scholarly journals Penerapan Artificial Intelligence dalam Mendiagnosa Penyakit Akibat Parasit Nyamuk Dengan Metode Dempster Shafer

2021 ◽  
Vol 1 (2) ◽  
pp. 141-146
Author(s):  
Ragil Monicha Winahyu ◽  
Iqbal Kamil Siregar ◽  
Masitah Handayani
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Typhoid Fever ◽  
Health Center ◽  
Web Applications ◽  
Hemorrhagic Fever ◽  
Climatic Conditions ◽  
Tropical Diseases ◽  
Sick People ◽  
Breeding Grounds

Abstract : The climatic conditions in Indonesia are very vulnerable to the formation of breeding grounds for disease populations. There are many types of diseases that generally occur due to mosquito parasites including Dengue Hemorrhagic Fever (DHF), Typhoid Fever, Measles (Morbili), Malaria, and several other tropical diseases. Information from doctors is needed by all sick people, but is constrained by the problem of costs for such expensive treatment. That is the reason for making an expert system that can diagnose mosquito parasitic fever. This designed system uses the Dempster.- Shafer method. Dempster-shafers can be used to combine separate pieces of information to calculate one by one the probability of an event occurring. This application can diagnose diseases caused by mosquito parasites by entering the symptoms of the questions answered by the patient and getting maximum results. The system can run on web applications such as Google Chrome and Mozilla.The research was conducted at the Simpang Empat Health Center, Asahan Regency.         Keywords : Mosquito; Dempster Shafer; Health Center  Abstrak : Kondisi iklim yang ada di Indonesia sangat rentan dengan pembentukan tempat berkembang biaknya populasi penyakit.  Ada banyak jenis penyakit yang pada umumnya terjadi yaitu akibat parasit nyamuk diantaranya Demam Berdarah Dengue (DBD),  Demam Tifoid, Campak (Morbili), Malaria, dan beberapa penyakit tropis lainnya. Informasi dari dokter dangat dibutuhkan oleh semua orang sakit, namun terkendala masalah biaya untuk perobatan yang begitu mahal. Itulah yang menjadi alasan untuk dibuatnya sebuah sistem pakar yang dapat mendiagnosa penyakit demam parasit nyamuk. Sistem  yang dirancang ini menggunakan metode Dempster.- Shafer. Dempster-shafer bisa digunakan untuk menggabungkan potongan-potongan informasi yang terpisah untuk menghitung satu persatu kemungkinan yang terjadi dari suatu peristiwa. Aplikasi ini bisa mendiagnosis penyakit  akibat parasit nyamuk dengan memasukkan gejala pertanyaan yang dijawab oleh pasien dan mendapatkan hasil yang maksimal. Sistem dapat berjalan pada aplikasi web seperti google crhrome dan mozilla. Penelitian dilaksanakan di Puskesmas Simpang Empat Kabupaten Asahan. Kata Kunci : Nyamuk; Dempster Shafer; Puskesmas

SISTEM PAKAR MENDIAGNOSA VIRUS MAYORA DENGAN METODE VARIABLE CENTERED INTELLIGENT RULE SYSTEM (VCIRS)

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Siti Nurhena ◽  
Nelly Astuti Hasibuan ◽  
Kurnia Ulfa
Keyword(s):  
Artificial Intelligence ◽  
Immune System ◽  
Expert System ◽  
Expert Systems ◽  
Dengue Hemorrhagic Fever ◽  
Hemorrhagic Fever ◽  
Visual Basic ◽  
Artificial Intelligence Techniques ◽  
Individual Needs ◽  
Rule System

