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Suranti , Dewi
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Computer Science & IT

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Application of the Naive Bayes Method in Expert Systems for Diagnosing Gingivitis Fernando, Rendy; Suranti , Dewi; Suryana , Eko
Jurnal Komputer Indonesia Vol. 1 No. 2 (2022): Desember
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v1i2.24

Abstract

The number of program activities at the Beringin Raya Health Center in Bengkulu City is sometimes not proportional to the number of doctors in the puskesmas, so not all patients can have health consultations, especially about gingivitis. Gingivitis is a disease caused by a bacterial infection which causes the gums to swell due to inflammation. Therefore we need an application that can help the process of diagnosing gingivitis based on the symptoms experienced by the patient, so that the initial diagnosis experienced by the patient can be known. The expert system for diagnosing gingivitis at the Beringin Raya Nursing Health Center in Bengkulu City was made using the PHP programming language and MySQL database, which can be accessed online via the https://sistempakargingivitis.my.id/ link. The expert system for diagnosing gingivitis in the treatment of Beringin Raya, Bengkulu City, has implemented the Naive Bayes Method to represent, combine, and propagate uncertainty, which has several intuitive characteristics according to the way of thinking of an expert. The training data used is 11 data which is used as the basis for the probability value of each symptom in the disease to carry out a consultation diagnosis. Based on the consultation with the selected symptoms, namely G1, G2, G3 and G4, the diagnosis of Nonvital Teeth disease (Dead Teeth) was obtained with a bayes value of 0.2045454541875. Based on the system testing that has been done, it can be concluded that the functionality of the application has been running well and this expert system can provide consulting results based on the symptoms selected by the user through the stages of the Naive Bayes method
Penerapan Algoritma C4.5 Dalam Memprediksi Tingkat Kelulusan Siswa Pada SMPN 06 Bengkulu Tengah Wahidi, Agus Rahman; Maryaningsih, Maryaningsih; Suranti , Dewi
Jurnal Komputer Vol 1 No 2 (2023): Januari-Juni
Publisher : CV. Generasi Insan Rafflesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70963/jk.v1i2.55

Abstract

SMPN 6 Central is a junior high school educational institution in Central Bengkulu. This school has a lot of data related to academic activities, for example student graduation data. These data have not been utilized as fully as possible, for example to predict student graduation, so that action can be taken to maximize preparation for the final exam. This research was conducted to design an application system using a classification technique that can process large amounts of data to find patterns that occur in student data. The data processing is used to predict student graduation. The classification technique used is the decision tree with the implementation of C4.5 algorithm. The input used is in the form of attributes from student data including semester from semester 1 to 6, skills scores and National Standard School Examination scores (USBN). Therefore, to make it easier to predict the graduation rate, an application testing uses data on students who have graduated from 2019 to 2020, totaling 100 students and the results of testing from 2021 to 2022, totaling 81 students. The knowledge gained from the results of the application training is expected to be utilized by the management of SMPN 6 Central Bengkulu as a more effective decision-making tool in planning and preparing for students' final exams. Based on the results of the tests carried out, it can be concluded that this application can predict student graduation at SMPN 6 Central Bengkulu.
Sistem Pakar Mendiagnosa Penyakit Appendisitis Menggunakan Metode Certainty Factor Feryra, Stivano; Suranti , Dewi; Yupianti
Jurnal Komputer Vol 2 No 1 (2023): Juli-Desember
Publisher : CV. Generasi Insan Rafflesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70963/jk.v2i1.64

Abstract

Health is an important asset in carrying out activities so it needs to be maintained and considered properly, therefore it is important to equip yourself with knowledge and maintain a healthy lifestyle in order to avoid various diseases. One of the diseases that attack humans and is often found in hospitals is appendicitis. The lack of knowledge and socialization to the community about this disease Appendicitis (Inflammation of the Appendix), resulting in the community considering this disease as trivial or ordinary, in fact according to the information of doctors this disease which if not treated properly will cause death. Therefore, to help the community and medical personnel in providing knowledge, consultation and socialization about the disease Appendicitis (Inflammation of the Appendix) is to design and build an expert system application by applying the Certainty Factor method. The Certainty Factor method has the advantage of being able to measure something whether it is certain or uncertain, for example in diagnosing a disease.The final result of this research is an expert system to diagnose Appendicitis (Inflammation of the Appendix) along with the confidence value of the diagnosed disease, which shows the system's level of confidence in the disease.
Co-Authors Alamsyah , Hendri Fernando, Rendy Feryra, Stivano Imansyah, Dwi Junizar, Wansa S Jusuf Wahyudi Maryaningsih, Maryaningsih Ristika, Ristika Suryana , Eko Ternando, Riki Wahidi, Agus Rahman Yupianti