Article Per Year (5 Year)
p-Index From 2021 - 2026
4.347
P-Index
This Author published in this journals
All Journal Dinamik Sistemasi: Jurnal Sistem Informasi Jurnal Ilmiah FIFO ILKOM Jurnal Ilmiah KOMPUTIKA - Jurnal Sistem Komputer Building of Informatics, Technology and Science TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Teknik Informatika (JUTIF) Jurnal Pendidikan dan Teknologi Indonesia Jurnal Algoritma Paradigma Jurnal Ilmiah Edutic : Pendidikan dan Informatika Jurnal Ilmiah Informatika dan Ilmu Komputer CHAIN: Journal of Computer Technology, Computer Engineering and Informatics Journal of Artificial Intelligence and Technology Information Journal of Information Technology, Software Engineering and Computer Science Bulletin of Artificial Intelligence Jurnal Informatika dan Rekayasa Perangkat Lunak
Aditia Yudhistira
Universitas Teknokrat Indonesia
Aerospace Engineering Arts Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other

Published : 33 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 33 Documents
Search

 1   2   3   4 
Sistem Pendukung Keputusan untuk Evaluasi Kinerja Menggunakan Metode TOPSIS: Studi Kasus Penilaian Karyawan Aditia Yudhistira; Tri Widodo
CHAIN: Journal of Computer Technology, Computer Engineering, and Informatics Vol. 2 No. 3 (2024): Volume 2 Number 3 July 2024
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/chain.v2i3.145

Abstract

Employee performance evaluation is a systematic process carried out by an organization to assess the contribution, ability, and achievement of individuals in carrying out their duties and responsibilities. This process is not only aimed at identifying the best performers, but also to uncover potential employee development as well as areas for improvement. Employee performance evaluations often face challenges in ensuring the objectivity of the assessment, especially when relying on the subjective perception of the appraiser. Traditional methods often rely on the subjectivity of the assessor, which can result in less accurate or unfair evaluations. In addition, in organizations that have many employees with diverse backgrounds and tasks, consistent and comprehensive assessments are becoming increasingly difficult. The purpose of this study is to implement SPK based on the TOPSIS method to evaluate employee performance objectively and systematically, as well as to increase transparency and consistency in the employee performance evaluation process. The ranking results show the ranking of employee performance evaluation results based on the scores obtained by each candidate. Candidate AF ranked first with the highest score of 0.8471, followed by Candidate SR with a score of 0.7055 got second place. The third position was occupied by HA Candidate with a score of 0.4975. The results of this ranking provide an overview of each candidate's overall performance.
Analysis of Immunization Coverage Among Toddlers in Indonesia using the K-Means Algorithm based on 2025 People’s Welfare Data Maria Angelina Luisa Makin; Aditia Yudhistira
Sistemasi: Jurnal Sistem Informasi Vol 15, No 3 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i3.6203

Abstract

Disparities in toddler immunization coverage across different regions of Indonesia indicate the need for an analytical approach capable of capturing regional characteristics in greater depth. This study aims to cluster toddler immunization coverage using the K-Means algorithm based on the 2025 Indonesian People’s Welfare Data published by Statistics Indonesia. The variables analyzed include immunization history, types of immunization, place of immunization, and immunization providers. Data processing was conducted using Python through the Google Colab platform. The determination of the optimal number of clusters using the Elbow Method resulted in three clusters, with a Silhouette Score of 0.5086, indicating a moderately good clustering quality. The results show that the cluster labeled Low surprisingly exhibits the highest immunization coverage (95.68%), suggesting that the cluster labels do not represent coverage levels in a linear manner but instead reflect differences in operational characteristics and the distribution of immunization services across regions. Meanwhile, the Medium cluster shows the lowest coverage (63.82%), and the High cluster falls at an intermediate level (92.23%). Further analysis indicates that the type of immunization and immunization history are the most influential variables in cluster formation. With clustering quality categorized as moderately good, the K-Means method is considered capable of adequately identifying immunization coverage patterns for region-based policy analysis. These findings demonstrate that a clustering approach can reveal immunization coverage patterns that are not captured through conventional statistical analysis and can serve as a basis for more targeted and data-driven immunization policy formulation.
Segmentasi Gudang E-Commerce Berdasarkan Biaya Logistik dan Pola Transaksi Menggunakan Metode K-Means dan Fuzzy C-Means Saidina Ali Habib; Aditia Yudhistira
Jurnal Algoritma Vol 23 No 1 (2026): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.23-1.3457

Abstract

Sistem distribusi multi-gudang e-commerce menghadapi tantangan segmentasi data logistik akibat karakteristik transaksi yang heterogen, tidak seimbang, dan memiliki overlap antarvariabel yang tinggi. Penelitian ini bertujuan melakukan segmentasi gudang berdasarkan biaya logistik dan pola transaksi menggunakan algoritma K-Means dan Fuzzy C-Means. Penelitian mengintegrasikan feature engineering berbasis rasio melalui Logistics Cost Ratio (LCR), Value Density (VD), dan Transaction Intensity (TI), serta menerapkan robust scaling dan outlier trimming sebesar 1% untuk meningkatkan stabilitas clustering. Dataset terdiri dari 13.550 transaksi dari empat gudang utama dengan 13.284 data valid setelah preprocessing. Evaluasi dilakukan menggunakan Silhouette Score, Davies-Bouldin Index (DBI), dan Calinski-Harabasz Index (CHI). Hasil penelitian menunjukkan bahwa K-Means dengan k = 3 menghasilkan performa terbaik dengan Silhouette Score sebesar 0,421, DBI sebesar 0,584, dan CHI sebesar 12.273,98. Transformasi fitur berbasis rasio terbukti menghasilkan distribusi cluster yang lebih seimbang dan interpretatif dibandingkan penggunaan data mentah. Segmentasi yang dihasilkan terdiri atas cluster efisiensi tinggi, cluster transaksi reguler, dan cluster beban logistik tinggi yang dapat digunakan sebagai dasar pengambilan keputusan distribusi logistik berbasis data pada sistem multi-gudang e-commerce.
Co-Authors Adamansyah, Eka Putri Ahmad Ari Aldino Akil Thalib Anggoro, Bayu Ari Sulistiyawati Arshad, Muhammad Waqas Asistyasari, Ayuni Chandra, Iryanto Dedi Darwis Gustina, Intan Hafizhah, Hafizhah Handika, Tegar Dio Hari Agung Adrianto Imas Sukaesih Sitanggang KHADAFI, MUHAMMAD Luthfi Falih, Yudep Rafidal Ma'rufudin Mahmudah, Siti Anisa Maria Angelina Luisa Makin Megawaty, Dyah Ayu Nasrul, Royhan niswatun umami, Nila Oprasto, Raditya Rimbawan Palupiningsih, Pritasari Pasaribu, A. Ferico Octaviansyah Putri, Clara Indriani Ryan Randy Suryono Saidina Ali Habib Sanjaya, M. Alung Setiawansyah Setiawansyah Sitna Hajar Hadad Subhan Subhan Suci Fitrianti, Suci Sumanto Sumanto Tri Widodo Ulum, Faruk Wahyudi, Agung Deni Wang, Junhai Yansyah, Dery yasin, ikbal Yosep Nuryaman Yuri Rahmanto