The diagnosis process is the first step to knowing a type of disease. This type of disease caused by mosquitoes is one of the major viruses (MAVY), dengue hemorrhagic fever (DHF) and malaria. Sometimes not everyone can find the virus that is carried by this mosquito, usually children who are susceptible to this virus because the immune system that has not been built perfectly is perfect. To know for sure which virus is infected by mosquitoes, it can diagnose by seeing symptoms perceived symptoms. Expert systems are one of the most used artificial intelligence techniques today because expert systems can act as consultations. In this case the authors make a system to start a diagnosis process with variable centered intelligent rule system (VCIRS) methods through perceived symptoms. With the facilities provided for users and administrators, allowing both users and administrators to use this system according to their individual needs. This expert system is made with the Microsoft Visual Basic 2008 programming language.Keywords: Expert System, Mayora Virus, Variable Centered Intelligent Rule System (VCIRS)The diagnosis process is the first step to knowing a type of disease. This type of disease caused by mosquitoes is one of the major viruses (MAVY), dengue hemorrhagic fever (DHF) and malaria. Sometimes not everyone can find the virus that is carried by this mosquito, usually children who are susceptible to this virus because the immune system that has not been built perfectly is perfect. To know for sure which virus is infected by mosquitoes, it can diagnose by seeing symptoms perceived symptoms.Expert systems are one of the most used artificial intelligence techniques today because expert systems can act as consultations. In this case the authors make a system to start a diagnosis process with variable centered intelligent rule system (VCIRS) methods through perceived symptoms.With the facilities provided for users and administrators, allowing both users and administrators to use this system according to their individual needs. This expert system is made with the Microsoft Visual Basic 2008 programming language.Keywords: Expert System, Mayora Virus, Variable Centered Intelligent Rule System (VCIRS)

scholarly journals Spasial Autokorelasi Sebaran Demam Berdarah Dengue Di Kecamatan Ambarawa

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Kartika Dian Pertiwi ◽  
Ita Puji Lestari
Keyword(s):  
Health Center ◽  
Geographical Location ◽  
Secondary Data ◽  
Population Data ◽  
Hemorrhagic Fever ◽  
Primary Data ◽  
Mosquito Nets ◽  
Ceiling Temperature ◽  
Global Positioning ◽  
Breeding Grounds

Incidence of Dengue Hemorrhagic Fever (DHF) in Ambarawa increased significantly during 20118-2019. In 2018 there were 19 DHF events, and in 2019 there were 124 DHF events. This study was conducted to determine the spatial distribution of dengue spread and environmental conditions associated with breeding grounds, resting places, installations, holes in walls, ceiling, temperature, humidity, air pressure, the use of mosquito nets in 2019.This research is a descriptive study with ecological studies. The population of this study was all DHF events in the working area of Ambarawa Health Center from 2018-2019 with the criteria to have a clear address with a total of 130 DHF events. This study uses secondary data containing DHF event data from Ambarawa Health Center and population data in the working area of Ambarawa Health Center in 2018-2019 and primary data related to the geographical location of DHF events. As a research instrument used is a questionnaire table, Environmental observation sheet, Global Positioning System (GPS), thermogygrometer. The results obtained from the pattern of the spread of DHF events in the working area of Ambarawa Health Center in 2018 were patterned spread with NNI 1.4 in 2018 and grouped (grouped) with NNI 0,000258 in 2019. The extent of the distribution of DHF events in Ambarawa was from in 2018-2019 the more widespread with the discovery of dengue patients in all kelurahan in 2019 after not found dengue patients in Baran and Bejalen villages in 2018. Dissemination of DHF information in Ambarawa from 2018-2019 can be found in Kupang District, spreading DHF patterned distribution (disbanded) in 2018 and in groups (in groups) in 2019 with the value of the NNI getting smaller.

scholarly journals Putting the world back to work: An expert system using big data and artificial intelligence in combating the spread of COVID-19 and similar contagious diseases

