APPLICATION OF EXPERT SYSTEMS OR DECISION-MAKING SYSTEMS IN THE FIELD OF EDUCATION

Expert system (ES) is a branch of artificial intelligence (AI) that is used to manage different problems by making use of interactive computer-based decision-making process. It uses both factual information and heuristics to resolve the complicated decision-making issues in a specific domain. The architecture of the expert system was analyzed and found that it includes several parts such as user interface, knowledge base, working memory, inference engine, explanation system, system engineer, and knowledge engineer, user, and expert system shell in which each part of the architecture of an expert system is based on different functionary that helps it to make an adequate decision by analyzing complex situations. The research aims to analyze the application of expert systems or decision-making systems in the field of education and found that it is used for different purposes such as assessing teacher performance, providing guidance to the students regarding their career, and providing quality learning to students with disabilities. It is also used to help the students to make rightful career decisions and become efficient professionals after completing their studies.

The role of chatterbots in enhancing tourism: a case study of Penang tourism spots

Chatterbots have been widely used as a tool for conversational booking assistance mainly for hotels such as the Expedia. This paper extends the use of chatterbot beyond booking by presenting the proof of concept of a chatterbot expert system called the VIZARD. The proposed VIZARD is developed using an expert system shell called verbot. The core of Vertbot 5 is the natural language processing (NLP) engine based on pattern matching. The core Verbot 5 engine is responsible for finding matches to a given user input string and firing the appropriate rule. The findings from the user acceptance test concluded that majority of the respondents agreed that the VIZARD expert system stands at an unbiased state while being more aligned on supporting the usefulness of the system.

Rancang Bangun Aplikasi Sistem Pakar Berbasis Android Untuk Diagnosa Kerusakan Printer Canon MP Series

Printer adalah objek yang dibutuhkan untuk menunjang aktivitas seseorang sebagai alat utama untuk berbagai usaha seperti percetakan, desain dan sebagainya. Berdasarkan data yang diberikan oleh IDC (International Data Corporation), penjualan printer di Indonesia mengalami kenaikan sebesar 0,6 persen dari tahun ke tahun. Seiring berjalannya waktu, pengguna pasti akan mengalami kerusakan pada printer yang tidak terduga. Perbaikan pada printer sebaiknya dilakukan oleh seorang teknisi yang paham dengan kerusakan printer. Minimnya pengetahuan yang dimiliki oleh pengguna printer dapat mengakibatkan penanganan yang salah dan dapat berakibat fatal. Kerusakan pada umumnya yang terjadi meliputi kertas macet saat mencetak, cartridge tinta bermasalah, roll penarik kertas mesin printer rusak atau patah, mesin printer tidak dapat menyala atau mati total dan hasil cetakan buram. Aplikasi yang dirancang menggunakan metode Forward Chaining berbasis Android untuk membantu pengguna mendiagnosa kerusakan mesin printer. Aplikasi sistem pakar yang akan digunakan oleh peneliti adalah Expert system shell yaitu McGoo. Berdasarkan hasil penelitian yang telah dilakukan melalui wawancara dan observasi dihasilkan sebuah aplikasi sistem pakar yang dapat diakses melalui smartphone berbasis Android sehingga dapat membantu pengguna printer Canon MP Series untuk memahami dan mampu mengatasi masalah pada kerusakan printer berdasarkan hasil diagnosa yang dilakukan.

Rancang Bangun Aplikasi Sistem Pakar Berbasis Android Menggunakan Metode Forward Chaining Untuk Mendiagnosis Kerusakan Pada Hardware Laptop

Kebutuhan dan penggunaan laptop yang banyak sering diikuti oleh banyaknya permasalahan yang sering terjadi pada laptop yang digunakan. Beberapa permasalahan yang sering terjadi, seperti layar laptop tampil blue screen, baterai laptop yang cepat habis, keyboard tidak berfungsi dengan normal, ataupun laptop yang tiba-tiba mati dengan sendirinya. Bila permasalahan tersebut timbul, biasanya pengguna laptop yang masih awam tidak mengerti apa yang harus mereka lakukan. Biaya perbaikan laptop yang harus dibayar termasuk mahal. Tidak hanya itu, jika permasalahan tersebut dibawa ke tempat servis laptop, ada beberapa teknisi laptop yang salah mendiagnosis kerusakannya karena kurang pemahaman atau pengalaman mengenai masalahnya. Maka dari itu, untuk mengatasi beberapa permasalahan yang sering terjadi di atas, dibuatlah aplikasi sistem pakar berbasis Android menggunakan metode forward chaining yang dapat mendiagnosis kerusakan hardware laptop secara tepat. Expert system shell yang digunakan adalah McGoo yang selanjutnya menggunakan Thunkable sebagai pembuat aplikasi sistem pakar. Dengan sistem ini, diharapkan user dapat lebih cepat, mudah, dan efisien dalam memperbaiki laptop dan mengambil keputusan secara tepat. Kesimpulan yang didapat menunjukkan bahwa pembentukan pohon keputusan untuk diagnosis kerusakan hardware laptop dapat diimplementasikan ke dalam aplikasi. Berdasarkan hasil pengujian, aplikasi sistem pakar yang telah terbentuk dapat diakses melalui smartphone berbasis Android sehingga dapat membantu pengguna laptop untuk memahami dan mengatasi masalah dan gangguan pada bagian hardware laptop.

An IoT Expert System Shell in Block-Chain Technology with ELM as Inference Engine

Knowledge society blockchain is one of the most powerful and recent tools to make the internet environment safer and reliable. Manufacturing has traditionally been dominated by standard designs that are mass-produced, due to the fact, that custom production causes additional costs that make it less affordable than mass production. This paper proposes to develop a designer expert system for IoT installation layout designs, using blockchain distributed system based on a machine learning, with users entering data to the expert system by a smart bot software. This expert system will work using extreme learning machine as inference engine; therefore, this is a shell to develop any expert system with fast learning. The whole system is represented by a smart contract with a value linked to the value of the expert system, the more this expert system be quoted on the web, the more the shares of the smart contract will cost.

Android-Based Dental and Oral Health Diagnostic Expert System

Dental and oral health is one of the most crucial thing for human health. If it is taken cared properly then all foods will be absorbed optimaly and human body will have all the nutritions needed. Otherwise, if it is not taken cared properly then it will affects health condition of a human body. Lack of awareness of Indonesians about their dental and oral health had caused many of infection cases which leads to teeth structural damage. In 2013, Health Research and Development Agency had done a survey based on interview’s result. They found that 25,9 percent of people in Indonesia were having issues with their dental and oral health in the last 12 months. Among them, there was 68,8 percent people who had not taken an treatments. To resolve this problem, expert system with android platform is made to diagnose dental and oral diseases. The research methodology used is forward chaining method. Expert System Shell used is CLIPS which then adopted into Android application.

A Fault Diagnosis Expert System for Commercial Bus Manufacturing process

Bus manufacturing is one of the important assets in automotive industries as well as mode of public transportation. The design process is difficult and long throughout time. Moreover, there are many manuals, rules and regulation according to different standard which make the standardization and design process to be difficult and time consuming. Hence, this project describes the use of an expert system shell for commercial bus design. In bus manufacturing field, design of commercial bus is heavily depending on human experts. With the help of expert system, process of design commercial bus will be shortened up to 56.5% compared to conventional way. The developed system can be used as a training module for inexperienced personnel. In this research work, the fault diagnosis system was developed by using Kappa-PC expert system shell. It is supported by object orientated technology for the MS window environment. Lastly, the developed system will be validated with a case study to verify the capability of the developed system.