Web-based rule-based system for early detection of anemia among pregnant mothers

Anemia among pregnant mothers is a serious issue that may cause pregnancy complications, premature birth that can lead to mortality, and low birth weight (BBLR). Monitoring for anemia among pregnant mothers is quite a phenomenon for midwives and health professionals due to time constraint as it takes time to establish a proper diagnosis. Late diagnosis establishment results in late treatment. Therefore, this paper proposes a web-based rule-based information system using the rule-based algorithm to ease monitoring and detection of anemia among high risk pregnant mothers. The method employed is online rule-based information system to diagnose anemia among pregnant mothers. Respondents input data of symptoms that will then be processed by the information system to generate diagnoses. Resulting diagnoses are displayed as they are. The rule-based method in the information system validates data of symptoms and diagnoses with experts in the field to serve as reference in providing health care information. This is a pre-experimental research with one posttest group. The intervention group (N=10) was given treatment using the information system, while the control group (N=10) was given treatment manually. Interventions were conducted for 20 days, and measurements were carried out on the 21st day using the Technology Acceptance Model (TAM). The anemia detection system for pregnant mothers developed here is proven to be effective in helping anemia detection and has been validated by experts (midwives) and hence, been declared valid. With effectiveness score of 90 %, this web-based rule-based information system is effective in detecting, monitoring, and reporting anemia among pregnant mothers.