Work ◽  
2020 ◽  
Vol 67 (3) ◽  
pp. 557-572
Author(s):  
Said Tkatek ◽  
Amine Belmzoukia ◽  
Said Nafai ◽  
Jaafar Abouchabaka ◽  
Youssef Ibnou-ratib
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Expert System ◽  
Population Monitoring ◽  
High Definition ◽  
Contagious Diseases ◽  
The World ◽  
General Guide ◽  
The Impact ◽  
Back To Work

BACKGROUND: To combat COVID-19, curb the pandemic, and manage containment, governments around the world are turning to data collection and population monitoring for analysis and prediction. The massive data generated through the use of big data and artificial intelligence can play an important role in addressing this unprecedented global health and economic crisis. OBJECTIVES: The objective of this work is to develop an expert system that combines several solutions to combat COVID-19. The main solution is based on a new developed software called General Guide (GG) application. This expert system allows us to explore, monitor, forecast, and optimize the data collected in order to take an efficient decision to ensure the safety of citizens, forecast, and slow down the spread’s rate of COVID-19. It will also facilitate countries’ interventions and optimize resources. Moreover, other solutions can be integrated into this expert system, such as the automatic vehicle and passenger sanitizing system equipped with a thermal and smart High Definition (HD) cameras and multi-purpose drones which offer many services. All of these solutions will facilitate lifting COVID-19 restrictions and minimize the impact of this pandemic. METHODS: The methods used in this expert system will assist in designing and analyzing the model based on big data and artificial intelligence (machine learning). This can enhance countries’ abilities and tools in monitoring, combating, and predicting the spread of COVID-19. RESULTS: The results obtained by this prediction process and the use of the above mentioned solutions will help monitor, predict, generate indicators, and make operational decisions to stop the spread of COVID-19. CONCLUSIONS: This developed expert system can assist in stopping the spread of COVID-19 globally and putting the world back to work.

scholarly journals HUBUNGAN PERILAKU MASYARAKAT DALAM PEMBERANTASAN SARANG NYAMUK DAN FAKTOR LINGKUNGAN DENGAN KEJADIAN DEMAM BERDARAH DENGUE DI WILAYAH PUSKESMAS I DENPASAR SELATAN DAN PUSKESMAS I DENPASAR TIMUR

2016 ◽  
Vol 10 (1) ◽  
pp. 17
Author(s):  
Dwi Jata ◽  
Nyoman Adi Putra ◽  
I.B.G. Pujaastawa
Keyword(s):  
Public Health ◽  
Health Center ◽  
Sampling Method ◽  
Hemorrhagic Fever ◽  
Total Sample ◽  
Cross Sectional ◽  
Public Health Center ◽  
Community Behavior ◽  
Service Need

Dengue hemorrhagic fever (DHF) is one of diseases that causes health problems in Indonesia and oftenly creates extraordinary events with great death. The purpose of this research is to discover relationship community behavior in mosquito nesting eradication and environmental factors with DHF incidence in 1st Public Health Center Denpasar Selatan and 1st Public Health Center Denpasar Timur. The research design used is observational, cross-sectional. Total sample of 82 households. Sampling was done in proportion sampling method. Results of the analysis of environmental variables associated with DHF incidence in 1st Public Health Center Denpasar Selatan: occupant density (p = 0.02), mobility (p = 0.01), the habit of hanging clothes (p = 0.04). 1st Public Health Center Denpasar Timur: mobility (p = 0.00), clogged water ditches (p = 0.00), containers water existance (p = 0.03), the habit of hanging clothes (p = 0.00). Knowledge, attitude and actions in 1st Public Health Center Denpasar Selatan and 1st Public Health Center Denpasar Timur statistically correlated with DHF incidence. As conclusion of the research results, in 1st Public Health Center Denpasar Selatan and 1st Public Health Center Denpasar Timur, that is mobility, the habit of hanging clothes, knowledge, attitude and actions strongly related with DHF incidence, while that is clogged water ditches, containers water existance and occupant density has no relation with DHF incidence. Public Health Center need to intensify health promotion, improves the quality of MNE (PSN), and the Provincial Health Service need to support Public Health Center on setting policies which necessary.

