scholarly journals Kombinasi Metode Certainty Factor dan Forward Chaining untuk Identifikasi Jenis Kulit Wajah Berbasis Android

2021 ◽  
Vol 5 (1) ◽  
pp. 74
Author(s):  
Syavira Cahyaningsih ◽  
Agung Triayudi ◽  
Ira Diana Sholihati
Keyword(s):  
Expert System ◽  
System Application ◽  
Normal Skin ◽  
Skin Care ◽  
Skin Type ◽  
Facial Skin ◽  
Certainty Factor ◽  
Dry Skin ◽  
Forward Chaining ◽  
Level Of Confidence

Using skincare and facial skin care must be in accordance with the type of facial skin, because if it is not suitable, it can cause problems such as facial skin breakouts, dry skin, irritated skin, and acne prone skin. To find out the type of facial skin, you have to do an examination with a skin and genital specialist, but the high cost of consultation and the long queue process is an obstacle for everyone. Therefore, the authors created an expert system to identify facial skin types using a combination of certainty factor methods with forward chaining techniques. The diagnostic results from calculations using an expert system application and the results of manual calculations from one of the respondent data from 100 respondent data, namely producing the same level of confidence, each of which produces a percentage of 99.45% and the diagnostic results state that the user has a normal skin type.

Perpaduan Metode Certainty Factor dan Forward Chaining untuk Menentukan Tingkat Stres Mahasiswa Tingkat Akhir Berbasis Android

2021 ◽  
Vol 5 (3) ◽  
pp. 267
Author(s):  
Nurholis Nurholis ◽  
Fauziah Fauziah ◽  
Novi Dian Natashia
Keyword(s):  
Expert System ◽  
System Application ◽  
Confidence Level ◽  
Bachelor's Degree ◽  
Certainty Factor ◽  
Forward Chaining ◽  
Final Project ◽  
Level Of Confidence ◽  
Stress Levels ◽  
Predetermined Time

Students who are taking the final semester are students who are completing all their subjects, can take the final project provided they have met the number of credits set to obtain a bachelor's degree. In the process of making a final project, students are required to complete it within a predetermined time, this demand causes students to be depressed, causing stress that affects them in completing their final project and study period. Based on this problem, an Expert System Application was made to Diagnose Stress Levels in Final Year Students by Combining Certainty Factor Methods and Android-Based Forward Chaining Techniques to find out more clearly the level of stress experienced by final year students. The results of the diagnosis on the expert system application and the results of manual calculations on one of the data which is representative of the 200 student data, which produce the same level of confidence, each of which produces a confidence level of 97.97% and was diagnosed with mild stress.Keywords:Android, Certainty Factor, Forward Chaining, Final Year Students, Expert System, Stress.

scholarly journals SISTEM PAKAR IDENTIFIKASI JENIS KULIT WAJAH DENGAN METODE CERTAINTY FACTOR

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Yovita Kinanti Kumarahadi ◽  
M. Zainal Arifin ◽  
Sigit Pambudi ◽  
Tito Prabowo ◽  
Kusrini Kusrini
Keyword(s):  
Expert System ◽  
Skin Care ◽  
Facial Skin ◽  
Certainty Factor ◽  
Dry Skin ◽  
Communication Tools ◽  
Temperature Regulator ◽  
Sufficient Knowledge ◽  
Sense Of Touch

The skin has many functions, including as a protective body, as a sense of touch or communication tools, and as a temperature regulator. The desire of most people, especially women, have white, healthy, clean and well-taken facial skin. However, the treatment does not pay attention to the type of skin, causing new problems such as acne, dry skin and others. To do skin care requires sufficient knowledge. This study aims to help provide identification of the type of facial skin using an expert system. The method used is certainty factor. The results obtained in this study are that this system has been able to identify the type of facial skin with an accuracy of 91%. Thus, an expert system for identifying the type of facial skin can be used to assist users in carrying out treatments.

scholarly journals Perancangan Sistem Pakar Penentuan Jenis Kulit Wajah Menggunakan Metode Certainty Factor

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Rangga Pebrianto ◽  
Siti Nurhasanah Nugraha ◽  
Windu Gata
Keyword(s):  
Expert System ◽  
System Design ◽  
System Application ◽  
Body Part ◽  
Skin Type ◽  
Facial Skin ◽  
Certainty Factor ◽  
Consultation Process ◽  
Factor Method ◽  
The Face

