scholarly journals Rancang Bangun Sistem Pakar dengan Metode Forward Chaining untuk Rekomendasi Pariwisata di Labuan Bajo Menggunakan iOS Platform

2020 ◽  
Vol 3 (3) ◽  
pp. 125
Author(s):  
Leonardo Jeffry Sutedjo ◽  
Rinabi Tanamal
Keyword(s):  
Expert System ◽  
Online Media ◽  
Process Data ◽  
Rule Based ◽  
Tourist Attractions ◽  
Forward Chaining ◽  
Tourist Destinations

Nowadays many tourists like to travel. When on vacation the user is confused about where to go and whether it's good or not. When tourists want to take a vacation and the user must choose to do a tour and it turns out that it is not good in terms of good or bad attractions. So there is encouragement to help tourists to provide recommendations for good tourist places to visit. But now with so many online media to buy tickets, but the local guide is still rampant in maintaining tourism. This location with the presence of local guides who do not understand the price and when they are in Labuan Bajo the price of the user is still not right then it makes tourists confused. The existence of a problem raises the urge to make an application of an expert system that recommends tourist attractions in Labuan Bajo by using the Forward Chaining method. In making this application uses a rule based to process data on applications on iOS. And using mcgoo is used to create and process data taken from experts. This application can help tourists to find excellent places to travel. Because the purpose of the user to travel is to have fun if the user is confused to determine the existing location then this application will help the user determine the desired tourist attractions. This application also provides several tourist options such as tours on the sea, cities, or hills/mountains. The target of visitors is always less because tourists lack the desire to travel in Labuan Bajo because of the lack of recommendations on Labuan Bajo tourism. The results of research conducted by more foreign tourists who prefer to visit Labuan Bajo because local tourists prefer tourist destinations that are still crowded, such as Bali and Lombok. So that makes tourism in Labuan Bajo not yet an attraction for local tourists.

scholarly journals Sistem Pakar Diagnosa Penyakit THT Menggunakan Metode Dempster Shafer

Repositor ◽  
2020 ◽  
Vol 2 (9) ◽  
Author(s):  
Doni Yulianto ◽  
Yufiz Azhar ◽  
Nur Hayatin
Keyword(s):  
Expert System ◽  
Search Method ◽  
Rule Based ◽  
Forward Chaining ◽  
Lack Of Information ◽  
The Subject ◽  
The Right ◽  
Uncertainty Method ◽  
Development Step ◽  
Nose And Throat

AbstrakBerbagai penyakit pada manusia dapat menimbulkan masalah serius jika tidak cepat ditangani, seperti halnya penyakit THT (Telinga, Hidung, dan Tenggorokan). Penderita penyakit THT di Indonesia cukup tinggi, karena masyarakat sering menganggap remeh penyakit THT dan kurangnya informasi mengenai penyakit tersebut. Perlu adanya sistem yang memberikan informasi mengenai gejala pada penyakit THT dan jenis penyakit apa saja yang diderita, serta solusi apa yang tepat untuk menangani penyakit THT. Subjek dalam penelitian ini adalah sistem pakar untuk mendiagnosa penyakit THT. Pada penelitian ini menggunakan dua metode, yaitu metode ketidakpastian menggunakan Dempster Shafer dan metode penelusuran yaitu Forward Chaining. Langkah pengembangan diawali dari pengumpulan data, lalu pembuatan Rule Based, mengimplementasikan metode, dan melakukan pengujian akurasi pakar. Hasil penelitan ini adalah sistem pakar mendiagnosa penyakit THT sebanyak 7 jenis penyakit dengan gejala sebanyak 24 jenis. Penelitian ini juga menggunakan metode Dempster Shafer untuk mendapatkan nilai kepastian berupa persentase nilai kepastian pada hasil diagnosa penyakitnya. Berdasarkan hasil pengujian pakar, dapat disimpulkan bahwa sistem pakar memiliki tingkat kesamaan dengan pakar sebesar 85% yang berarti bahwa sistem pakar ini layak untuk digunakan.AbstractVarious diseases in humans can cause serious problems if not quickly handled, such as ENT diseases (ear, nose, and throat). People with ENT disease in Indonesia is quite high, because people often consider the condition of ENT disease and lack of information about the disease. There is a system that provides information about the symptoms in ENT diseases and what types of diseases suffered, as well as what is the right solution to handle ENT diseases. The subject in this study is an expert system for diagnosing ENT diseases. The study used two methods, namely the uncertainty method using Putty Shafer and the search method that is Forward Chaining. The development step starts from collecting data, then creating a Rule Based, implementing methods, and conducting expert accuracy testing. The results of this research is a system of experts diagnose ENT diseases as many as 7 types of diseases with the symptoms as much as 24 types. This research also uses the method of putty Shafer to get certainty of the percentage value of certainty in the diagnosis of diseases. Based on expert testing results, it can be concluded that an expert system has a level of similarity with experts at 85% which means that the expert system is worthy of use.

