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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 CogITo Smart Journal 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) Jurnal SITECH : Sistem Informasi dan Teknologi Journal of Information Systems and Informatics Jurnal Akuntansi Bisnis 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 Journal of Economics and Business UBS Jurnal AbdiMas Nusa Mandiri Journal of Business and Audit Information System (JBASE) Jurnal Pengabdian dan Kewirausahaan Bulletin of Computer Science Research Konstelasi: Konvergensi Teknologi dan Sistem Informasi Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Algoritma Jurnal Sains dan Teknologi Innovative: Journal Of Social Science Research Nuansa Informatika Jurnal Ragam Pengabdian
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 Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

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Developing a UKM Activity Application for Universities in North Jakarta Using Scrum Kevin Christianto; Francka Sakti Lee; Putu Sita Witari; Johanes Fernandes Andry; Agus Budiyantara
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

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 Mega Henia Br Ginting; Francka Sakti Lee
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

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 Ahya Radiatul Kamila; Johanes Fernandes Andry; Francka Sakti Lee; Felliks F. Tampinongkol
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

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.
The Influence of Corporate Brand Halo and Political News Exposure on Investors' Stock Purchase Intention Surianto Surianto; Very Budyanto; Ahya Radiatul Kamila; Ongky Alex Sander; Francka Sakti Lee
Journal of Economics and Business UBS Vol. 15 No. 5 (2026): Journal of Economics and Business UBS (Issue in Progress)
Publisher : Cv. Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52644/sw6een79

Abstract

Political uncertainty can shape investment decisions, while favorable perceptions of a corporation may influence how investors evaluate stocks amid political news coverage. This study examined the relationships between Corporate Brand Halo, Political News Exposure, and investors’ stock purchase intention toward PT Industri Jamu dan Farmasi Sido Muncul Tbk during the August 2025 demonstrations in Indonesia. Guided by the Heuristic–Systematic Model (HSM), the study employed a quantitative explanatory design involving 200 respondents selected through purposive sampling. Data were collected using an online questionnaire based on a six-point Likert scale and analyzed using partial least squares structural equation modeling (PLS-SEM) in SmartPLS 4 with 5,000 bootstrap resamples. The results showed that Corporate Brand Halo was positively and statistically significantly associated with stock purchase intention (β = 0.700, p < .001), whereas Political News Exposure was not significantly associated with stock purchase intention (β = −0.082, p = .111). The model explained 44.3% of the variance in stock purchase intention. These findings suggest that favorable corporate brand perceptions were more strongly associated with investment interest than exposure to political news within the study sample. The study concludes that corporate brand perceptions are relevant to understanding investors’ stock purchase intentions under conditions of political uncertainty, highlighting the importance of maintaining corporate credibility and consistent stakeholder communication. However, exposure to political news alone should not be interpreted as evidence of systematic information processing or as a direct determinant of stock purchase intention.
Co-Authors Agustina, Agustina Agustinus Frits Wijaya Ahya Radiatul Kamila Ananda, Deah Ananda, Vincent Ray Anatasia, Velly Andrian, Andrian Andrian, Kelvin Andry, Johanes Fernandes Andry, Johanes Fernandes Angellia Onggo, Kallista Angie Wiyani Putri Angie Wiyani Putri Angie Wiyani Putri Anwar, Sahrul Aprilia, Keysia Arron, Rivaltino Arvin, Bryan Aryani, Dini Ayu Azhari, Ozmar Bernadus Gunawan Sudarsono Bernadus Gunawan Sudarsono Bernanda, Devi Yurisca Bili, Wibi Alfari Brainard, Aryo Breliastiti, Ririn Breliastiti, Ririn Buananta, Septian Eka Ady Budiyantara, Agus Byron Harnope Charolina, Yanthi Charolina, Yanthi - Christian Kurniadi Jusuf Christianto, Kevin Christy, Vania Cornelius, Wilson Delly Vera Deny, Deny Derhass, Gerry Hudera Deswin Auliyaa Rabbani Devi Yurisca Bernanda Dinata, David Freggy Dylen, Varel Eko Ariawan EKO WAHYU PRASETYO Endi Putro Fandevi Maitri Felicia, Jennifer Felliks F. Tampinongkol Fenardi, Okky Fernando, Lukas Fernando, William Fidelia Novena Doa Fidelia Novena Doa Geasela, Yemima Monica Geasela, Yemima Monica Gerry Hudera Derhass Giovanni Alvaro Gunawan Sudarsono, Bernadus Hendy Tannady Honni Honni Honni Honni Honni Honni, Honni Honni, Honni Huang, Calvin Ignatius Adrian Mastan Isputrawan, M. Fauzi Johanes Fernandes Andry Johanes Fernandes Andry Johanes Fernandes Andry Jovannia Grisella Eka Putri Jusia Amanda Ginting Kastanya, Lidia Kenji Tjandra Kenvil Lesmana Kevin Christianto Kevin Christianto Kevin Christianto Kevin Christianto Kevin Tanuwidjaya KEZIA, KEZIA Lesmana, Kenvil Liawen, Callista Chrestella Liliana, Lydia Limawal, Isabelle Ivana Lina Noviana Lydia Liliana M. Fauzi Isputrawan Marco Antonio Narahaba Martinez Nicholas Marvelino, Matthew Matthew, Randy Mega Henia Br Ginting Meyliana, Sintia Michael Pranata Monica Clara Monica Geasela, Yemima Mulyo, Jonathan Riady Nababan, Andika Jakaria Nadia Karepowan Natanael Cristo Nelson, Catheryn Iona Neti Amalia Ngurah Suryantara, I Gusti Nisrina, Alaniah Noviana, Lina Nurken, Brian Prasnavira Nurprihatin, Filscha Octaviana, Annabel Onggo, Kallista Angelia Owen, Bryan Paramita Rosadi Piter, Dicsi Purnomo, Yunianto Putra, Rakassiwi Ayudharma Putu Sita Witari Rahman, Muhammad Ryo Reynaldi Ekklesia Rion Comeron Rudi, Ardian Brian Pratama Samuel Winata Samuel Winata Sander, Ongky Alex Santoso, Andi Putra Setiawan, Selly Setyaningsih, Putry Wahyu Shiang Lung Felix Stevanus Stevanus Steven Saputra Steven Steven Steven Steven Steven Winata Sudarsono, Bernandus Gunawan Sulaeman, Asvian Surianto Surianto Suryantara, I Gusti Ngurah Tampinongkol, Felliks F Tanjaya, Verawaty Teady Matius Surya Mulyana Terry, Johanes Theresia, Jennifer Vania Christy Vania Christy Verawaty Verawaty Very Budiyanto Very Budyanto Wandy Wandy Wiedjaya, Handry Wijaya, Hermawan William Darma William Heber Wincent, Wincent Witari, Putu Sita Witari, Putu Sita Yanthi Carolina Yeba Teo Reinhad Gunawan Yeba Teo Reinhad Gunawan Yemima Monica Geasela Yemima Monica Geasela Yunianto Purnomo Yunianto Purnomo Yunianto Purnomo Yusup, Christian Ronaldo