Article Per Year (5 Year)
p-Index From 2020 - 2025
3.037
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah KOMPUTASI JRSI (Jurnal Rekayasa Sistem dan Industri) SEIKO : Journal of Management & Business Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Indonesia : Manajemen Informatika dan Komunikasi Journal La Multiapp Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Jurnal Indonesia Sosial Sains eProceedings of Engineering Eduvest - Journal of Universal Studies Informatics Management, Engineering and Information System Journal Jurnal Indonesia : Manajemen Informatika dan Komunikasi The Indonesian Journal of Computer Science
Nur Ichsan Utama
Universitas Telkom
Religion Aerospace Engineering Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Neuroscience Nursing Physics Public Health Social Sciences Other

Published : 22 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Journal La Multiapp

 1 
Backend Development of a Microservice-Based Website Application for Public Issue Reporting: Case Studyn in People Representative Council Isnaeni, Rizqullah Maziyah; Utama, Nur Ichsan; Suakanto, Sinung
Journal La Multiapp Vol. 5 No. 2 (2024): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v5i2.1148

Abstract

This research introduces a web application aimed at advancing public issue reporting, promoting civic engagement, and expediting government responses. In collaboration with DPRD Jawa Barat, the research leverages Scrum methodology, social network features, and a microservice architecture to create an efficient communication platform between citizens and governmental bodies. The backend of the application, developed using the Go programming language, adopts a microservice architecture to enhance scalability and maintainability. The Scrum methodology facilitates an agile development process, ensuring adaptability to changing requirements and fostering continuous improvement throughout the project lifecycle. Additionally, the study explores the incorporation of social network features to encourage public engagement within the application. This integration allows citizens to connect, share, and discuss public issues, further enhancing the collaborative nature of the reporting platform. To ensure the seamless functionality of the microservices, API testing is employed, validating the reliability and consistency of the application's interfaces. Stress testing is also conducted to assess scalability and performance capabilities, identifying potential optimizations for the system's responsiveness under varying levels of load. In conclusion, this research presents an innovative solution for public issue reporting that combines microservice architecture, Scrum methodology, and social network features. The application's integration of these elements aims to not only streamline citizen-government communication but also create a dynamic platform that encourages active public involvement and collaboration.
Implementation of Machine Learning-Based Classification Model in Employee Recruitment Decision Prediction Adillah, Muhammad Fauzan Nur; Suakanto, Sinung; Utama, Nur Ichsan
Journal La Multiapp Vol. 6 No. 2 (2025): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v6i2.2050

Abstract

Employees are vital assets for any organization, and accurate recruitment decision-making is crucial for the organization's long-term success. Incorrect decisions can lead to high costs due to re-hiring processes, onboarding, and decreased productivity. This study aims to develop a recruitment decision prediction model using data obtained from the Final Results of the 2024 CPNS Recruitment in the Ministry of Finance. The data includes attributes such as educational background, age, GPA, SKD Score, and SKB Score. To understand the relationships between variables, correlation analysis was conducted using a correlation matrix and heatmap visualization. Additionally, data exploration was performed using histograms to show the influence of attributes on recruitment decisions. This study employs five machine learning algorithms for prediction: Linear Support Vector Machine, Decision Tree (C5.0), Random Forest, k-Nearest Neighbor (k-NN), and Naïve Bayes Classifier. The results indicate that some attributes significantly influence recruitment decisions, and machine learning models can identify candidates who are more suitable for the available positions. Among the five models tested, Naïve Bayes proved to be the most effective, achieving an accuracy of 88% and an AUC of 0.97, demonstrating its strong performance in distinguishing positive and negative classes. The key factors contributing to the model's success include relevant feature selection, data quality, as well as appropriate preprocessing and validation techniques. This model is expected to enhance objectivity, efficiency, and accuracy in employee recruitment processes, thereby assisting organizations in making more precise and fair decisions.
Co-Authors Adillah, Muhammad Fauzan Nur Ahnaf , Farhan Bani Al Ansary, Faishal Mufied Al Fatwa, Rizki Aprilita Firsty Hazdia Asyam , Muhammad Rizq Dzaki Bagaskara, Kumara Ris Panji Dian Novitasari Puspitaningrum Ekky Novriza Alam Fa'rifah, Riska Yanu Faishal Mufied Al Anshary Himawan, Naufal Aqil Ilham Perdana Isnaeni, Rizqullah Maziyah Lailatuth Thohiroh, Elvira Muhammad Abizard Al Thareq Muharman Lubis Mustada, Fitrina Annisa Naufal Aqil Himawan Nur Adillah, Muhammad Fauzan Oktariani Nurul Pratiwi Puspitaningrum, Dian Novitasari Raharjo, Adi Raina, Apriani Nur Ridwan, Abdullah Rio Aurachman Riverinda Rijadi, Safara Cathasa Sapna, Sitti Munawwarah Sinung Suakanto Siregar , Anggiat Pandu Daniel Tien Fabrianti Kusumasari