuani
Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Soft computing
Divisions: Universiti Teknologi MARA, Melaka > Jasin Campus > Faculty of Computer and Mathematical Sciences
Keywords: Expert system; Rule-based; Medication reminder
Date: 2015
Edit Item
Edit Item


[thumbnail of TD_TENGKU AZUANI TENGKU MOHD ZABRI CS 15_5.pdf] Text

Download (148kB)

Digital Copy

Digital (fulltext) is available at:

Physical Copy

Physical status and holdings:
Item Status:

ID Number




Statistic details