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All Journal Jurnal Abadimas Adi Buana Jurnal ULTIMA InfoSys Journal of Information System and Computer
Wildani Eko Nugroho
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Humanities Computer Science & IT Economics, Econometrics & Finance Energy Public Health Other

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Pengenalan Aeromodelling Berbasis IT Untuk Menumbuhkan Jiwa Wirausaha Dan Prestasi Di SMK NU Tarub Tegal Jatmiko Indriyanto; Wildani Eko Nugroho; Nurohim
Jurnal Abadimas Adi Buana Vol 4 No 2 (2021): Jurnal Abadimas Adi Buana
Publisher : LPPM Universitas PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/abadimas.v4.i2.a2721

Abstract

The basic problem of SMK graduates is that most are still looking for work in companies, because the number of SMK graduates is not comparable to the employment opportunities in companies, so many are unemployed. Unemployment is open at the level of SMK graduates is still high. The results of an analysis of the economic potential of the open unemployment data in 2015 showed that over one third or 36.78% of vocational school graduates were still unemployed. Education and training for job seekers has not been maximally organized by the Tegal City Government to encourage them to become new entrepreneurs (WUB). There are still many vocational students who have difficulty getting into state universities because of lack of achievement. The government has provided a path of achievement, the selection process focuses on academic and non-academic achievements during high school / equivalent Seeing the above problems, the introduction of IT-based Aeromodelling to Grow Entrepreneurial Soul and Achievement, can increase student interest to switch his mind to try entrepreneurship and achievement. The introduction of IT-based Aeromodelling for Growing an Entrepreneurial Soul and Achievement turned out to be able to, increase students' interest in entrepreneurship and achievement in non-academic fields.
OPTIMALISASI METODE NAIVE BAYES DAN DECISION TREE UNTUK MENENTUKAN PROGRAM STUDI BAGI CALON MAHASISWA BARU DENGAN PENDEKATAN UNSUPERVISED DISCRETIZATION Wildani Eko Nugroho; Heru Saputro
Journal of Information System and Computer Vol. 2 No. 1 (2022): Juli 2022
Publisher : Universitas Islam Nahdlatul Ulama Jepara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34001/jister.v1i2.257

Abstract

Higher Education is a place for providing education that aims to produce quality human resources and is able to face increasingly fierce job competition. Therefore, from the recruitment process or the admission process, prospective new students must consider various procedures that aim to be able to direct prospective new students in determining the study program that will be taken by prospective new students. The things that have been broken in the admission process for new students include the scores of national exam results, report cards, school test scores and the admission test for new students, as well as the admission process of the achievement path and aiming for missions. From these things, performance must be improved is a supporting factor so that the process of transforming educational science to students can be carried out properly. The purpose of this study is to obtain classification in determining the study program of prospective new students by optimizing the Naïve Bayes and Decision Tree methods with an Unsupervised Discretization Approach, as an effort to improve the internal quality assurance system, especially the standards for the admission process for new students in determining study programs at the Harapan Polytechnic with Tegal. Where in the process of accepting new students, planning, implementing, evaluating, and monitoring have been carried out as a form of implementing the Internal Quality Assurance System (SPMI). In this study, the data used was data on the results of the admission of prospective new students from all study programs. These data include data on the administrative completeness of the requirements of prospective new students, as well as data on the value of the results of the new student admission test. The data used is data for 1 academic year 2019/2020. From this data, training and testing will be carried out using Rapidminer 9, a classification of lecturer teaching performance will be obtained.
Use of the K-Medoids Algorithm for Food Clustering Using Nutritional Value and Evaluation of the Elbow Method and the Davies Bouldin Index Method Wildani Eko Nugroho; Dwi Kurniawan, Safar; Febrian Sabanise, Yerry; Prayoga, Prayoga
ULTIMA InfoSys Vol 16 No 1 (2025): Ultima InfoSys : Jurnal Ilmu Sistem Informasi
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/si.v16i1.4226

Abstract

The six categories of necessary nutrients water, minerals, vitamins, carbs, proteins, and fats must be present in the food that people eat on a daily basis. Humans require nutrition since it will enable them to do everyday duties and maintain their health. The pupose of this study is to classify foods with comparable nutritional values. Foods with high, medium, and low nutritional levels are grouped into three clusters. This study applies the K-Medoids algorithm optimization to the clustering approach. The study’s clustering results can be utilized to choose and consume foods that will meet nutritional needs and help delay the onset of food related disorders. For instance, if you wish to gain weight, you can choose foods in cluster 0. Cluster 2 foods can be picked if you wish to diet or lose weight, while Cluster 1 meals can serve as a benchmark if taken in excess, as this can lead to obesity.
Co-Authors Arif Rakhman Dany Artha Widiyanto Febrian Sabanise, Yerry Haryo Guritno Heru Saputro Jatmiko Indriyanto Nurohim Nurohim Oman Somantri Prayoga Prayoga Safar Dwi Kurniawan