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All Journal Jurnal Pengabdian Bukit Pengharapan Novatio : Journal of Management Technology and Innovation Jurnal Lentera ICT
Prasetyo, Karno Ganjar
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Computer Science & IT Decision Sciences, Operations Research & Management Other

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PENGEMBANGAN KETERAMPILAN SISWA SMK UNTUK DUNIA KERJA MELALUI WORKSHOP CUSTOMER SERVICE EXCELLENCE DAN VIRTUAL ASSISTANT: studi kasus : SMK Mutiara Bangsa Tajur Halang kabupaten Bogor Kusmayanti, Kusmayanti; Prasetyo, Karno Ganjar
Jurnal Pengabdian Bukit Pengharapan Vol. 4 No. 1 (2024)
Publisher : LPPM Institut Teknologi dan Bisnis Kristen Bukit Pengarapan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61696/jurdian.v4i3.506

Abstract

This Community Service Program (PkM) aims to develop the skills of Mutiara Bangsa Vocational School students in facing the world of work through Customer Service Excellence and Virtual Assistant workshops. This activity is carried out with an approach based on improving service quality and utilizing digital technology, in accordance with current industry needs. Students are trained to understand professional customer service concepts, such as responsiveness, empathy and reliability, and are given practical skills in operating virtual assistant technology. The results of the training show a significant increase in student competency, which is expected to build their confidence to compete in a competitive job market. This program contributes to improving the quality of vocational education and preparing students for the world of work with more relevant and applicable skills.
Cybersecurity and Innovation Risk Management: Organizational Responses in the Digital Era Noviany, Henny; Prasetyo, Karno Ganjar
Novatio : Journal of Management Technology and Innovation Vol. 3 No. 4 (2025): October 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/novatio.v3i4.1029

Abstract

The rapid pace of digital transformation has reshaped healthcare, finance, and energy sectors, creating opportunities for innovation while amplifying vulnerabilities to cyber threats. This narrative review synthesizes organizational responses to cybersecurity and innovation risk management across global contexts. Literature was systematically collected from Scopus, Web of Science, PubMed, and Google Scholar using defined keywords and inclusion criteria, with thematic synthesis guided by review standards. Four central themes emerged: (1) the effectiveness of secure access and identity management in protecting sensitive data, (2) the integration of artificial intelligence and blockchain in predictive modeling and threat detection, (3) measurable improvements in resilience through advanced technological adoption, and (4) the influence of systemic and structural factors, including governance frameworks and international collaboration. Evidence highlights disparities between developed and developing regions, where resource and infrastructure limitations hinder adoption. The discussion links findings with resilience theory while noting limitations such as the neglect of SMEs, dominance of Western perspectives, and reliance on secondary data. Policy implications emphasize capacity-building, harmonized frameworks, and innovation-driven cultures. Comprehensive, collaborative, and context-sensitive approaches are essential for advancing cybersecurity resilience in the digital era.
ANALISIS PERBANDINGAN ALGORITMA DECISION TREE DENGAN SUPPORT VECTOR MACHINE UNTUK MENDETEKSI KOMPETENSI MAHASISWA KONSENTRASI INFORMATIKA KOMPUTER STUDI KASUS : POLITEKNIK LP3I JAKARTA, KAMPUS DEPOK Prasetyo, Karno Ganjar
JURNAL LENTERA ICT Vol. 5 No. 2 (2019): JURNAL LENTERA ICT
Publisher : POLITEKNIK LP3I JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Detection of computer informatics student competence is indispensable for anticipating students who have a very poor performance in following the learning process in an educational institution for the purpose of all educational institutions are creating a qualified student. It can be seen in the results of the 5th and 6th semester students who have gained employment. Polytechnic LP3I Jakarta Depok one vocational education institution founded to create a human being who has the ability / skills required by the company so that the concept is to offer education that have Link and Match. Competitors who have the same goals is one of the challenges to be faced by the agency so we need a solution to overcome it. One solution is the detection of computer informatics student competence of students. This can be done by using data mining techniques. One data mining techniques used are support vector machines (SVM). Support vector machine method is able to overcome the problem of high-dimensional, addressing the problem of classification and regression with linear or nonlinear kernel that can be the ability of learning algorithms for classification and regression, but the support vector machine has a problem in the appropriate parameters. To overcome these problems required method of decision tree as a comparison, for the selection of appropriate parameters. Several experiments were conducted to obtain optimum accuracy. Experiments using support vector machine and decision tree which is used to optimize the parameters C, and ε population. Training data used computer informatics student data from 2012 to 2014 academic year. The experimental results show the decision tree method of data that is equal to 92.50% with a ratio of 60 training data were compared with data vector machine that is equal to an accuracy of 92.56% and the second T-Test metod done that method has a probability value of < 0.05 which algorithm C4.5.Keywords: Detection, Competence, Support Vector Machine, Decision Tree
Co-Authors Kusmayanti, Kusmayanti Noviany, Henny