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All Journal Jurnal Ilmu Komputer dan Informasi JIKSI (Jurnal Ilmu Komputer dan Sistem Informasi) Computatio : Journal of Computer Science and Information Systems JURNAL INTEGRASI Seminar Nasional Teknologi Informasi Komunikasi dan Industri JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Sebatik INTECOMS: Journal of Information Technology and Computer Science Jurnal ULTIMATICS Journal on Education Simtek : Jurnal Sistem Informasi dan Teknik Komputer Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Journal of Information Systems and Informatics Journal of Intelligent Decision Support System (IDSS) Jurnal Bakti Masyarakat Indonesia Jurnal Teknik Informatika (JUTIF) Internet of Things and Artificial Intelligence Journal
Tony Tony
Fakultas Teknologi Informasi Universitas Tarumanagara
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics Social Sciences Other

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DESAIN APLIKASI PRESENSI ONLINE BERBASIS WEB PADA PT PASSWORD SOLUSI SISTEM Leon Fernando Wijaya; Tony
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 13 No. 1 (2025): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v13i1.32902

Abstract

Attendance and overtime are two crucial aspects of human resource management. This study takes PT Password Solusi Sistem, an IT solutions provider and systems integrator, as a case study. Currently, the company uses an online attendance application from an external service provider, but it faces challenges such as inefficient overtime calculations and limited feature customization. This research aims to design a web-based online attendance application that includes additional features not available in the current system. The development follows the Scrum methodology, beginning with user requirements gathered through interviews and progressing through the implementation of each application module. The resulting system design includes three user roles: Infrastructure Staff, Infrastructure Manager, and Human Resources Manager. Infrastructure Staff handle check-in and check-out attendance as well as manual overtime submissions, while the Infrastructure and Human Resources Managers have authority over user management, export of attendance and overtime data, shifts, and company holidays. Additionally, this study produces an interactive and user-friendly interface design.
PERANCANGAN WEBSITE PENDAFTARAN PESERTA DIDIK BARU PADA SMA KRISTEN YUSUF Catherine; Tony
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 13 No. 1 (2025): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v13i1.32904

Abstract

Nowadays, in the digital era, SMA Kristen Yusuf faces challenges in the registration process of new students which is still done manually via telephone, WhatsApp, and direct visits to the school, which hampers the efficiency and accuracy of data. This research aims to design and implement a website-based new student registration system that can simplify the online registration process and improve the efficiency of data management at school. The design of the user interface is done using Figma software, which allows better visualisation and responsiveness to make it easier for users to access the system. Using the Agile method, this system is built with Next.js framework for user interface, MySQL for database management, and Golang for backend data management. The results show that this online registration system makes it easier for parents to register their children and helps the school in managing new student data more efficiently and accurately, as well as increasing the school's visibility in cyberspace, making it easier for prospective students to access.
PERANCANGAN SISTEM & USER INTERFACE UNTUK APLIKASI KASIR DAN INVENTARIS PADA BENGKEL BARU MOTOR SPORT Rafael Wun; Tony
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 13 No. 1 (2025): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v13i1.32911

Abstract

An easy-to-use and efficient interface is essential for cashiering and inventory management systems, especially in motorcycle workshops that have unique requirements for tracking goods and processing sales transactions. This research focuses on designing a web-based application interface to streamline sales transactions and inventory management at the Baru Motor Sport workshop. The User Interface (UI) simplifies core processes, including recording incoming and outgoing goods, managing inventory, and processing sales transactions in real-time. Vue.js is used to create a responsive and intuitive front-end, supported by Tailwind CSS for a modern design. The design process followed the Scrum methodology, which emphasizes iterative feedback, flexibility, and continuous improvement to align the UI with user needs. The interface accommodates three main roles: Admin, Inventory Staff, and Cashier Staff. Each role's UI is customized to facilitate user-specific tasks, such as inventory tracking for Inventory Staff and transaction handling for Cashier Staff, while Admin oversees user management and views sales reports. This UI design aims to improve operational efficiency, enhance usability, and support accurate and efficient workflows in the workshop.
PERANCANGAN APLIKASI E-COMMERCE DAN PENGELOLAAN DATA INVENTORI BERBASIS WEB PADA DAYA RAGA TEKNINDO Albertus Ferdinand Pratono; Tony
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 13 No. 1 (2025): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v13i1.32921

