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Acute respiratory infections (ARI) encompass diseases with epidemic prevalence and mortality (measured number of deaths in a population) worldwide. Several types of diseases are classified as acute respiratory infections (ARI), i.e., pneumonia, diphtheria, tuberculosis, and COVID-19. The Ministry of Health of Indonesia suggests that one of the performance indicators for infectious disease control and management is disease detection. Disease detection constitutes the most significant factor for infectious diseases, and early detection based on the patient's symptoms is essential to classify and treat the diseases. The delayed treatment of these diseases has resulted in many cases and deaths, especially in ARI. Furthermore, to help support the Ministry of Health's program, an expert system was established to detect early acute respiratory infections (ARI) based on the patient's symptoms. Employing a combination of forward chaining and certainty factor as the expert system method could produce a percentage range of system accuracy of 95 to 97.5%. [ABSTRACT FROM AUTHOR]

As one of the largest exporters in the world, cocoa (Theobroma cacao L.) production in Indonesia provides an important contribution to the plantation sector that can, directly and indirectly, attribute to the national economic development. However, recent data shows a decline in cocoa productivity in Indonesia. This is arguably caused by various factors, including poor agricultural management and practices in cocoa plantations, that may lead to lower fertility in the soil and an increased risk of diseases and pests. Potassium deficiency is a major contributing factor to the low soil fertility that affects cocoa yields. Therefore, in this work, we implement an application with an expert system utilizing the forward chaining method to detect potassium deficiency in cocoa plants and then give a fertilization-based recommendation based on the plants' condition. The system employs a set of rules to identify symptoms related to the deficiency on the sample photo of a cocoa leaf according to the channels of red, green, and blue of the image. The sample images of cocoa leaves are submitted to the application with an easy-to-use interface that can show the scanning result and proceed to display the suggested quantity of fertilizers to prevent potassium deficiency. Implementing the system can contribute constructive impacts to improve current practices in the overall cropping system of cocoa plants. [ABSTRACT FROM AUTHOR]

One of the factors causing rice production disturbance in Indonesia is that farmers lack knowledge of early symptoms of rice plant diseases. These diseases are increasingly rampant because of the lack of experts. This study aimed to overcome this problem by providing an Expert System that helps farmers to make an early diagnosis of rice plant diseases. Data of rice plant pests and diseases in 2016 were taken from Samarinda, East Kalimantan, Indonesia using an in-depth survey, and rice experts from the Department of Food Crops and Horticulture of East Kalimantan Province were recruited for the project. The Expert System for Rice Plant Disease Diagnosis, ESforRPD2, was developed based on the pest and disease experiences of the rice experts and uses a Waterfall Paradigm and Unified Modeling Language. This Expert System can detect 48 symptoms and 8 types of diseases of rice plants from 16 data tests with a sensitivity of 87.5%. The system can also provide recommendations for the treatment of identified diseases. ESforRPD2 is available in Indonesian at http://esforrpd2.blog.unmul.ac.id., Competing Interests: No competing interests were disclosed., (Copyright: © 2024 Agus F et al.)

Tuberculosis is a very dangerous infectious disease. Indonesia is one of the countries with a high number of tuberculosis sufferers. According to data collected as of May 17, 2018, there were 420,994 tuberculosis cases found in 2017. Various efforts have been made by the government together with the public and private agencies to control the spread of this tuberculosis disease. Symptoms of pulmonary tuberculosis tend to be difficult to analyze if only based on the signs and symptoms. Therefore we need an expert system that collects the symptoms of a pulmonary tuberculosis expert, so that the user can carry out the diagnosis independently using this expert system without having to go to the health center or health service first. The data needed in this study are in the form of symptoms that are often experienced by pulmonary tuberculosis patients. The development of this expert system uses the Tsukamoto fuzzy method. Of the 7 symptoms that are often experienced by patients with tuberculosis, there are 128 rules in the calculation using the Tsukamoto fuzzy method. The output obtained from this expert system is in the form of a user's diagnosis, whether or not pulmonary tuberculosis is indicated. From the results of the study, the researchers obtained the results for one user with the provision of severe cough for 20 days, high fever for 25 days, shortness of breath for 20 days, decreased appetite for 6 days, weight loss of 4 kg, cold sweat for 15 days and chest pain with grade 6 is a patient not indicated by pulmonary tuberculosis. [ABSTRACT FROM AUTHOR]

The purpose of this research is to combine multimedia elements and mathematics learning material to a mathematic learning interactive application. Research and design methodology that used is Game Development Life Cycle (GDLC) which consist of initiation, pre-production, production, testing and release. Content inside the game is made using gamification and expert system concept. The result of this research is an interactive learning game to support student to understand mathematic materials. The purpose of this application is to help student to learn mathematic in an interactive and interesting way, to deliver mathematic material easily. [ABSTRACT FROM AUTHOR]

The high maternal and infant mortality rates in developing countries, especially Indonesia, are quite alarming. There are many factors that cause high mortality numbers; one of them is the delay in handling cases of high-risk pregnancies. The main problem faced by developing countries is the lack of health facilities, including medical equipment and human resources. This research aims to develop a simple system that can be used to screen high-risk pregnancies. This system is based on an expert system. The Analytical Hierarchy Process (AHP) method is used in making decisions about potentially high-risk pregnancy patients. Essentially, the system can be used by anyone, anywhere, to carry out early screening of high-risk pregnancy patients, so that delays in the treatment of these patients can be resolved, because the symptoms of high-risk pregnancy are known from the beginning. Results indicate that this system shows promise for further development. [ABSTRACT FROM AUTHOR]