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Aji Setiawan
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Faculty of Engineering, Darma Persada University. Terusan Casablanca Streets, Pondok Kelapa, East Jakarta, Indonesia.
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Journal Technology Information and Data Analytic
Published by Universitas Darma Persada
ISSN : -     EISSN : 30640660     DOI : https://doi.org/10.70491/tifda.v1i2.43
Core Subject : Science, Education, Agriculture, Engineering,
Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Engineering Library & Information Science Other
Journal of Technology Information and Data Analytic is a scientific journal managed by the Faculty of Engineering, Darma Persada University. TIFDA is an open access journal that provides free access to the full text of all published articles without charging access fees from readers or their institutions. Readers are entitled to read, download, copy, distribute, print, search, or link to the full text of all articles in the TIFDA Journal. This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge. Focus & Scope Informatics: Software Engineering, Information Technology, Information System, Data Mining, Multimedia, Mobile Programming, Artificial Intelligence, Computer Graphic, Computer Vision, Augmented/Virtual Reality, Games Programming, Privacy and Data Security, Security, Machine learning, Database Internet of Things Information System : Software Management, Life Cycle Development Tools.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 24 Documents
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Search results for , issue "Vol 2 No 1 (2025)" : 24 Documents clear
P Perancangan Sistem Absensi Digital dan Monitoring Kehadiran dan Lembur di PT. TRIKARSA BAHTERA ABADI Darmawan, Dimas Bagus; Septiadi, Robby; Saputra, Rendy Wijaya; Haryono, Wasis
Journal TIFDA (Technology Information and Data Analytic) Vol 2 No 1 (2025): Journal Technology Information and Data Analytic (TIFDA)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v2i1.87

Abstract

Manual attendance systems that are still used in many construction companies often face obstacles such as data manipulation, late recapitulation, and the absence of real-time worker location validation. This study aims to design and implement a web-based digital attendance system with GPS validation and photo documentation to improve the efficiency and accuracy of recording project worker attendance and overtime. The system was developed using the Waterfall approach which includes needs analysis, system design, code implementation, testing, and maintenance. The implementation results show that the system can record attendance and overtime accurately, and facilitate monitoring by project admins through an interactive dashboard. The system also provides separate user roles such as admin, finance, SEM, owner, and workers, each of which has access to relevant features. With this system, the process of monitoring and decision-making related to attendance management becomes faster, more transparent, and more integrated.
Deteksi Serangan Brute Force SSH Menggunakan Klasifikasi Naïve Bayes pada Log Cowrie Honeypot di Lingkungan Virtual Prasetyo, Arya Adhari; Herianto; Yahya; Syamsiyah, Nur
Journal TIFDA (Technology Information and Data Analytic) Vol 2 No 1 (2025): Journal Technology Information and Data Analytic (TIFDA)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v2i1.88

Abstract

The increasing number of brute force cyberattacks targeting SSH services highlights the urgent need for effective early detection and mitigation systems. This study aims to analyze brute force attack patterns using the Naïve Bayes classification algorithm based on log data generated by the Cowrie Honeypot. A simulated virtual environment was developed to emulate attack scenarios and generate authentic SSH log data while preserving real server confidentiality. The system architecture follows the CRISP-DM framework, including data preprocessing, model development, evaluation, and deployment. Evaluation using confusion matrix metrics showed that the Naïve Bayes algorithm successfully distinguished brute force attempts from normal traffic with high accuracy, precision, recall, and F1-score. The findings confirm the potential of combining Cowrie honeypot data with machine learning classifiers as an early warning tool for intrusion detection in enterprise network infrastructures.
Pengembangan Teknologi Internet Of Things Pendeteksi Kebakaran untuk Ruang Server dilengkapi Pemantauan Real-Time dan Notifikasi Whatsapp Serta Monitoring menggunakan Grafana Muhammad Rizkhi; Suzuki Syofian
Journal TIFDA (Technology Information and Data Analytic) Vol 2 No 1 (2025)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v1i2.43

