Profile matching is one of the methods in the Decision Support System, but in this study the profile matching method is used for expert systems, namely for diagnosing digestive disorders in children aged 0 to 7 years, the input data is symptom data while the output is in the form of diagnosis results in the form of a percentage of types of disorders. digestion. The process of profile matching is to determine the weight of the criteria for each symptom, create a knowledge base/ideal profile, determine the weight of the gap, determine the core factor and secondary factor, calculate the gap for each input symptom with the symptoms in the knowledge base, determine the weight of each gap, calculate the core score factor and secondary factor, ranking with a weight of 60% core factor and 40% secondary factor. The results of the study show that the profile matching method can be used to create an expert system for diagnosing digestive disorders in children with an accuracy value of 82%.
Mengetahui Credit scoring dari nasabah adalah hal yang sangat penting bagi bank yang yang memberikan layanan perkreditan sebagai upaya untuk mencegah kredit macet. Algoritma CART adalah salah satu algoritma yang digunakan untuk memberikan klasifikasi terhadap suatu pola keterkaitan variabel yang menjadi independent variabel. Pada penulisan ini dimaksudkan untuk menggali pengetahuan tentang pola keterkaitan antara variabel-variabel peubah sehingga dapat diketahui apakah nasabah masuk dalam kategori Credit scoring yang baik atau buruk atau dalam hal ini bad or good.
Montessori is a learning method to stimulate children to reach their potential in all fields. In the field of reading literacy, one of the initial stages is how to stimulate initial reading skills, starting with introducing letters using the syllable learning method. The stimulation process must be in a fun and non-boring way of playing exploration so that children will not feel that they are learning, especially in the current state of the COVID-19 pandemic, where the learning process becomes boring for children because it has to be done at home. just. The purpose of this study is to create a learning technology in the form of an electronic Montessori Sand Board Letter (SBL) Puzzle for Indonesian syllables that can help stimulate early childhood according to the Montessori principle in recognizing syllables. The system development method uses the System Development Life-Cycle (SDLC) method. Based on the results of functional testing using the black box method, it is stated that the entire functional system is 100% functioning according to the system design. The results of testing and validation by Montessori practitioners state that the system has been made according to Montessori rules. Based on the results of usage observations, the Montessori Sand Board Letter (SBL) electronic puzzle for 85% Indonesian syllables can stimulate children's ability to recognize Indonesian syllables
A patient should not be in a psychologically worrisome condition for fear of lowering the temperature causing slow healing to last a long time. Prolonged anxiety will develop into stress, so it is very necessary to detect anxiety early before anxiety persists and results in stress. However, these anxiety symptoms are related to the same psychological factors and contain uncertainties that cannot always be controlled and monitored by doctors. The purpose of this research is to create a system that can monitor the patient's anxiety symptoms in real-time based on the Internet of Things (IoT) so that doctors can determine the right treatment to maintain the patient's psychological condition. The system detects responses in humans when someone feels anxious, namely heart rate, body temperature, and sweat intensity which are detected using sensors. The information obtained from the sensor becomes input parameters which are then processed using fuzzy logic to detect early symptoms. Fuzzy logic was chosen because it is a method for solving fuzzy problems with the uncertainty of the threshold value of symptom change. The output is in the form of anxiety symptoms which are divided into 3 (three) symptoms, namely normal, mild, and severe. The research method used is the SDLC (System Development Life-Cycle) method. the results based on the black box test state that the entire functional system works according to its function, the white box test results state that all logic is correct and appropriate. The results showed that the system that had been built succeeded in monitoring anxiety in patients with a system accuracy of 98%.
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