Abstrak - Wajah adalah bagian tubuh terpenting yang harus selalu dijaga dan dirawat. Sehingga banyak cara merawat wajah yang dilakukan untuk mendapatkan wajah putih, bersih, dan terbebas dari jerawat. Pengetahuan analisa kulit wajah sangat diperlukan untuk menentukan jenis kulit serta produk perawatan yang sesuai dengan jenis kulit. Sistem pakar merupakan sistem yang mengadopsi pengetahuan dari seorang pakar dan dapat berperan layaknya seorang pakar dalam menangani proses konsultasi. Tujuan dari penelitian ini yaitu merancang sebuah sistem pakar yang dapat menentukan jenis kulit wajah berbasis android dengan menerapkan metode certainty factor dalam proses penghitungan derajat tingkat keyakinan. Dengan aplikasi sistem pakar berbasis android ini konsultan dapat melakukan pemeriksaan dengan mudah, dan pendiagnosaan sekaligus solusi dapat terselesaikan secara cepat dan tepat berdasarkan data yang diinputkan.Katakunci: Android, Certainty Factor, Perancangan Sistem PakarAbstract - Face is the most important body part that should always be kept and cared for. So many ways of taking care of the face are done to get the face of white, clean, and free of acne. The knowledge of facial skin analysis is necessary to determine the skin type as well as care products that suit the skin type. The expert system is a system that adopts the knowledge of an expert and can play like an expert in handling the consultation process. The purpose of this research is to design an expert system that can determine the type of Android-based facial skin by applying the certainty factor method in the process of counting degrees of confidence. With this Android-based expert System Application consultants can perform inspections with ease, and the solution can be easily resolved quickly and precisely based on the data being inputed.Keywords: Android, Certainty Factor, Expert System Design

scholarly journals Implementasi Forward Chaining dan Certainty Factor pada Aplikasi Konsultasi Kecantikan

2021 ◽  
Vol 5 (01) ◽  
pp. 8-17
Author(s):  
Bunga Ratna Sari ◽  
Sabar Rudiarto
Keyword(s):  
Case Studies ◽  
Negative Impact ◽  
Skin Type ◽  
Facial Skin ◽  
Certainty Factor ◽  
Trust Value ◽  
Forward Chaining ◽  
Beauty Salons ◽  
Beauty Products

Having skin that is free from problems is a dream for most women, especially in Indonesia. However, the problem is not all women are aware that in carrying out treatment or using a product, it must match the needs of each skin type. The rise of beauty salons that operate but are not under the auspices of specialist doctors and also cheap beauty products that are claimed to solve skin problems in an instant makes women easily tempted. This of course can have a big negative impact when the maintenance procedures performed are not up to standard, and there are dangerous ingredients in the products used. For this reason, consulting with a specialist or the expert is indispensable. Researchers used the forward chaining method and certainty factors in building this system which is expected to be used in determining facial skin problems and their solutions based on case studies at the XYZ beauty clinic. The Forward Chaining method is used to draw conclusions based on the facts entered. While certainty factor is used to calculate the trust value from the existing conclusions. This method requires 2 main values ​​in performing calculations, namely MB (measurement of belief) and MD (measurement of disbelief). Based on the research that has been done, the system was successfully built and gave an accuracy value of 97.35%.

scholarly journals Sistem Pakar Diagnosa Penyakit Tanaman Rambutan dengan Metode Forward Chaining dan Certainty Factor Berbasis Android

2020 ◽  
Vol 5 (3) ◽  
pp. 329
Author(s):  
Bayu Abrianto Risnadi ◽  
Fauziah Fauziah ◽  
Ratih Titi Komala Sari
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
System Application ◽  
Confidence Level ◽  
Certainty Factor ◽  
Forward Chaining ◽  
Calculation Results ◽  
Manual Calculation

The purpose of this research is to create an expert system application to diagnose diseases in the rambutan plant that can be accessed anytime and anywhere so that the handling of the disease can be done appropriately. The Forward Chaining and Definity Factor methods are used because they are very suitable for expert systems that diagnose something that is uncertain so that the manual calculation results from the symptom data and the existing expert values result in a 98.91% confidence level percentage, and solutions are given to treat disease-stricken plants. The implementation uses Android Studio so that the application can run dynamically on various devices so that farmers can immediately find out what is happening with the conditions of their rambutan plants directly.Keywords:Rambutan Plant, Expert System, Android, Forward Chaining, Certainty Factor.