Rancang Bangun Sistem Pakar Pendiagnosa Penyakit Demam Typhoid dan Demam Berdarah Dengue dengan Metode Forward Chaining

2012 ◽  
Vol 4 (1) ◽  
pp. 17-23
Author(s):  
Benny Wijaya ◽  
Maria Irmina Prasetiyowati
Keyword(s):  
Expert System ◽  
Knowledge Base ◽  
Rule Based ◽  
Forward Chaining

Penyakit demam typhoid dan demam berdarah dengue merupakan penyakit yang umum di Indonesia. Kedua penyakit ini memiliki gejala yang hampir sama. Apabila pada saat menangani pasien, dokter salah mengetahui jenis penyakit yang diderita, hal ini dapat menyebabkan kematian. Oleh karena itu, dibuatlah Sistem pakar pendiagnosa penyakit demam typhoid dan demam berdarah dengue. Sistem pakar ini dibangun menggunakan metode inferensi forward chaining. Metode inferensi forward chaining ini diimplementasikan dengan menggunakan bahasa pemrograman C#. Sistem pakar yang dirancang dalam skripsi ini merupakan rule-based expert system. Dari hasil uji coba sistem dapat disimpulkan bahwa tingkat keakuratan sistem adalah 93,33%, rata – rata waktu yang dibutuhkan untuk mendiagnosa penyakit menggunakan sistem ini adalah 3,16 menit. Tingkat keakuratan sistem bergantung pada knowledge base yang disimpan dalam database

scholarly journals An Expert System for the Prognostication of the Brain and Nerve Diseases in Children with Convulsion Signs Based on Certainty Factors (Preprint)

2018 ◽  
Author(s):  
Narges Roozitalab ◽  
Hamid Nemati
Keyword(s):  
Expert System ◽  
Naive Bayes ◽  
Neurological Diseases ◽  
Naïve Bayes ◽  
Rule Based ◽  
Forward Chaining ◽  
Two Systems ◽  
The One ◽  
Time Required ◽  
Expert Physician

BACKGROUND Nowadays, the importance of the treatment of neurological diseases in children is well known to everybody. Currently, there are only 60 neurological specialists in Iran. Due to the lack of necessary equipment, we need to send lab. Samples to the countries which have advanced laboratories for diagnosis. Therefore, a diagnostic expert system can significantly prevent deaths of children. In this paper, we design and implement a rule-based expert system in CLIPS language using certainty factors and forward chaining inference in order to help physicians. Naïve Bayes and Logistic algorithm and the experiences of the expert person have been considered to estimate the certainty factors. The accuracy of this system is 94% for detecting diseases. Performances of these two systems are compared and the results confirm that the certainty factors that are specified by the expert physician have 6.2 percent prediction improvement over the one with Naïve Bayes. It is worth noting that an automatic rule generating program has been developed to reduce the time required to produce rules manually and minimize errors. OBJECTIVE Nowadays, the importance of the treatment of neurological diseases in children is well known to everybody. Currently, there are only 60 neurological specialists in Iran. Due to the lack of necessary equipment, we need to send lab. Samples to the countries which have advanced laboratories for diagnosis. Therefore, a diagnostic expert system can significantly prevent deaths of children. In this paper, we design and implement a rule-based expert system in CLIPS language using certainty factors and forward chaining inference in order to help physicians. Naïve Bayes and Logistic algorithm and the experiences of the expert person have been considered to estimate the certainty factors. The accuracy of this system is 94% for detecting diseases. Performances of these two systems are compared and the results confirm that the certainty factors that are specified by the expert physician have 6.2 percent prediction improvement over the one with Naïve Bayes. It is worth noting that an automatic rule generating program has been developed to reduce the time required to produce rules manually and minimize errors. METHODS Nowadays, the importance of the treatment of neurological diseases in children is well known to everybody. Currently, there are only 60 neurological specialists in Iran. Due to the lack of necessary equipment, we need to send lab. Samples to the countries which have advanced laboratories for diagnosis. Therefore, a diagnostic expert system can significantly prevent deaths of children. In this paper, we design and implement a rule-based expert system in CLIPS language using certainty factors and forward chaining inference in order to help physicians. Naïve Bayes and Logistic algorithm and the experiences of the expert person have been considered to estimate the certainty factors. The accuracy of this system is 94% for detecting diseases. Performances of these two systems are compared and the results confirm that the certainty factors that are specified by the expert physician have 6.2 percent prediction improvement over the one with Naïve Bayes. It is worth noting that an automatic rule generating program has been developed to reduce the time required to produce rules manually and minimize errors. RESULTS Nowadays, the importance of the treatment of neurological diseases in children is well known to everybody. Currently, there are only 60 neurological specialists in Iran. Due to the lack of necessary equipment, we need to send lab. Samples to the countries which have advanced laboratories for diagnosis. Therefore, a diagnostic expert system can significantly prevent deaths of children. In this paper, we design and implement a rule-based expert system in CLIPS language using certainty factors and forward chaining inference in order to help physicians. Naïve Bayes and Logistic algorithm and the experiences of the expert person have been considered to estimate the certainty factors. The accuracy of this system is 94% for detecting diseases. Performances of these two systems are compared and the results confirm that the certainty factors that are specified by the expert physician have 6.2 percent prediction improvement over the one with Naïve Bayes. It is worth noting that an automatic rule generating program has been developed to reduce the time required to produce rules manually and minimize errors. CONCLUSIONS Nowadays, the importance of the treatment of neurological diseases in children is well known to everybody. Currently, there are only 60 neurological specialists in Iran. Due to the lack of necessary equipment, we need to send lab. Samples to the countries which have advanced laboratories for diagnosis. Therefore, a diagnostic expert system can significantly prevent deaths of children. In this paper, we design and implement a rule-based expert system in CLIPS language using certainty factors and forward chaining inference in order to help physicians. Naïve Bayes and Logistic algorithm and the experiences of the expert person have been considered to estimate the certainty factors. The accuracy of this system is 94% for detecting diseases. Performances of these two systems are compared and the results confirm that the certainty factors that are specified by the expert physician have 6.2 percent prediction improvement over the one with Naïve Bayes. It is worth noting that an automatic rule generating program has been developed to reduce the time required to produce rules manually and minimize errors.

