Rahayu, Raden Erwin Gunadi
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Pengembangan Sistem Pakar Diagnosa Kerusakan Motor Injeksi Matic Menggunakan Forward Chaining dan Expert System Development Nugraha, Insan Satia; Agustin, Yoga Handoko; Rahayu, Raden Erwin Gunadi
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1493

Abstract

Technological progress at this time is extremely rapid in the field of transportation, one of which is automatic injection motorbikes, for automatic injection motorbikes there are definitely obstacles or problems in reducing the performance of ordinary motorbikes. In this case, many automatic injection motorbikes go to the Ahass Fahya Jaya Motor workshop, in This problem should be done with simple checks, such as checking the spark plug, checking the battery and etc. In checking small things, the author has created a professional system application by providing the knowledge of experienced experts and has received a certificate from Ahass, anticipating that this application may be useful for readers or users of the application. In making this expert system application there are several features, one of which can be accessed by the admin with a certain code, later the user will enter the full name, email and motorbike series, the administrator can change the symptoms of damage, change the solution and also add application knowledge. Based on these problems, we obtained a knowledge base of 20 damage data and 23 symptoms obtained from visits to Ahass Fahri Jaya Motor. Selecting the forward chaining method can efficiently produce solutions by combining existing knowledge rules and known facts. Meanwhile, choosing the Expert System Development Life Cycle methodology for expert systems can be carried out in a more structured, efficient and effective manner. This methodology helps in producing high quality, accurate and reliable expert systems in supporting decision making in a particular domain. Based on user testing or at the usability testing stage, it has an accuracy value of 95% from the 26 automatic injection motor damage diagnosis test data carried out.
Pengembangan Sistem Pakar Diagnosa Kerusakan Motor Injeksi Matic Menggunakan Forward Chaining dan Expert System Development Nugraha, Insan Satia; Agustin, Yoga Handoko; Rahayu, Raden Erwin Gunadi
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1493

Abstract

Technological progress at this time is extremely rapid in the field of transportation, one of which is automatic injection motorbikes, for automatic injection motorbikes there are definitely obstacles or problems in reducing the performance of ordinary motorbikes. In this case, many automatic injection motorbikes go to the Ahass Fahya Jaya Motor workshop, in This problem should be done with simple checks, such as checking the spark plug, checking the battery and etc. In checking small things, the author has created a professional system application by providing the knowledge of experienced experts and has received a certificate from Ahass, anticipating that this application may be useful for readers or users of the application. In making this expert system application there are several features, one of which can be accessed by the admin with a certain code, later the user will enter the full name, email and motorbike series, the administrator can change the symptoms of damage, change the solution and also add application knowledge. Based on these problems, we obtained a knowledge base of 20 damage data and 23 symptoms obtained from visits to Ahass Fahri Jaya Motor. Selecting the forward chaining method can efficiently produce solutions by combining existing knowledge rules and known facts. Meanwhile, choosing the Expert System Development Life Cycle methodology for expert systems can be carried out in a more structured, efficient and effective manner. This methodology helps in producing high quality, accurate and reliable expert systems in supporting decision making in a particular domain. Based on user testing or at the usability testing stage, it has an accuracy value of 95% from the 26 automatic injection motor damage diagnosis test data carried out.