Abstract

Fire is a serious threat that can cause physical, economic, and loss of life. Often triggered by human factors, nature, or equipment such as electricity and LPG, fires require rapid detection and response. Internet of Things (IoT) technology provides solutions with smart sensors that monitor the environment in real-time to detect temperature, smoke, or hazardous gases. This study develops an IoT-based fire detection system for server rooms that integrates fire sensors, MQ-2 smoke sensors, DHT-11 temperature sensors, CCTV for visual monitoring, and notification via WhatsApp. The Grafana monitoring platform is used for sensor data visualization. The case study was conducted at PT Askara Internal, with the aim of improving server room security and reducing fire risks, as well as increasing operational resilience through innovative and effective technology.
Implementasi Data Mining Untuk Mendukung Program Reduksi Sampah di Daerah Khusus Jakarta Dengan Menggunkan Algoritma Time Series dan K-Means Clustering Muhammmad Krisna Adiputro; Afri Yudha
Journal TIFDA (Technology Information and Data Analytic) Vol 2 No 1 (2025)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v2i1.74

Abstract

This study aims to analyze the trend of waste growth in Jakarta using the ARIMA method and to group areas based on waste volume using the K-Means Clustering algorithm. The waste accumulation problem at the Bantargebang TPST continues to worsen each year, with increasing volumes from various sub-districts. Data used in this study were obtained from the DKI Jakarta Environmental Agency, covering the period from January 2022 to April 2024, focusing on organic waste, plastic, and household hazardous waste (B3). The research applies the CRISP-DM methodology, consisting of business understanding, data understanding, data preparation, modeling, evaluation, and implementation. Data processing includes cleaning, normalization, and splitting into training and testing sets. The analysis results show that the ARIMA model achieves good forecasting accuracy, with MAPE, MAE, and RMSE values around 3652. The K-Means algorithm successfully classifies Jakarta areas into three main clusters dominated by organic, plastic, and mixed waste types. A web-based system was developed using Streamlit and MongoDB Atlas to facilitate data analysis and visualization for policymakers, especially the Environmental Agency. The study concludes that ARIMA is effective in forecasting waste growth, while K-Means supports more targeted waste management strategies. It is recommended to enhance the system by incorporating external variables such as policy changes and socio-economic factors, and to improve model accuracy using more advanced machine learning techniques. Additionally, the system should be continuously updated and expanded to support more optimal and sustainable waste management across Jakarta.
Comparative Analysis of Naïve Bayes and SVM Algorithms for Early Detection of Lung Disease at Cimuning Community Health Center Jordi Hafidz; Aji Setiawan
Journal TIFDA (Technology Information and Data Analytic) Vol 2 No 1 (2025)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v2i1.75

Abstract

Comparative Analysis of Naïve Bayes and SVM Algorithms for Early Detection of Lung Disease at Cimuning Community Health Center
Steganography on MP3 Audio files to secure messages using the Least Significant Bit (LSB) and Advanced Encryption Standard (AES) methods Steven Blanco; Adam Arif Budiman
Journal TIFDA (Technology Information and Data Analytic) Vol 2 No 1 (2025)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v2i1.80

Abstract

The E-budgeting file code delivery system is one of the right choices for a company to send and store large amounts of data neatly and properly. Currently, Bank XYZ has not yet implemented an Android-based file delivery and storage system, resulting in difficulties in locating previously sent files. To address this issue, Bank XYZ has developed an E-budgeting file code delivery system. This system is Android-based and operates using Android smartphones online. It is also designed to securely store files using AES (Advanced Encryption Standard) encryption and LSB (Least Significant Bit) steganography methods. The purpose of the E-budgeting file code delivery system is to facilitate the secure transmission of these codes to the relevant parties
Perancangan Aplikasi Absensi dan Pengawasan Ruangan dengan Pengenalan Wajah menggunakan metode Convolutional Neural Network Rizki Nurpadilah; Timor Setiyaningsih
Journal TIFDA (Technology Information and Data Analytic) Vol 2 No 1 (2025)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v2i1.81