Treatment of Uncertainty in an Oncology Protocol by Probabilistic and Artificial Intelligence Approaches

1988 ◽  
Vol 27 (01) ◽  
pp. 23-33 ◽  
Author(s):  
Fiorella de Rosis ◽  
G. Steve ◽  
C. Biagini ◽  
R. Maurizi-Enrici
Keyword(s):  
Artificial Intelligence ◽  
Sensitivity Analysis ◽  
Expert System ◽  
Probabilistic Model ◽  
Decision Process ◽  
Clinical Decision ◽  
Final Diagnosis ◽  
Decision Models ◽  
Expert System Shell ◽  
Subjective Estimation

SummaryThe decision process for diagnosis and treatment of Hodgkin’s disease at the Institute of Radiology of Rome has been modelled integrating the guidelines of a protocol with uncertainty aspects. Two models have been built, using a PROSPECTOR-like Expert System shell for microcomputers: the first of them treats the uncertainty by the inferential engine of the shell, the second is a probabilistic model. The decisions suggested in a group of simulated and real cases by a section of the two models have been compared with an “objective” final diagnosis; this analysis showed that, in some cases, the two models give different suggestions and that “approximations” of the shell’s inferential engine may induce wrong conclusions. A sensitivity analysis of the probabilistic model showed that the outputs are greatly influenced by variations of parameters, whose subjective estimation appears to be especially difficult. This experience gives the opportunity to consider the risks of building clinical decision models based on Expert System shells, if the assumptions and approximations hidden in the shell have not been previously analyzed in a careful and critical way.

Construction Research of Exercise Prescription Expert System

2013 ◽  
Vol 718-720 ◽  
pp. 2422-2426
Author(s):  
Ming Gou ◽  
Jing Yang
Keyword(s):  
Artificial Intelligence ◽  
Information Processing ◽  
Expert System ◽  
Exercise Prescription ◽  
Scientific Model ◽  
Test Database

The test database of students' health is being analyzed with the information processing tool of artificial intelligence Expert System in order to create a scientific model of students Exercise Prescription in the end. It aims at starting with studying every student to realize an optimized development for the quality potential of every student.

scholarly journals Diagnosa Penyakit Demam Berdarah Dengue (DBD) menggunakan Metode Learning Vector Quantization (LVQ)

2020 ◽  
Vol 4 (3) ◽  
pp. 56
Author(s):  
Firman Tawakal ◽  
Ahmedika Azkiya
Keyword(s):  
Neural Network ◽  
Typhoid Fever ◽  
Vector Quantization ◽  
Dengue Hemorrhagic Fever ◽  
Hemorrhagic Fever ◽  
Learning Vector Quantization ◽  
Mean Square ◽  
Northern Australia ◽  
Neural Network Learning ◽  
Network Learning

Dengue Hemorrhagic Fever is a disease that is carried and transmitted through the mosquito Aedes aegypti and Aedes albopictus which is commonly found in tropical and subtropical regions such as in Indonesia to Northern Australia. in 2013 there are 2.35 million reported cases, which is 37,687 case is heavy cases of DHF. DHF’s symthoms have a similarity with typhoid fever, it often occur wrong handling. Therefore we need a system that is able to diagnose the disease suffered by patients, so that they can recognize whether the patient has DHF or Typhoid. The system will be built using Neural Network Learning Vector Quantization (LVQ) based on the best training results. This research is to diagnose Dengue Hemorrhagic Fever using LVQ with input parameters are hemoglobin, leukocytes, platelets, and heritrocytes. Based on result, the best accuracy is 97,14% with Mean Square Error (MSE) is 0.028571 with 84 train data and 36 test data. Conclution from the research is LVQ method can diagnose DHF Keywords: Dengue Hemorrhagic Fever; Learning Vector Quantization; classification; Neural Network;

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