Sistem Pakar Mengidentifikasi Kerusakan Pada Mesin Electronic Data Capture Ingenico Ict 250 Dengan Metode Forward Chaining
Abstract
The sophistication of technology today is really fast, with this technology it can facilitate work that originally used a manual system to switch to an automatic system and can be applied in everyday life, one of which is a substitute system for an expert or expert system. The EDC (electronic data capture) machine is indeed one of the supporters and triggers for accelerating the new culture. Financial transactions at the consumer level are easier to do, currently a new EDC machine technician working at PT. Indopay Merchants Services, which has its head office in Menara Batavia, Mas Mansyur 9th Floor, Jakarta, and a warehouse branch office in Semarang, takes a long time to diagnose the damage that occurred to an EDC machine. The development of expert systems can be used to provide solutions quickly and precisely, for example in determining the type of damage to the EDC machine. The solution to this problem, the author tries to build an application that will help make it easier for EDC machine technicians to provide solutions. An expert system is a system that tries to imitate human knowledge to a computer, so that computers can solve problems like experts. A good expert system is designed to be able to solve a certain problem by imitating the work of experts. It is hoped that the existence of an expert system to analyze the damage to the EDC machine will make it easier for new technicians to diagnose and study a malfunction that has occurred as well as provide convenience for user management and machine optimization at merchants.
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Amanda, N. F., & Setyo, A. E. (2016). SISTEM PAKAR DETEKSI KERUSAKAN MESIN DIESEL PLTD MENGGUNAKAN METODE FORWARD CHAINING. Jurnal Informatika Polinema, 2(1).
Imron, I., Afidah, M. N., Nurhayati, M. S., Sulistiyah, S., & Fatmawati, F. (2019). Sistem Pakar Diagnosa Kerusakan Mesin Sepeda Motor Transmission Automatic dengan Metode Forward Chaining Studi Kasus: AHASS 00955 Mitra Perdana. Jurnal Ilmiah Universitas Batanghari Jambi, 19(3). https://doi.org/10.33087/jiubj.v19i3.742
Maulana, B., & Haryanto, D. (2018). Sistem Pakar Diagnosa Kerusakan Mesin Sepeda Motor Matic Honda Karburator Dengan Metode Forward Chaining. Jumantaka, 1(1).
Merlina, N. (2016). Sistem Pakar Diagnosa Kerusakan Pada Mesin Pendingin Ruangan Dengan Metode Forward Chaining. None, 12(1).
Muthohir, M., & Zainudin, A. (2018). Penerapan metode simple additive weight (saw) pada sistem informasi pemilihan jurusan berbasis decision support system. Smart Comp: Jurnalnya Orang …, 7.
Nazarudin, N., Saputra, A., & Khumaini, H. (2017). SISTEM PAKAR DIAGNOSA KERUSAKAN MESIN SEPEDA MOTOR YAMAHA DI COMPION MOTOR DUMAI. I N F O R M A T I K A, 9(1). https://doi.org/10.36723/juri.v9i1.86
Noviardi, R. (2020). SISTEM PAKAR BERBASIS WEB MENGGUNAKAN METODE FORWARD CHAINING DALAM MENGANALISA KERUSAKAN MESIN FOTOKOPI DAN PENANNGGULANGANNYA (STUDY KASUS DI Q-EL COPIER SERVICE CENTER AND DISTRIBUTOR). JURTEKSI (Jurnal Teknologi Dan Sistem Informasi), 6(2). https://doi.org/10.33330/jurteksi.v6i2.548
Rakasiwi, S., & Kusumo, H. (2021). Utilization of E-money for School Payments Using Web-Based RFID Sensors. Advance Sustainable Science, Engineering and Technology, 3(2). https://doi.org/10.26877/asset.v3i2.9721
Refli Noviardi. (2020). Sistem Pakar Berbasis Web Menggunakan Metode Forward Chaining Dalam Menganalisa Kerusakan Mesin Fotokopi Dan Penannggulangannya (Study Kasus Di Q-El Copier Service Center and Distributor). JURTEKSI (Jurnal Teknologi Dan Sistem Informasi), 53(9).
Rusdiansyah, R., & Rantau, F. (2018). Sistem Pakar Untuk Mendiagnosa Kerusakan Mesin Sepeda Motor Matic Dengan Metode Forward Chaining. Jurnal Pilar Nusa Mandiri, 14(1).
Savitri, P., & Hadi, T. (2018). IMPLEMENTASI METODE FORWARD CHAINING DALAM SISTEM PENDETEKSI KERUSAKAN HARDWARE PADA KOMPUTER DAN LAPTOP BERBASIS ANDROID. Simetris: Jurnal Teknik Mesin, Elektro Dan Ilmu Komputer, 9(1). https://doi.org/10.24176/simet.v9i1.2004
DOI: https://doi.org/10.31294/evolusi.v10i1.12454
ISSN: 2657-0793 (online). ISSN: 2338-8161 (print)