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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal ABDIMAS (Pengabdian kepada Masyarakat) UBJ Jurnal Dharmabakti Nagri International Journal of Information Technology and Computer Science Applications (IJITCSA) Seminar Nasional Inovasi Teknologi AMMA : Jurnal Pengabdian Masyarakat Journal of Informatics and Information Security
Ajif Yunizar Pratama Yusuf
Fakultas Ilmu Komputer; Universitas Bhayangkara Jakarta Raya
Religion Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing Social Sciences Other

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Journal : Journal of Informatics and Information Security

 1 
Implementasi Algoritma K-Means Clustering Menggunakan Aplikasi Orange Untuk Mengetahui Pola Indeks Pembangunan Manusia Tahun 2022 Kaylista N.N.K; Nabiilah Khoirunnisaa; Gading Viewianti E.N.F; Ajif Yunizar Pratama Yusuf
Journal of Informatic and Information Security Vol. 4 No. 1 (2023): Juni 2023
Publisher : Program Studi Teknik Informatika, Fakultas Teknik Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/m50n5t48

Abstract

The Human Development Index (HDI) is used as a statistical parameter to evaluate the progress and quality of human life in a country. Human development plans are measured through three basic aspects: a long and healthy life, knowledge, and a decent standard of living. The research focuses on the application of k-means algorithms to identify patterns and group 34 provinces in Indonesia based on indicators that form the 2022 HDI. These indicators include life expectancy (UHH), school life expectancy (HLS), average school time (RLS), and spending. This HDI grouping aims to identify the HDI variables that should be a priority in development. The results of the analysis showed the formation of two groups (clusters) through K-Means Cluster Analysis. Cluster 1 has provincial characteristics with high to very high values on UHH, HLS, RLS, and customized output. Meanwhile, Cluster 2 consists of provinces with medium to high values on UHH, HLS, RLS, and adjusted output.
Decision Making Using Hierarchical Analytical Processes to Evaluate Computer Management Performance Ajif Yunizar Pratama Yusuf; Kusdarnowo Hantoro; Rani Suryani
Journal of Informatic and Information Security Vol. 3 No. 1 (2022): Juni 2022
Publisher : Program Studi Teknik Informatika, Fakultas Teknik Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/2h4c2d76

Abstract

The presence of PC computers since the 80s with its rapid and very widespread growth can be seen as a one of the most significant developments in the field of information and communication technology. This study aims to propose decision making using the Analytical Hierarchy Process approach to evaluate computer computers with respect to using the order of preference of the user. To get the most desirable features that affect the decision to choose a computer to be identified. This is realized through a survey conducted on the target group, experienced experts in the telecommunications sector and literature study. The AHP methodwas then used in the evaluation procedure. Analytical Hierarchy Process (AHP) was applied to determine the relative weight of the evaluation criteria applied to rank computer alternatives. The results of this case study illustrate the effectiveness of the proposed computer management performance selection.
Metode SAW (Simple Additive Weighting) Untuk Pemilihan Karyawan Terbaik Kusdarnowo Hantoro; Andy Achmad Hendharsetiawan; Ajif Yunizar Pratama Yusuf
Journal of Informatic and Information Security Vol. 2 No. 2 (2021): Desember 2021
Publisher : Program Studi Teknik Informatika, Fakultas Teknik Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/9jt32f24

Abstract

The purpose of determining the best employees is as an appreciation for employee performance so as to motivate employees to be able to work optimally and be able to survive in the organization for a long time. Although the goal is very simple, however, the process turns out to be very complex, takes quite a long time and costs quite a bit so that this creates the opportunity for errors to occur in determining who is the right person. Especially if the company has employees with abilities that are not much different from other employees, the determination is sometimes very subjective. Actually there are several assessment criteria in the decision-making process for selecting the best employees, namely: an assessment based on the criteria for attendance, loyalty, and tardiness and employee performance. Because it is necessary to build a system that can assist decision making to determine the selection process objectively by using the SAW (Simple Additive Weighting) method.
Implementasi Algoritma Naïve Bayes untuk Klasifikasi Pemahaman Program MBKM bagi Mahasiswa Ajif Yunizar Pratama Yusuf; Rafika Sari
Journal of Informatic and Information Security Vol. 3 No. 2 (2022): Desember 2022
Publisher : Program Studi Teknik Informatika, Fakultas Teknik Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/40dppk38

Abstract

Outcome based education is the basis for the Informatics Study Program at Bhayangkara Jakarta Raya University (Ubhara Jaya) in formulating graduate profiles. Research to identify student knowledge related to MBKM. The analytical approach ranks 25 questions in the MBKM program which are the focus of students and lecturers. Through the survey conducted, it will provide an overview of whether the MBKM program has an attraction for students to develop their competencies, skills and soft skills as a provision for future graduates. In addition, do students and lecturers assess the MBKM program as having significant benefits in improvingstudent abilities? The research was conducted by implementing data mining survey results of students and lecturers in depth. The method used is a classification learning ensemble. The classification process begins with collecting available data, preprocessing data in the form of feature selection, cleaning, integration, and transformation; continued with the process of making models on training data by applying 10-fold cross validation and the assembly learning method to handle imbalance classes; and finally evaluation of modeling results on data testing. The output target of this research is a policy recommendation for implementing the MBKMprogram for the Ubhara Jaya Informatics study program.
Co-Authors Adi Muhajirin Agus Setyawan Ahmad Dedi Jubaedi Andy Achmad Hendharsetiawan Beno Aditya Sanusi Bhagaskara Farhan Wiguna Dr. Tb. Ai Munandar, S.Kom., MT Endang Retnoningsih Fata Nidaul Khasanah Gading Viewianti E.N.F Gedhe Hilman Wakhid Hantoro, Kusdarnowo Harsiti Harsiti Herlawati Herlawati Illa Nur’aini Kaylista N.N.K Khairunnisa Fadhilla Ramdhania Muhammad Ganang Martyana Muhammad Salam Asyidqi Nabiilah Khoirunnisaa Ozzi ardhiyanto Prima Dina Atika Purnomo, Rakhmat RAFIKA SARI Rani Suryani Reghita Suryani Putri Renilda Filiandini Syifa Rahmadhani Tb Ai Munandar Tyastuti Sri Lestari