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Journal : INFOKUM

EXPERT SYSTEM FOR TROUBLESHOOTING LAPTOP MOTHERBOARD DAMAGE USING FORWARD CHAINING METHOD AT BUDI DARMA UNIVERSITY COMPUTER LAB Hery Sunandar; Berto Nadeak; Pristiwanto; Saidi Ramadan Siregar
INFOKUM Vol. 9 No. 1,Desember (2020): Data Mining, Image Processing,artificial intelligence, networking
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (336.378 KB)

Abstract

The development of laptop hardware technology in the 21st century is increasingly rapid to support information technology that is increasingly easily accessed. Laptops have an important role in helping human activities, especially in teaching and learning activities. Not infrequently a laptop or better known as a laptop as most students and lecturers and even students who sit in secondary education have started to use it. In national tertiary education, the entire campus requires both public and private universities to have laptop laboratories. Along with these developments in the case of laptop usage is getting bigger.
Determination Of Budi Darma University Ordering Patterns Needs With Apriory Algorithm Hery Sunandar; Abdul Sani Sembiring
INFOKUM Vol. 10 No. 1 (2021): Desember, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (914.954 KB)

Abstract

In a university, office stationery is needed to support the teaching and learning process, one of which is paper, markers, ink and so on. In determining the right strategy in terms of purchasing stationery, an effective analysis is needed, to reduce excessive spending. One way that can be done to order stationery is to use data mining techniques. The data mining technique used in this case is to use the Apriori algorithm. The a priori algorithm is one of the classical data mining algorithms. The a priori algorithm is used so that computers can learn association rules, look for patterns of relationships between one or more items in a dataset. This research was conducted by observing several research variables that are often considered by universities in ordering office stationery. (ATK). The results of this study are in the form of interesting patterns of data mining results which are important information to support ordering stationery