Expert system for early diagnosis of meningitis disease using certainty factor method

Rumaisa, Fitrah; Junaedi, Danang

doi:10.1109/icitsi.2016.7858202

Cited by 11 publications

(3 citation statements)

References 1 publication

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“…Selain itu, berbagai penelitian mengenai suatu sistem pakar untuk diagnosis penyakit atau menyelesaikan permasalahan lainnya dengan metode algoritma Certainty Factor telah banyak dilakukan. Contoh kasusnya termasuk mendiagnosis penyakit di iklim tropis (Yanti, dkk, 2018), penyakit pada bunga anggrek hitam (Widians, dkk, 2018), identifikasi alga (Setiawan, dkk, 2021), diagnosis penyakit meningitis (Rumaisa & Junaedi, 2016), penyakit tuberkulosis paru tambahan (Ramadiani, dkk, 2017), penyakit gigi dan mulut (Pasaribu, dkk, 2020), penyakit pada tanaman cabai (Andriani, dkk, 2018), serta penyakit pada budidaya mentimun holtikultura (Armaya, dkk, 2022). Di Indonesia, tepatnya di daerah Kabupaten Tapanuli Utara, Provinsi Sumatera Utara, sudah diterapkan penggunaan sistem pakar dalam mendiagnosis penyakit Anthrax pada hewan ternak kerbau menggunakan algoritma Certainty Factor.…”

Section: Pendahuluanunclassified

Sistem Diagnosis Penyakit Kerbau menggunakan Algoritma Forward Chaining

DZAKWAN,

SUBIYANTO,

APRILIANTO

et al. 2024

ELKOMIKA

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ABSTRAKKetergantungan peternak pada pakar atau dokter hewan karena terbatasnya pengetahuan dalam mengindentifikasi penyakit kerbau merupakan opsi yang sulit dan mahal. Dalam mengatasi hal tersebut, artikel ini menyajikan pengembangan sistem pakar diagnosis penyakit kerbau. Sistem ini diimplementasikan dalam bentuk web serta dirancang dengan mengumpulkan data tentang 17 jenis penyakit kerbau dan 49 gejala yang berkaitan. Proses diagnosis menggunakan kombinasi algoritma Forward Chaining dan Certainty Factor, yang memungkinkan sistem untuk mencocokkan gejala yang diamati dengan database penyakit kerbau menghasilkan diagnosis yang akurat. Hasil Pengujian sistem menunjukkan tingkat akurasi mencapai 100% dalam 15 kali pengujian berturut-turut. Hasil pengujian juga divalidasi oleh pakar spesialis kerbau. Kesimpulannya, sistem ini layak digunakan oleh peternak kerbau untuk mendiagnosis penyakit kerbau secara dini.Kata kunci: sistem pakar, penyakit pada kerbau, gejala, forward chaining, certainty factor ABSTRACTFarmers' reliance on experts or veterinarians due to limited knowledge in identifying buffalo diseases is a difficult and expensive option. To address the problem, this paper presents the development of an expert system for buffalo disease diagnosis. The system is implemented on the web and designed by collecting data on 17 buffalo disease types and 49 associated symptoms. The diagnosis process uses a combination of Forward Chaining and Certainty Factor algorithms, which allows the system to match observed symptoms with the buffalo disease database resulting in an accurate diagnosis. System testing results showed an accuracy rate of 100% in 15 consecutive tests. Results were also validated by buffalo specialist experts. In conclusion, the system is feasible to be used by buffalo farmers to diagnose buffalo diseases early.Keywords: expert system, buffalo diseases, symptoms, forward chaining, certainty factor

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Section: Pendahuluanunclassified

Sistem Diagnosis Penyakit Kerbau menggunakan Algoritma Forward Chaining

DZAKWAN,

SUBIYANTO,

APRILIANTO

et al. 2024

ELKOMIKA

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“…An expert system is a computer-based application that utilizes knowledge, facts, and rules of reasoning techniques as a basic reference in solving problems that are usually solved by experts in a particular field, and also tries to represent and duplicate certain functions and procedures so as to be able to solve problems like an expert in a particular field [9].…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Expert System for Diagnosing Early Symptoms of COVID-19 Using the Certainty Factor Method

Julianti

Nurmaesah

Prayogo

2022

JSG

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Coronavirus Disease 2019 (Covid-19) is a pathogenic virus that is the main cause of respiratory tract diseases that can cause respiratory problems such as lung infections and can cause death. Based on data from the health department, the city of Tangerang said that the level of transmission of Covid-19 in the Tangerang Raya area was included in the red zone category, where the spread of Covid-19 averaged 130 additional cases per day. The main problem found is the difficulty of detecting early symptoms that arise as an indication of being infected with Covid-19 and tools to assist in detecting early symptoms felt by the general public. In this study, a rule-based knowledge representation process for the initial clinical symptoms of Covid-19 infection was carried out using an expert system with the certainty factor method, which aims to measure the level of certainty that has been confirmed by Covid-19 against the initial clinical symptoms felt by the user and makes it easier for users to detect the early symptoms of Covid-19 and helps the government, in this case, the health service center through the availability of the expert system application. Based on the results and discussions that have been carried out in this study, it can be concluded that the results of experiments to detect early clinical symptoms that were implemented using an expert system with the certainty factor method showed empirical calculations in the range of 81-85% confidence level on the results given by the system in initial clinical symptoms entered by the user. The results of the research above were obtained through a process of validating the suitability of initial clinical symptoms to the level of Covid-19 infection by using the forward chaining method and then measuring the level of confidence in the results that have been given based on the established rules. The expert system application with the proposed certainty factor method is the basis for developing mobile-based applications that can be used easily for the wider community

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“…Dengan adanya sistem pakar, pihak yang bukan pakar dapat menyelesaikan masalah yang biasa diselesaikan oleh pakar. Sistem pakar telah digunakan untuk mengidentifikasi berbagai penyakit yang terdapat pada manusia, hewan, maupun tanaman [6]- [12].…”

Section: Pendahuluanunclassified

Penerapan Metode Teorema Bayes Untuk Mendeteksi Hama Pada Tanaman Padi Mayas Kalimantan Timur

et al. 2021

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The community very much needs the nutritional needs of food during a pandemic. One source of nutrition that can be obtained is rice or rice derived from rice plants. Mayas rice is a rice plant with advantages in terms of high taste quality and components of certain physiological functions that are beneficial to health. However, Mayas rice has quite a lot of pest attacks, thus reducing agricultural production. On the other hand, the knowledge possessed by the community regarding pests in Mayas rice is still very minimal. Hence, people find it difficult to determine the proper pest control method. Bayes theorem applied in an expert system can be a solution to diagnose the types of pests that attack Mayas rice. The research data is a knowledge base that contains 32 symptoms that appear and 10 types of pests that attack Mayas rice. The results showed that the percentage of certainty in the diagnosis of the types of pests that pounded Mayas rice was based on the symptoms given by the user. The level of testing using ten test cases displays the results of an expert system for identifying types of pests that attack Mayas rice which is suitable for use with a percentage of 90%.

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Expert system for early diagnosis of meningitis disease using certainty factor method

Cited by 11 publications

References 1 publication

Sistem Diagnosis Penyakit Kerbau menggunakan Algoritma Forward Chaining

Sistem Diagnosis Penyakit Kerbau menggunakan Algoritma Forward Chaining

Expert System for Diagnosing Early Symptoms of COVID-19 Using the Certainty Factor Method

Penerapan Metode Teorema Bayes Untuk Mendeteksi Hama Pada Tanaman Padi Mayas Kalimantan Timur

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