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All Journal International Journal of Advances in Applied Sciences Jurnal Simetris Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi Computatio : Journal of Computer Science and Information Systems Jurnal Informatika Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Teknoinfo INTECOMS: Journal of Information Technology and Computer Science JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Journal of Information Systems and Informatics Jurnal Teknologi Dan Sistem Informasi Bisnis JATI (Jurnal Mahasiswa Teknik Informatika) INFORMASI (Jurnal Informatika dan Sistem Informasi) JIKA (Jurnal Informatika) Infotek : Jurnal Informatika dan Teknologi Infotech: Journal of Technology Information Jurnal AbdiMas Nusa Mandiri Journal of Business and Audit Information System (JBASE) Jurnal Pengabdian dan Kewirausahaan Konstelasi: Konvergensi Teknologi dan Sistem Informasi Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Sains dan Teknologi Nuansa Informatika
Francka Sakti Lee
Universitas Bunda Mulia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering 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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

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Journal : Journal of Information Systems and Informatics

 1 
Risk Analysis of Business Continuity Plan in Light Steel Company Using ISO 31000 Framework Andry, Johanes Fernandes; Christianto, Kevin; Purnomo, Yunianto; Lee, Francka Sakti
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.955

Abstract

Light Steel Company is an industry engaged in manufacturing, has adopted technology and has a data center. The purpose of this study is to provide a guide and strategy for preventing risks and actions to minimize and overcome risks that can be used and implemented, so that the company's business processes can continue to run sustainably. This study uses Business Continuity Plan (BCP) using ISO 31000. Data collection is used by an interviewing employee who works at this organization. The analysis shows there are 15 possible risks that will hinder the operation of Light Steel companies based on the risk level high, medium, and low categories. High risk level is 26.7%, there are 4 possible risks, namely R05 (Loss of spare parts), R06 (Unscheduled maintenance and care for trucks and equipment spare parts), R10 (Server down) and R012 (Network connection problems). Medium risk level is 26.7%, there are 4 possible risks, namely R02 (flood), R07 (Cybercrime), R08 (Hacking), and R011 (Sudden power outage). Finally for low risk level is 46.6%, there are 7 possible risks, namely R01 (Earthquake), R03 (Dust), R04 (Fire), R09 (Abuse of access rights), R13 (Overheat), R14 (Data Corrupt), and R15 (Virus Attack, Malware).
Developing a UKM Activity Application for Universities in North Jakarta Using Scrum Christianto, Kevin; Lee, Francka Sakti; Witari, Putu Sita; Andry, Johanes Fernandes; Budiyantara, Agus
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.956

Abstract

Student Activity Units (UKM) plays an important role in supporting the development of student skills outside of academic activities. However, the management of UKM activities often faces obstacles in communication, administration, and membership management. This study aims to develop a UKM Activity Application designed to improve the operational efficiency of UKMs at Universities in North Jakarta. This application is equipped with key features such as member registration, activity management, attendance, and transparency of financial administration. The development was carried out using the Scrum method, which involves an iterative process starting from user needs analysis, product backlog preparation, to feature development in sprints. Daily stand-up meetings are held to monitor progress, and sprint reviews are used for evaluation and adjustment. The final result of this study is an application that is able to improve the efficiency of UKM activity management, strengthen communication between members, and increase student involvement in campus activities. This application is expected to be a modern digital solution to facilitate the management of UKMs in the university environment.
Design and Implementation of a Stock Purchase System for Printing Businesses Using the Waterfall Method Ginting, Mega Henia Br; Lee, Francka Sakti
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1057

Abstract

Efficient stock availability is essential for the seamless operation of business processes within a company. However, stock management often encounters several critical challenges, including discrepancies between warehouse inventory and logbook records, as well as mismatches between ordered and received quantities. These issues frequently lead to overstocking or stockouts overstocking increases operational costs and risks quality degradation or expiration of goods, while stockouts disrupt sales and customer service. To address these challenges, this study proposes the design of a stock purchasing management application aimed at optimizing inventory tracking and enhancing operational efficiency within a printing shop. The system is developed using the Waterfall methodology, a structured software development model that helps minimize errors throughout the design process. To validate the system's functionality, black box testing is employed, ensuring that the application performs as intended. The resulting application offers an effective solution to stock management issues, reducing inventory imbalances and supporting more efficient business operations.
Integration of Hash Encoding Technique with Machine Learning for Employee Turnover Prediction Kamila, Ahya Radiatul; Andry, Johanes Fernandes; Lee, Francka Sakti; Tampinongkol, Felliks F.
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1129

