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All Journal Jurnal CoreIT Buana Information Technology and Computer Sciences (BIT and CS) JOLLT Journal of Languages and Language Teaching SIENNA
Triraharjo, Bambang
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Computer Science & IT Engineering Languange, Linguistic, Communication & Media

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Journal : buana information technology and computer sciences bit and cs

 1 
Implementation of Orange Data Mining to Predict Student Graduation on Time at Pringsewu Muhammadiyah University Novianto, Roby; Triraharjo, Bambang; Baskoro
Buana Information Technology and Computer Sciences (BIT and CS) Vol 5 No 1 (2024): Buana Information Technology and Computer Sciences (BIT and CS)
Publisher : Information System; Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36805/bit-cs.v5i1.6073

Abstract

Thel prolcelss olf molnitolring and elvaluating thel graduatioln olf Muhammadiyah Pringselwu Univelrsity (UMPRI) studelnts relally nelelds tol bel dolnel belcausel thel studelnt graduatioln ratel is an ellelmelnt olf accrelditatioln asselssmelnt that is velry impolrtant folr elach Study Prolgram. Data Mining can bel useld tol classify studelnt graduatioln accuracy. This study aims tol apply thel olrangel data mining applicatioln using thel K-Nelarelst Nelighbolr (K-NN), Delcisioln Trelel and Naivel Bayels moldells and will theln elvaluatel thel accuracy olf elach olf thelsel moldells. This relselarch was colnducteld at Pringselwu Muhammadiyah Univelrsity in selvelral batchels, theln studelnt data will bel analyzeld using thel olrangel data mining applicatioln using thel K-NN, Delcisioln Trelel and Naivel Bayels moldells. Thel data telsting prolcelss appliels K-Folld Crolss Validatioln (K=5), whilel thel elvaluatioln moldell useld is thel Colnfusioln Matrix and ROlC. Thel relsults olf thel colmparisoln olf thel threlel moldells arel as folllolws, K-NN has an accuracy ratel olf 75.7%, Delcisioln Trelel has an accuracy ratel olf 78.1%, and Naivel Bayels has an accuracy ratel olf 77.8%. Thelrelfolrel, folr classifying thel graduatioln ratel olf Muhammadiyah Univelrsity studelnts, Pringselwu relcolmmelnds thel Delcisioln Trelel moldell belcausel it has a belttelr lelvell olf accuracy than K-NN and Naivel Bayels.
Implementation of the C4.5 Algorithm in Predicting the Interest of Prospective Students in Choosing Higher Education Triraharjo, Bambang; Ayu Minarni, Prilian; Baskoro
Buana Information Technology and Computer Sciences (BIT and CS) Vol 6 No 1 (2025): Buana Information Technology and Computer Sciences (BIT and CS) (InProcess)
Publisher : Information System; Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36805/bit-cs.v6i1.7697

Abstract

Data governance involves setting internal standards for how data is collected, stored, processed and deleted. In the context of the oil industry, data governance can intervene at the level of oil exploration and production to manipulate data in particular. In our contribution, we explain how Fuzzy c - means based machine learning can be used for oil data governance. This deep artificial intelligence concept, which we will use in addition to fuzzy logic, by applying Fuzzy c - means for good training can enable the decision-maker a better governance policy.
Co-Authors Adi Wibowo Aulia, Mega Ayu Minarni, Prilian Baskoro Baskoro Baskoro, Baskoro Dian Pratiwi Miftahunnajah, Syifa Novianto, Roby Nugroho, Adam Qori'ah, Aisyatul Vidyah Surya, Ridho Pamungkas Ibnu