Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal An Nafi’; Multidisciplinary Science Tamilis Synex: Multidimensional Collaboration
Hardiana
Universitas Sepuluh Nopember Papua
Religion Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
MODEL PROSES ANTRIAN RAWAT JALAN PUSKESMAS MENGGUNAKAN FINITE STATE AUTOMATA UNTUK PENINGKATAN PELAYANAN Fauziah Humairoh; Natalia Betty Ansanay; Wardah Sal Sabillah; Astrin Aprilia Umasugi; Hardiana; Astika Ramadani; Heru Sutejo
Tamilis Synex: Multidimensional Collaboration SPECIAL ISSUE Tamilis Synex: Multidimensional Collaboration 2024
Publisher : CV Edujavare Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penelitian ini bertujuan untuk mengembangkan model proses antrian rawat jalan di Puskesmas menggunakan konsep Finite State Automata (FSA) dengan dua jenis layanan, yaitu faskes umum dan faskes BPJS, guna meningkatkan efisiensi pelayanan. Model ini dirancang untuk meminimalkan waktu tunggu pasien, memudahkan pengelolaan alur pasien, serta meningkatkan transparansi layanan. Dengan pendekatan FSA, setiap tahapan dalam proses antrian diuraikan menjadi state yang mewakili kondisi tertentu, dan setiap transisi antar state diatur berdasarkan jenis layanan yang diterima pasien. Hasil penelitian menunjukkan bahwa penerapan FSA dapat mengurangi ketidakteraturan antrian, mempercepat proses layanan, serta memaksimalkan pemanfaatan sumber daya medis dan administrasi.
Implementasi Metode Teorema Bayes Pada Diagnosa Penyakit Gigi Muhammad Risman; Fiqram putra pratama; Gonzales H. Marlissa; Hardiana; Lucilla T. Ledious Monika; Astika Ramadhani; Rexci Trido Ngaderman7; Putra Hidayatullah; Patmawati Hasan
An Nafi': Multidisciplinary Science Vol. 2 No. 4 (2025): An Nafi’
Publisher : CV Edujavare Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70610/annafi.v2i4.1052

Abstract

This study implements the Bayes Theorem method to diagnose dental diseases based on patient-reported symptoms. Bayes Theorem operates by calculating the probability of a disease as a hypothesis based on available evidence in the form of observed symptoms. In this study, patient-reported symptoms are analyzed probabilistically to diagnose several types of dental diseases, namely gingivitis, dental caries, periodontal abscess, and pulpitis. The system utilizes conditional probability values between symptoms and diseases obtained from expert knowledge to calculate the posterior probability of each disease. The system is developed using the Python programming language and consists of a knowledge base containing symptom data, disease types, and probability values, as well as an inference engine that applies Bayes Theorem calculations. Research data were collected through interviews with dentists at Dian Farma Clinic, South Jayapura. The results indicate that the Bayes Theorem method is effective in supporting the early diagnosis of dental diseases in an objective and measurable manner; however, the diagnostic results still require further confirmation by professional medical personnel.
Co-Authors Astika Ramadani Astika Ramadhani Astrin Aprilia Umasugi Fauziah Humairoh Fiqram Putra Pratama Gonzales H. Marlissa Heru Sutejo Lucilla T. Ledious Monika Muhammad Risman Natalia Betty Ansanay Patmawati Hasan Putra Hidayatullah Rexci Trido Ngaderman7 Wardah Sal Sabillah