Abstract

Daya Raga Teknindo is a company engaged in the production of stainless steel wire clothes hangers, seeking to increase sales and maintain consistent production data. Currently, recording of production activities is still done manually using paper and Microsoft Excel, which risks resulting in inconsistencies and loss of data. To overcome these challenges, the company plans to develop a web-based application that includes several key features. The company profile feature is designed as a marketing tool so that people can get to know the company better, while the e-commerce feature aims to make it easier for customers to buy products online. Apart from that, this application will provide an admin dashboard as a means of consistently managing inventory data and production activities. With this application, it is hoped that Daya Raga Teknindo can increase sales, manage data better and make more effective business decisions.
Dashboard untuk Memantau Kinerja Penjualan di Klinik Gustavet Maulana, Aldi Resaldi; Tony, Tony
Computatio : Journal of Computer Science and Information Systems Vol. 8 No. 2 (2024): Computatio: Journal of Computer Science and Information Systems
Publisher : Faculty of Information Technology, Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/computatio.v8i2.27111

Abstract

Gustavet Clinic is an animal acupuncture service that was specifically established in 1999 by Dr. Gustav. In 2006, Gustavet shifted its focus to holistic services, particularly animal acupuncture, under the guidance of Dr. Gustav, who personally studied acupuncture techniques from human acupuncture and established an acupuncture association in Indonesia along with his teachings. In 2012, Gustavet expanded into a veterinary and acupuncture clinic. The aim of this final project is to create an interactive dashboard using Tableau software, employing prototyping methods, to monitor sales at Gustavet Clinic. Data is extracted from sales records within the Kreloses inventory application, available at Gustavet Clinic, for the years 2021, 2022, and 2023. This dashboard provides an easy way to view information about pet food and veterinary drug sales. Through intuitive graphs and charts, users can quickly access information on total sales, profits, best-selling products, and year-over-year sales comparisons. The dashboard is designed to assist Gustavet Clinic in making better decisions to enhance sales performance and services for pet owners.
DENTAL CARIES SEVERITY DETECTION WITH A COMBINATION OF INTRAORAL IMAGES AND BITEWING RADIOGRAPHS Jennifer Jennifer; Winni Setiawati; Gabriella Adeline Halim; Tony Tony
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 3 (2025): JITK Issue February 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i3.6042

Abstract

Dental caries is a multifactorial oral disease caused by plaque due to bacterial sugar fermentation. Quite a number of dentists have misdiagnosed caries due to the subjective nature of visual examination and radiograph in early-stage lesions. Thus, research on the implementation of deep learning technology is expected to improve the accuracy of diagnosis. However, caries detection with deep learning has accuracy problems. This problem makes researchers interested in developing a deep learning method that combines Faster R-CNN algorithm and texture feature extraction to more accurately detect carious teeth from bitewing radiography datasets and intraoral images. The overall performance of the model to detect the radiographic class was slightly better than the intraoral class. Overall, the classification accuracy of the model was 88.95% which is better than previous research that only used one or the other type of images. GLCM (Gray-Level Co-Occurrence Matrix) is effective in detecting contrast areas, but it still cannot specifically distinguish normal anatomical contrast from caries. The Faster R-CNN model learned well and was able to differentiate between each caries type and was successfully integrated with the GLCM matrix for radiographic image pre-processing to facilitate caries detection. This approach could have the potential of assisting dental professionals in reducing diagnostic errors and increasing patient care.
CLASSIFICATION OF NATURAL DISASTERS IN WEST SEMARANG BASED ON WEATHER DATA USING DEEP LEARNING Nicholas Martin; Jason Permana; Tony Tony
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 4 (2025): JITK Issue May 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i4.6147

Abstract

Natural disasters like floods, landslides, and fires pose serious threats to both life and mental well-being, especially in vulnerable areas like West Semarang, which frequently experiences extreme weather. To mitigate these risks, an accurate classification system is essential for timely prevention and response. This study compares the performance of three neural network models—Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU)—in classifying natural disasters using weather data. LSTM and GRU are particularly effective for handling long-term dependencies and addressing vanishing gradient problems common in time series data. Data for the study comes from the Semarang City Regional Disaster Management Agency (BPBD) and the Meteorology, Climatology, and Geophysics Agency (BMKG), spanning 2019 to 2022. The models achieved a high accuracy of 95.8%, but this is due to an imbalanced dataset—70 records of natural disasters versus 1377 without—resulting in classification favoring "no disaster." Among the models, LSTM performed the best, reaching optimal accuracy in just 20.0671 seconds per epoch. This suggests LSTM is the most effective model for this classification task.
Forecasting Indonesian Banking Stock Prices Using Prophet, XGBoost, and Ridge Regression: A Comparative Analysis Tony, Tony; Ratchagit, Manlika; Hiryanto, Lely
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.4973