Abstract

Employee turnover refers to the replacement of employees within an organization, which can lead to losses such as recruitment costs and decreased productivity. Predicting turnover is crucial for companies to anticipate and take appropriate actions to retain potential employees. This study aims to optimize the employee turnover prediction model by integrating hash encoding techniques and machine learning. The dataset used in this study is an open-source dataset obtained from Kaggle dataset. It consists of 14,994 rows and 10 columns (features) representing employee-related information such as satisfaction level, evaluation score, number of projects, average monthly hours, and whether the employee left the company. Among these features, some are of object data type. Since machine learning algorithms generally cannot work directly with object-type features, the use of hash encoding is proposed. This technique converts object-type data into numerical data. It is part of the preprocessing stage, aiming to reduce memory usage, speed up data preprocessing, and improve model performance. After preprocessing is completed, the prediction model is trained using the Random Forest algorithm to predict employee turnover. The evaluation is conducted using accuracy, recall, precision, and F1-score metrics, which yielded results of 0.988, 0.961, 0.988, and 0.974, respectively. These results indicate that the integration of hash encoding techniques and machine learning can produce a well-performing model for predicting employee turnover.
Co-Authors ., Ozmar Agustina, Agustina Alvaro, Giovanni Ananda, Vincent Ray Andrian, Andrian Andrian, Kelvin Andry, Johanes Fernandes Anwar, Sahrul Aprilia, Keysia Arron, Rivaltino Arvin, Bryan Aryani, Dini Ayu Azhari, Ozmar Bernadus Gunawan Sudarsono Bernanda, Devi Yurisca Brainard, Aryo Breliastiti, Ririn Budiyantara, Agus Charolina, Yanthi Charolina, Yanthi - Christianto, Kevin Cornelius, Wilson Delly Vera Deny, Deny Derhass, Gerry Hudera Dinata, David Freggy Dylen, Varel Eko Ariawan Endi Putro Felicia, Jennifer Fenardi, Okky Fernando, Lukas Fernando, William Geasela, Yemima Monica Geasela, Yemima Monica Ginting, Jusia Amanda Ginting, Mega Henia Br Heber, William Hendy Tannady Honni Honni Honni, Honni Honni, Honni Huang, Calvin Ignatius Adrian Mastan Isputrawan, M Fauzi Isputrawan, M. Fauzi Johanes Fernandes Andry Kamila, Ahya Radiatul Kevin Christianto KEZIA, KEZIA Lesmana, Kenvil Limawal, Isabelle Ivana Marco Antonio Narahaba Marvelino, Matthew Matthew, Randy Meyliana, Sintia Michael Pranata Monica Clara Mulyo, Jonathan Riady Nababan, Andika Jakaria Nadia Karepowan Nurken, Brian Prasnavira Nurprihatin, Filscha Onggo, Kallista Angelia Owen, Bryan Paramita Rosadi Piter, Dicsi Purnomo, Yunianto Putra, Rakassiwi Ayudharma Rabbani, Deswin Auliyaa Rahman, Muhammad Ryo Reynaldi Ekklesia Rudi, Ardian Brian Pratama Samuel Winata Santoso, Andi Putra Setiawan, Selly Shiang Lung Felix Stevanus Stevanus Steven Steven Sudarsono, Bernandus Gunawan Sulaeman, Asvian Suryantara, I Gusti Ngurah Tampinongkol, Felliks F Tampinongkol, Felliks F. Tannady, Hendy Teady Matius Surya Mulyana, Teady Matius Verawaty Verawaty Wandy Wandy Wiedjaya, Handry Wijaya, Agustinus Frits Wijaya, Hermawan William Darma Wincent, Wincent Witari, Putu Sita Witari, Putu Sita Yusup, Christian Ronaldo