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All Journal Journal of Innovation and Future Technology (IFTECH) Jurnal Pengabdian Masyarakat Nusantara
Irfan Sadida
Universitas ‘Aisyiyah Surakarta
Computer Science & IT Education Electrical & Electronics Engineering Engineering Health Professions Library & Information Science Social Sciences Other

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PENINGKATAN KETERAMPILAN DESAIN GRAFIS BAGI MAHASISWA AISKA UNIVERSITY DALAM MENGHADAPI ERA 4.0: IMPROVING GRAPHIC DESIGN SKILLS FOR AISKA UNIVERSITY STUDENTS IN ERA 4.0 Irfan Sadida; M. Gunawan Setyadi; Aisyah Mutia Dawis
Jurnal Pengabdian Masyarakat Nusantara Vol. 4 No. 3 (2022): September : Jurnal Pengabmas Nusantara
Publisher : Universitas Muhammadiyah Manado

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (699.335 KB) | DOI: 10.57214/pengabmas.v4i3.115

Abstract

The rapid development of technology is very influential on institutions, society and even universities. At this time, the role of graphic design in all fields is needed. This can be proven by the many fields of business that utilize the expertise of graphic designers. The shifting habit of using digital media in human activities has made the use of design as media promotion increasingly widespread in the business world. Examples of promotional media include brochures, leaflets, posters, business cards, billboards, banners, and banners. This illustrates that graphic design skills are important things that students need to have in this modern era. Therefore, it is important to hold graphic design training as an initial means for students to improve their ability to produce a quality graphic design work.
EXPLORING COMPLEX DECISION TREES: UNVEILING DATA PATTERNS AND OPTIMAL PREDICTIVE POWER Ismail Setiawan; Renata Fina Antika Cahyani; Irfan Sadida
Journal of Innovation And Future Technology (IFTECH) Vol 5 No 2 (2023): Vol 5 No 2 (August 2023): Journal of Innovation and Future Technology (IFTECH)
Publisher : LPPM Unbaja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/iftech.v5i2.2829

Abstract

This research investigates the development and analysis of decision tree models in the context of classification tasks. Decision tree models were developed without employing pruning or pre-pruning techniques and were tested on relevant datasets. The research findings demonstrate that complex models without pruning achieved the highest level of accuracy in classifying data. This study was inspired by the potential issue of students facing the risk of not completing their studies (dropout), which could lead to a decline in the college's accreditation rating. Therefore, this model was devised to assist in identifying factors that could influence this outcome as a preventative measure. Additionally, we successfully generated clear visualizations of the decision trees, enhancing the understanding of the model's decision-making process. This research provides insights into the adaptability of decision tree models within this specific case and showcases their potential for enhancing decision-making across various contexts. These findings encourage further discussions on the benefits of pruning methods within this specific context and the broader application potential of decision tree models.
Co-Authors Aisyah Mutia Dawis Ismail Setiawan M. Gunawan Setyadi Renata Fina Antika Cahyani