Expert System for Diagnosing Pregnancy Complaints by Forward Chaining

Wati, Embun Fajar; Puspitasari, Anggi

doi:10.33395/sinkron.v5i1.10593

Cited by 3 publications

(3 citation statements)

References 5 publications

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“…In this technique data is used to decide which rule to execute. The process is repeated several times until the results are obtained [26].…”

Section: Forward Chaining Methodsmentioning

confidence: 99%

Expert System for Detection of Diseases in Layers Using Forward Chaining and Certainty Factor Methods

Febrianto,

Udayanti,

Indriyono

et al. 2023

JMASIF

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Inaccuracies in the process of diagnosing a type of disease result in errors in handling so that it will pose a risk of death. Accurate diagnostic process results require a high level of confidence so that the results are truly convincing. Current technological developments are making more and more mindsets for the development of information technology in the field of computerization born. One of them is an expert system. This expert system is often used to analyze disease in laying hens. The deficiency in previous research is that there is no degree of confidence so what happens is that the diagnosis often only uses the value of the expert. The role of the system user is only to select the available symptoms without giving the weighted value of the selected symptoms. This study aims to build an expert system capable of detecting symptoms in laying hens by assigning a degree of confidence to each symptom. The system is built with a combination of forward chaining techniques with a certainty factor, the weight value is based on a combination of the weight of symptoms from users and experts to anticipate conditions that are not ideal. Several stages in the research include data collection, knowledge base modeling, implementation into applications and testing. The conclusion that can be drawn from the trial results is that the system can show a maximum validity value of up to 100% when compared to manual calculations.

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“…In this technique data is used to decide which rule to execute. The process is repeated several times until the results are obtained [26].…”

Section: Forward Chaining Methodsmentioning

confidence: 99%

Expert System for Detection of Diseases in Layers Using Forward Chaining and Certainty Factor Methods

Febrianto,

Udayanti,

Indriyono

et al. 2023

JMASIF

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“…Several studies have developed an expert system for early detection of pregnancy disorders and complications. Basiroh [9], Embun F.wati [10], and Abdillah [11] created an expert system to detect pregnancy disorders and complications using the forward chaining method. Maylawati [12] designed an expert system using Artificial Neural Network to diagnose pregnancy complications.…”

Section: Introductionmentioning

confidence: 99%

Electromedical Device And Expert System for Early Detection of Hyperemesis Gravidarum

Fitrilina,

Ganesha,

Handayani

et al. 2023

JNTE

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Hyperemesis Gravidarum (HG) is a pregnancy complication that is often overlooked as it is typically considered normal. If HG is not properly treated, nutrition will not be fulfilled which can negatively affect maternal and fetal health and even maternal and fetal death. The exact cause of HG is not identified, so there are no effective preventive methods. However early detection can help for prompt and appropriate treatment. Therefore, a monitoring system for pregnancy conditions was designed for HG early detection. This system employs the MPX5050 DP pressure sensor for measuring blood pressure, the MAX30100 for assessing maternal heart rate and oxygen saturation, the MAX4466 sensor for monitoring fetal heart rate, and an expert system using the certainty factor method to diagnose the probability of hyperemesis gravidarum. The expert system achieves an accuracy of 93.33%. In comparison to the aneroid sphygmomanometer, the designed sphygmomanometer reveals a mean difference of 3.5 mmHg for diastolic pressure, with a standard deviation below 8 mmHg for both systolic and diastolic pressures. The measurement of heart rate and oxygen saturation has a deviation of 1.8 % and 1.02 % respectively. These deviations align with the standards specified by the Ministry of Health for medical devices. For the fetal heart rate, the mean deviation is 3.4 bpm, and the measurement error is 2.38%. Thus, this system can be utilized to monitor pregnancy conditions, enabling the early detection of hyperemesis gravidarum

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“…Appliedly, the forward chaining method is easy to use and can provide good recommendations to users (Ardiansah, Efatmi, Mardawati, & Putri, 2020). The results of the application of the forward chaining method show the maximum level of accuracy (Susanto, Fadlil, & Yudhana, 2020) (Imamah, Agustiono, Rochman, & Firdaus, 2020) (Wati & Puspitasari, 2020). The forward chaining method is successfully applied to the system being developed to identify users based on their knowledge base.…”

Section: Introductionmentioning

confidence: 99%

Development of Expert System Application to Detect Chicken Disease using the Forward Chaining Method

Ramadan,

Harahap,

Muti’ah

2023

SinkrOn

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Chicken is the most widely kept and consumed poultry in Indonesia. Due to the large population of poultry, a variety of diseases have also emerged, from minor diseases to diseases that can kill chickens and infect humans. As a result of these diseases, there are implications for the losses suffered by chicken farmers. Most farmers find it very difficult to identify chicken diseases due to their lack of knowledge. On the other hand, expecting treatment from a veterinarian or expert is very limited and expensive. Therefore, a system is needed that can easily help chicken farmers detect diseases in their pet chickens. This research aims to build an expert system to detect chicken diseases by applying the forward chaining method. The expert system is implemented as a web-based application. The research stages start with identifying problems, collecting data, creating a knowledge base and production rules, building applications, and getting results. The results showed that the forward chaining method provides convenience in detecting chicken diseases. This is proven by only selecting the symptoms of the disease that appear, and then the application will provide conclusions regarding what type of disease is being suffered by chickens. In addition, this application also provides information related to ways of handling and control that can be done to overcome the chicken disease. Hopefully, the results of this research can facilitate chicken farmers in identifying and handling diseases effectively and efficiently.

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Expert System for Diagnosing Pregnancy Complaints by Forward Chaining

Cited by 3 publications

References 5 publications

Expert System for Detection of Diseases in Layers Using Forward Chaining and Certainty Factor Methods

Expert System for Detection of Diseases in Layers Using Forward Chaining and Certainty Factor Methods

Electromedical Device And Expert System for Early Detection of Hyperemesis Gravidarum

Development of Expert System Application to Detect Chicken Disease using the Forward Chaining Method

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