Sistem Pakar Mendeteksi Penyakit Tanaman Kelapa Sawit Menggunakan Metode Forward Chaining

2019 ◽  
Vol 1 ◽  
pp. 444
Author(s):  
Dimas Satria ◽  
Poningsih Poningsih ◽  
Widodo Saputra
Keyword(s):  
Expert System ◽  
Programming Languages ◽  
Palm Oil ◽  
Oil Palm ◽  
Oil Production ◽  
Plant Diseases ◽  
Accurate Information ◽  
Forward Chaining ◽  
Web Programming ◽  
Level Of Confidence

The purpose of this paper is to create an expert system to detect oil palm plant diseases in order to help farmers / companies in providing accurate information about the diseases of oil palm plants and how to overcome them and to help reduce the risk of decreasing palm oil production. This system is designed to mimic the expertise of an expert who is able to detect diseases that attack oil palm plants. The method used is forward chaining that is starting from a set of data and proving a fact by describing the level of confidence and uncertainty found in a hypothesis. The results of this study are to diagnose diseases of oil palm plants and their computerization using web programming languages.

A Selection of Bandung City Travel Route Using The FLOYD-WARSHALL Algorithm

2020 ◽  
Vol 12 (7) ◽  
Author(s):  
Muhammad Ghifari Arfananda ◽  
◽  
Surya Michrandi Nasution ◽  
Casi Setianingsih ◽  
◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Rapid Development ◽  
Route Selection ◽  
Tourist Attractions ◽  
Tourist Destinations ◽  
A Value ◽  
Distance Data ◽  
Simple Additive Weighting ◽  
The City ◽  
Selection Of

The rapid development of information and technology, the city of Bandung tourism has also increased. However, tourists who visit the city of Bandung have problems with a limited time when visiting Bandung tourist attractions. Traffic congestion, distance, and the number of tourist destinations are the problems for tourists travel. The optimal route selection is the solution for those problems. Congestion and distance data are processed using the Simple Additive Weighting (SAW) method. Route selection uses the Floyd-Warshall Algorithm. In this study, the selection of the best route gets the smallest weight with a value of 5.127 from the Algorithm process. Based on testing, from two to five tourist attractions get an average calculation time of 3 to 5 seconds. This application is expected to provide optimal solutions for tourists in the selection of tourist travel routes.