scholarly journals Sistem pakar mendiagnosa penyakit kolesterol berbasis database dan web

2019 ◽  
Vol 4 (1) ◽  
pp. 29-35
Author(s):  
Aswadul Fitri Saiful Rahman ◽  
Puja Indriani ◽  
Mayda Waruni Kasrani
Keyword(s):  
Expert System ◽  
System Application ◽  
Fast Food ◽  
Fast Food Restaurant ◽  
Web Based ◽  
Forward Reasoning ◽  
Forward Chaining ◽  
Level Of Confidence ◽  
Big Cities ◽  
Modern Era

Technological advancements, increasing various aspects of life in the modern era have changed the style and pattern of people's lives. Unhealthy lifestyles are clearly seen in big cities, seen from food that can be found in every fast food restaurant or fast food. If the diet is not controlled, a person will be more susceptible to diseases that are difficult to cure, namely cholesterol. In this study the authors aim to design an expert system application that is used to diagnose cholesterol based and web- based cholesterol diseases based on the symptoms of the disease felt by patients who become a decision in the form of a level of confidence and the solution by using the forward chaining method to get forward reasoning and calculate the value of trust of the symptoms chosen by the patient.

Penerapan Metode Forward Chaining dan Certainty Factor untuk Mendiagnosa Penyakit Sapi Perah Berbasis Android

2021 ◽  
Vol 5 (3) ◽  
pp. 238
Author(s):  
Wahyu Eka Mahendra ◽  
Septi Andryana ◽  
Winarsih Winarsih
Keyword(s):  
Expert System ◽  
Dairy Cows ◽  
System Application ◽  
Confidence Level ◽  
Initial Diagnosis ◽  
The Body ◽  
Diagnosis And Treatment ◽  
Certainty Factor ◽  
Forward Chaining ◽  
Insight Into

Dairy cows are suitable livestock to be developed because they can produce milk as a source of beneficial protein for the body. One of the obstacles faced by farmers is the emergence of diseases in dairy cows such as mastitis. Often breeders feel confused about the illnesses their pets suffer; this is due to their lack of insight into the types of diseases of dairy cows. In this study, a solution was provided, namely providing a service by applying the forward chaining method and certainty factor in an Android-based expert system application. This study aims to broaden farmers' insight, as well as help breeders to facilitate faster, more practical initial diagnosis and treatment solutions. The results of this study indicate that, in calculating the sample, the diagnosis of mastitis has a confidence level of 99.92%. This number shows that this system can be applied to solve existing problems.Keywords:Certainty Factor; Dairy Cows; Expert System; Forward Chaining.

scholarly journals Sistem Pakar dalam Membandingkan Metode Forward Chaining dengan Certainty Factor untuk Mengidentifikasi Jenis Kulit Wajah

2021 ◽  
pp. 257-262
Author(s):  
Nadya Alinda Rahmi ◽  
Gunadi Widi Nurcahyo
Keyword(s):  
Human Body ◽  
Subject Matter ◽  
Skin Inflammation ◽  
The Body ◽  
Subject Matter Experts ◽  
Facial Skin ◽  
Certainty Factor ◽  
Dry Skin ◽  
Forward Chaining ◽  
Test Outcomes

Skin is one piece of the body that has adaptable properties to shield the human body from natural effects. A great many people need facial skin that is tight and liberated from skin illnesses, particularly skin inflammation inclined skin. Next, everybody ought to do facial consideration and utilize a few fixings that are appropriate for facial skin, there are five kinds of ordinary skin, sleek skin, dry skin, blend skin and touchy skin. To inspect the kind of facial skin by contrasting the Forward Chaining and Certainty Factor procedures. This assessment utilizes 30 information acquired from interviews with subject matter experts. There are a few signs acquired from different issues distinguished on facial skin which are utilized as indication data for facial skin types constrained by subject matter experts. This data is utilized to check the sort of facial skin dependent on guidelines and data from a trained professional. The preliminary advances taken are to look at the Forward Chaining and Certainty Factor strategies. The outcomes acquired subsequent to testing and assessment of the Forward Chaining and Certainty Factor strategies were 83.33% and the discoveries expressed that the customer had a commonplace skin type. The test outcomes can be seen from the two strategies that test unequivocal facial skin types, then, at that point the principle system utilized not set in stone to help dermatologists in analyzing facial skin types.

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.

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