Abstract

The development of technology in the field of facial recognition provides a great opportunity to improve efficiency and security in various aspects, one of which is the attendance and room surveillance system. This study aims to design an attendance and room surveillance application based on facial recognition using the Convolutional Neural Network (CNN) method in a private company engaged in the property sector. This application is designed to simplify the employee attendance process and improve room surveillance by automatically recognizing employee faces, thereby reducing the risk of attendance fraud and ensuring more accurate attendance. The CNN method was chosen because of its ability to process images and recognize facial patterns with high accuracy. This system consists of several main features, namely employee face registration, automatic face-based attendance, and monitoring employee presence in the office space. The test results show that this application is able to identify faces with a good level of accuracy, as well as provide convenience and comfort for users.
Perbandingan Algoritma Decision Tree dan K-Means Clustering Untuk Menentukan Penghargaan Terhadap Loyaltas Customer Bagus Tri Mahardika; Donnie Varyasetya Prastowo
Journal TIFDA (Technology Information and Data Analytic) Vol 2 No 1 (2025)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v2i1.82

Abstract

PT Tangguh Buana Roda Indonesia has difficulty in retaining loyal customers due to less than optimal customer management. This research proposes the use of a data mining-based system to categorize loyal customers using the K-Means and Decision Tree methods. The evaluation shows that the combination of K-Means and Decision Tree algorithms provides a higher average accuracy of 93.7175%. Compared to using Decision Tree alone which reached 92.8525% and K-Means which was only 91.667%. With the combination of these two algorithms, it is expected to support the awarding of loyal customers and strengthen the relationship between customers and companies. The system that has been created is web-based which will facilitate strategic planning to increase customer loyalty.
Pengembangan Sistem Informasi Lowongan Kerja di Career Center Universitas Darma Persada Yahya Yahya; Endang Ayu Susilawati; Eva Novianti; Rahmadanti
Journal TIFDA (Technology Information and Data Analytic) Vol 2 No 1 (2025)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v2i1.83

Abstract

Career centers play a vital role in bridging the gap between higher education and the workforce by helping students and alumni access job opportunities and develop relevant skills. At Universitas Darma Persada, the career center faced challenges in disseminating job vacancy information efficiently due to time constraints and limited distribution methods, primarily via Instagram. This study aims to design and develop a web-based job vacancy information system to improve accessibility and communication between job seekers and employers.The uniqueness of this research lies in the development of a role-based job portal system that integrates multiple user roles, namely job seekers (students and alumni), career staff, and employers, into a single digital platform. The objective is to accelerate job vacancy publication, facilitate job applications, and streamline employer access to candidate data.This study adopts the Waterfall methodology, including stages of requirement analysis, system design, implementation, and testing. Data were collected through observation, interviews, and literature review. The final system was developed using Visual Studio Code, PHP, MySQL, and other web development tools.The results show that the system successfully reduces delays in job vacancy announcements, expands reach beyond Instagram, and provides a more structured and interactive recruitment process. Employers can post jobs and review CVs, while job seekers can apply directly and track their application status. The system has proven effective in enhancing the career center’s role in graduate employability support.
Pengembangan Sistem Informasi Penyewaan Billboard di PT Tecma Mitratama Advertindo Endang Ayu Susilawati; Eva Novianti; Sultan Satrio Ichsan
Journal TIFDA (Technology Information and Data Analytic) Vol 2 No 1 (2025)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v2i1.84

Abstract

The billboard rental process at PT Tecma Mitratama Advertindo currently encounters issues, particularly in calculating rental prices for periods outside the predefined options of one, three, six, and twelve months. When customers request rental durations beyond these standard periods, prices must be calculated manually using a calculator, resulting in delays in issuing rental offer letters. This study aims to develop a billboard rental information system integrated with the marketing division's workflow. The system is expected to streamline the rental process and enable real-time monitoring of billboard rental status. The system development process includes requirements analysis, system design, and web-based interface implementation. The results indicate that the developed system can reduce reliance on manual processes and enhance the efficiency of the marketing division’s operations.

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