SISTEM PAKAR MENU MAKANAN SEHAT BAGI PENDERITA KOLESTEROL DENGAN METODE FORWARD CHAINING

2017 ◽  
Vol 3 (2) ◽  
pp. 72
Author(s):  
Gusnita Darmawati
Keyword(s):  
Expert System ◽  
Cholesterol Level ◽  
Blood Group ◽  
Healthy Food ◽  
Healthy Diet ◽  
Blood Type ◽  
Forward Chaining ◽  
Cholesterol Levels ◽  
Microsoft Office ◽  
Visual Basic 6.0

<p>Penelitian ini membangun suatu sistem pakar untuk menentukan menu makanan sehat berdasarkan golongan darah dan tingkat kadar kolesterol pasien dengan metode Forward Chaining. Tujuan untuk membantu orang awam dalam menentukan menu makanan sehat untuk pasien kolesterol. Sistem ini menganalisa masalah penentuan menu makanan sehat berdasarkan golongan darah dan tingkat kadar kolesterol pasien. Hasil yang diperoleh dari sitem pakar ini adalah berupa informasi makanan sehat yang akan dikonsumsi oleh pasien kolesterol dengan jenis golongan darah dan tingkat kadar kolesterol yang berbeda. Analisa dilakukan dengan cara mengetahui jenis golongan darah dan tingkat kadar kolesterol pasien yang ditampilkan oleh program sistem pakar ini, rancangan sistem ini menggunakan inference forward chaining, dengan implementasi sistem menggunakan sistem database Microsoft Office Access dan bahasa pemrograman Visual Basic 6.0. Dari rancangan aplikasi sistem pakar yang dibuat, maka orang awam yang memderita kolesterol dapat menentukan menu makanan sehat untuk di konsumsi berdasarkan golongan darah dan tingkat kadar kolesterol dengan menjalankan aplikasi sistem pakar.</p><p><em><br /></em></p><p><em><em>This study builds an expert system to determine the healthy food menu based on blood type and cholesterol levels of patients with Forward Chaining method. The goal is to help the layman in determining a healthy diet for cholesterol patients. This system analyzes the problem of determining healthy food menu based on blood group and patient cholesterol level. The results obtained from this expert system is in the form of healthy food information that will be consumed by cholesterol patients with the type of blood group and different cholesterol levels. From the design of expert system applications created, the layman who memderita cholesterol can determine the healthy diet to be consumed by blood type and cholesterol level by running an expert system application.<br /> <br /> </em></em></p>

SISTEM PAKAR UNTUK DIAGNOSA PENYAKIT ANAK YANG DIDUKUNG OLEH BAHASA PEMOGRAMAN VISUAL

2017 ◽  
Vol 3 (2) ◽  
pp. 108
Author(s):  
Dian Permata Sari
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Human Knowledge ◽  
Inference Method ◽  
Medical Field ◽  
Forward Chaining ◽  
At Home

<p>Sistem pakar merupakan sistem yang mengadopsi pengetahuan manusia ke komputer yang dirancang untuk memodelkan kemampuan menyelesaikan masalah seperti layaknya seorang pakar. Dengan sistem pakar ini, orang awam pun dapat menyelesaikan masalahnya atau hanya sekedar mencari suatu informasi berkualitas yang sebenarnya hanya dapat diperoleh dengan bantuan para ahli di bidangnya. Salah satunya yaitu dibidang medis untuk mendiagnosapenyakit anak. Mengetahui gejala dari suatu penyakit secara dini dapat menjadi bantuan pertama yang dapat dilakukan para orang tua di rumah jika anak mereka terserang penyakit.Basis pengetahuan disusun sedemikian rupa kedalam database dengan beberapa tabel. Penarikan kesimpulan dalam sistem pakar ini menggunakan metode inferensi <em>forward chaining</em>. Sistem pakar akan memberikan pertanyaan-pertanyaan kepada user berupa gejala dari beberapa penyakit dan user akan menjawab pertanyaan tersebut. Hingga <em>user</em> akan mendapatkan solusi dari hasil pertanyaan tadi. </p><p><em><br /></em></p><p><em>Expert systems are systems that adopt human knowledge into computers designed to model the ability to resolve problems like an expert. Through thisexpert systems,commoner cansolvetheproblem orjustlookingfor a qualityinformationthat can onlybeobtainedwiththehelpofexperts in thefield. One ofthemis in the medical field to diagnosethe children's illness.Knowingthesymptomsofanillnessearly can bethefirstaidto parents if their children stricken withthedisease at home.</em><em>Knowledgebase is arranged into a highlystructureddatabasewithmultipletables. Inferences in this expert system uses forward chaining inference method. Expert systems will provide questions to the user in the form of the symptoms of some diseases and the user will answer that question. Until the user will get the solution of the question.</em></p>

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