Abstract

This study investigates the efficacy of Prophet, XGBoost, and Ridge Regression in forecasting stock prices of four major Indonesian banks—Bank Central Asia (BBCA.JK), Bank Negara Indonesia (BBNI.JK), Bank Rakyat Indonesia (BBRI.JK), and Bank Mandiri (BMRI.JK)—using daily historical data from January 2020 to March 2025, sourced from Yahoo Finance. The banking sector's volatility, evidenced by year-to-date declines ranging from 7.59% (BBCA) to 22.69% (BMRI) as of May 1, 2025, underscores the need for accurate predictive models. Performance was evaluated using Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), revealing Ridge Regression as the superior method, consistently achieving the lowest errors (i.e., MAE of 23.81 for BBNI.JK and RMSE of 55.75 for BBCA.JK). Prophet exhibited the highest errors, suggesting its seasonal focus is less suited to stock price unpredictability, while XGBoost performed moderately better but lagged behind Ridge Regression. The results highlight Ridge Regression’s effectiveness in handling multicollinearity and noise in financial data. Our discussions emphasize the importance of model selection based on data characteristics, with implications for investment decision-making in the Indonesian market. This research contributes to the field of computational finance by providing a comparative analysis that not only identifies Ridge Regression as a superior method for forecasting stock prices but also illuminates the limitations of popular models like Prophet and XGBoost in handling financial data's unique characteristics, guiding future model selection and development. Future research could explore hybrid models to enhance accuracy across varied market conditions, addressing the study’s 60-day forecasting horizon limitation.
Co-Authors Adhi, Dennis Kurniawan Adrian Hartanto Adrian Santoso Agus Budi Dharmawan Agus Budi Dharmawan Agus Hendrah Roni Ailsa Bella Albertus Ferdinand Pratono Angelica Christina Angeline Alviona Meilyta Anthony Gunawan Ardi Sugiarto Bernard Dean Sofli Bezaliel Rumengan Bobby Tumbelaka Budianto Lomewa Lo Catherine Chairisni Lubis Christina, Angelica Clive Riady Cynthia Marcelina Darius Andana Haris Dayanti, Afina Putri Dedi Trisnawarman Dennis Kurniawan Adhi Desi Arisandi Destini, Janessa Sarah Diana Tanu Wijaya Dyah Erny Herwindiati Edward Brainard Pranata Eric Anthony Erikson T Ferdyan Tarigan Filipus Hanung Nugroho Foris Julio Suyanto Francisca Francisca Frans Lienardi Fransiska Luminovita Freddy Kurniawan Frencent Kinselton Gabriella Adeline Halim Garry Wiratama Geoffrey Valhart Harioyno Gosal, Maria Rosa Handy Lesmana Hendri Yukianto Henry Felix Hartanto Ignatius Lorenzo indrafani J. Panjaitan Ivan Sutedjo Janessa Sarah Destini Jason Permana Jennifer Jennifer Jensen Wang Jimmy wijaya Joel Eko Budianto Joko Joko Juan Gilland Djoni Kelvin Kennedy Stefano Kenny Yan Kevin Andryani Kristina Kristina Kusumoputro Kusumoputro Lely Hiryanto Leo Fantony Leon Fernando Wijaya Liko Dylan Manatap Dolok Lauro Manatap Dolok Lauro, Manatap Dolok Marcel Alexandro Rumbang Mardian Puli Sandy Maria Rosa Gosal Maulana, Aldi Resaldi Mega Pertiwi Meilita Chintya Melani Asta Rosari Meyliani Tanjung Michael Antoni Monica Saputra Natasha Angelica Nicholas Martin Novario Jaya Perdana Pranata, Edward Brainard Rachel Andrea Christy Raditya Rizki Ilhamsyah Raditya Rizki Ilhamsyah Rafael Wun Ratchagit, Manlika Rebecca Santi Rei Malchiel Reinhoran Reinhoran Resnu Rifnaldy Riady, Clive Riwinoto Riwinoto Roberto Davin Ruach Sakadewa Salsabila Azhary Firdaus Sandy Tanudjaja Shela sherly sherly Sidik Mulyono Sindy Sindy Stephen Christian tania evrita Teny Handhayani Thomas Andreas Tisa Sudargo TRI SUTRISNO Valencia Ilona Vera Felia Via Angelika Vikaliendry Nathayana Viny Christanti M Wahyudi Wahyudi Wasino Wasino Wasino Wijaya, Leon Fernando Windah Maria Sonia Nadiah Hutagalung Winni Setiawati Zyad Rusdi