Sistem Pakar Untuk Pendiagnosaan Karies Gigi Menggunakan Teorema Bayes

Hafizah, Hafizah; tugiono, tugiono; azlan, azlan

doi:10.53513/jsk.v4i1.2625

Cited by 18 publications

(17 citation statements)

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“…Studi Tugiono dan rekannya pada tahun 2020 mendiskusikan penerapan algoritma teorema Bayes dalam sistem pakar untuk mendiagnosa karies gigi. Hasil penelitian menyatakan bahwa pasien mengalami karies gigi tingkat sedang, dengan tingkat kepercayaan sekitar 71% [12].…”

Section: Pendahuluanunclassified

Sistem Pakar Diagnosa Rheumatoid Arthritis dengan Menerapkan Algoritma Teorema Bayes

Indra Angkat,

Sianturi,

Hartono Sinambela

et al. 2024

JIKOMSI

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Penyakit tulang, seperti Rheumatoid Arthritis (RA), dapat dipicu oleh penuaan, gaya hidup tidak sehat, cedera, dan faktor genetik. RA, kondisi kronis pada tulang, seringkali memengaruhi wilayah-wilayah tertentu dalam tubuh, menyebabkan peradangan pada sendi yang dapat mengakibatkan kerusakan dan deformitas sendi. Meskipun belum sepenuhnya dipahami, faktor genetik dan lingkungan diyakini berperan dalam perkembangan RA. Gejala RA melibatkan nyeri, pembengkakan, keterbatasan gerakan, dan deformitas sendi. Penanganan yang efektif sangat penting, meskipun belum ada obat yang menyembuhkan RA sepenuhnya. Sistem kecerdasan buatan, berbasis pada algoritma teorema Bayes, muncul sebagai solusi potensial untuk memfasilitasi diagnosis penyakit tulang tanpa perlu pertemuan langsung antara dokter dan pasien. Algoritma teorema Bayes, yang mencerminkan kecerdasan buatan, telah berhasil diterapkan dalam berbagai penelitian diagnosa penyakit, termasuk hipertensi, presbiopi, anemia, dan karies gigi. Dalam konteks RA, penelitian ini mengidentifikasi kemungkinan bahwa sekitar 71.39% pasien menderita sindrom RA berdasarkan analisis data menggunakan algoritma teorema Bayes. Riset ini bertujuan meningkatkan efisiensi dan objektivitas dalam mendiagnosis RA, mengeksplorasi potensi algoritma teorema Bayes dalam mengidentifikasi kondisi kesehatan pasien berdasarkan gejala atau keluhan. Dengan pendekatan ini, diharapkan proses diagnosis dapat menjadi lebih efisien dan objektif, memberikan manfaat bagi pasien dan dokter dalam mengelola penyakit tulang.

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Section: Pendahuluanunclassified

Sistem Pakar Diagnosa Rheumatoid Arthritis dengan Menerapkan Algoritma Teorema Bayes

Indra Angkat,

Sianturi,

Hartono Sinambela

et al. 2024

JIKOMSI

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“…Metode teorema bayes adalah merupakan metode yang memanfaatkan data sampel yang diperoleh dari popoluasi yang ada [13], [14]. Metode teorema bayes memandang parameter sebagai variabel yang menggambarkan pengetahuan awal tentang parameter sebelum pengematan dilakukan dan dinyatakan dalam suatu distribusi yang disebut dengan distribusi prior [15] [16].…”

Section: Metode Teorema Bayesunclassified

Implementasi Teorema Bayes Untuk Diagnosa Penyakit Hawar Daun Bakteri (Kresek) Dan Penyakit Blas Tanaman Padi

Purwadi¹,

Nasyuha²

2022

Jur. Ris. Kom.

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Rice is a plant that has an important role for the majority of the population in Indonesia. Rice plants have a fairly high carbohydrate content. Therefore, rice cultivation is very important to be maintained. The government is targeting rice yields in 2013 to reach 72.06 million tons of dry milled grains and a surplus of 10 million tons in 2015. But in fact, this has not been realized due to disease attacks on rice plants which are quite detrimental to farmers. This is due to the lack of knowledge among Indonesian farmers about the problem of rice plant diseases. Farmers often have difficulty in consulting with an expert because of the travel time to the agricultural office which is quite far. In this expert system research, the Bayes theorem calculation method determines the probability of an event based on the effects obtained through observations. The result of the analysis of this method is an expert system analysis to diagnose diseases in rice plants along with the probability value of the diagnosed disease, which shows the level of system confidence in the disease by Bayes calculation that the conclusion with the highest value of 0.574 is Blast Disease

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“…an approach to establish the relationship between one or more dependent variables (simple linear regression) as well as the independent variables (multiple linear regression). Assuming that the relationship between these variables can be approximated by a straight-line equation, the model that approximates the relationship between variables in the data is referred to as linear regression stabilization (Hafizah et al, 2019).…”

Section: ) Literature Reviewmentioning

confidence: 99%

Implementation of Data Mining Prediction Delivery Time Using Linear Regression Algorithm

Wahyudi¹,

Arroufu²

2022

JAETS

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In the current era of modernization, online shopping has become a habit of the people, and is closely related to freight forwarding services in charge of delivering online shopping items from the seller to the buyer. So that buyers need a fast and safe delivery service to ensure the goods sent on time to their destination. Customer satisfaction is one of the most important factors in the shipping business. However, there are several obstacles that occur in the field that cause delays in the delivery of goods. Therefore, one solution that can be used to overcome this problem is to use data mining technology to predict delivery times. Using 1,000 datasets consisting of 4 Attributes, data processing will be carried out with prediction techniques using the Linear Regression algorithm. By utilizing data when the goods are taken, when the goods are on the way, until they reach the buyer, they can produce forecasts or predictions and produce several analyzes so that in the future there will be no delivery delays. Based on the RMSE (Root Mean Square Error) value which serves to generate the level value the error of the prediction results using this method and in an RMSE value of 0.370 %. It can be concluded that using the Linear Regression algorithm is proven to be accurate in predicting delivery times.

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Sistem Pakar Untuk Pendiagnosaan Karies Gigi Menggunakan Teorema Bayes

Cited by 18 publications

References 0 publications

Sistem Pakar Diagnosa Rheumatoid Arthritis dengan Menerapkan Algoritma Teorema Bayes

Sistem Pakar Diagnosa Rheumatoid Arthritis dengan Menerapkan Algoritma Teorema Bayes

Implementasi Teorema Bayes Untuk Diagnosa Penyakit Hawar Daun Bakteri (Kresek) Dan Penyakit Blas Tanaman Padi

Implementation of Data Mining Prediction Delivery Time Using Linear Regression Algorithm

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