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Imam Rangga Bakti
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INDONESIA
Jurnal Serumpun Teknik Informatika
Published by Yayasan Ibrahim Learning Centre Agam
ISSN : -     EISSN : 3123965X     DOI : https://doi.org/10.66485/jsti.v1i2
Core Subject : Science,
Computer Science & IT
Jurnal Serumpun Teknik Informatika (JSTI) is intended as a medium for scientific studies of research, thoughts, and critical analyses on computer science and technology research. As part of the spirit to disseminate scientific knowledge derived from research and thought for community service and as a reference source for academics in the field of Computer Science and Technology. Jurnal Serumpun Teknik Informatika (JSTI) is an international peer-reviewed journal dedicated to advancing the field of Informatics. Published by the Yayasan Ibrahim Learning Centre Agam, Indonesia, Jurnal Serumpun Teknik Informatika (JSTI) provides a platform for researchers, scientists, and academics worldwide to publish their research findings and share their knowledge with the broader scientific community.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 1 No. 2 (2026): April 2026" : 5 Documents clear
Implementation of Two-Factor Authentication (2FA) Using a REST API-Based WhatsApp Gateway to Prevent Fake Bidders on an Online Auction Platform Rizky Parlika; Hamdi Indra; Tegar Satria Kirana
Jurnal Serumpun Teknik Informatika Vol. 1 No. 2 (2026): April 2026
Publisher : Yayasan Ibrahim Learning Centre Agam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66485/jsti.v1i2.19

Abstract

Account security and identity validity are crucial aspects of online auction platforms to prevent price manipulation by fake bidders. Conventional authentication methods are often vulnerable to cyber-attacks or compromise user convenience for the sake of security. This study aims to implement a Two-Factor Authentication (2FA) system on the Mokasindo auction platform using WhatsApp Gateway integrated via REST API technology. The development method includes Webhook mechanisms for real-time user phone number validation and AJAX Short Polling techniques to deliver auto-login features without page refreshing. Black Box testing results indicate that the system successfully verifies user identity accurately and mitigates the risk of fictitious account registration. This implementation offers an optimal balance between system security and User Experience (UX), with an average recorded verification process latency of only 3.5 seconds. This solution proves effective in creating a more secure, responsive, and trustworthy auction ecosystem for users.
Comparative Analysis of Performance and Security Static and Dynamic JSON Web Token (JWT) Rizky Parlika; Muhammad Romi Nasution; Dino Rosanilo Yuswanto
Jurnal Serumpun Teknik Informatika Vol. 1 No. 2 (2026): April 2026
Publisher : Yayasan Ibrahim Learning Centre Agam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66485/jsti.v1i2.20

Abstract

The rapidly evolving technology era demands a secure and efficient authentication mechanism when exchanging information between users and servers. One of the most common authentication methods used in REST APIs is JSON Web Token (JWT) due to its stateless and lightweight nature. However, the implementation of static JWT still has a weakness because pre-existing tokens can be used in other contexts such as other devices or other IP addresses. This can result in token misuse, resulting in data leakage. This study was conducted by comparing the performance and security aspects of static JWT and dynamic JWT in REST APIs using the PHP Laravel framework. Testing results show that the implementation of static and dynamic JWT does not have a significant difference in performance. However, dynamic JWT excels in security aspects because it is able to detect unauthorized access attempts due to context mismatch.
Predicting Bitcoin Price Trends Using an LSTM Model Based on Multi-Variable Technical Indicators Rizky Parlika; Ilham Asy’ari; Rizky Ananda Ramadhan
Jurnal Serumpun Teknik Informatika Vol. 1 No. 2 (2026): April 2026
Publisher : Yayasan Ibrahim Learning Centre Agam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66485/jsti.v1i2.21

Abstract

The sharp price fluctuations in the cryptocurrency market, particularly in Bitcoin (BTC), create significant risks while simultaneously offering speculative profit potential for investors. Traditional analytical methods are often ineffective in detecting non-linear patterns present in stochastic financial time series data. This study proposes the application of a Deep Learning model utilizing the Long Short-Term Memory (LSTM) architecture to project the directional trend of Bitcoin prices (whether upward or downward) for the upcoming one-hour period. In the model's development, historical price data is integrated with a set of crucial technical variables, including the Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), and Exponential Moving Average (EMA), which serve as input attributes to enhance accuracy. Market data is retrieved in real-time via the Binance API, covering the last 1000 candlesticks. Experimental results using a Stacked LSTM architecture demonstrate that the model achieves an accuracy rate of 51.08% on the test data. Although this classification accuracy is considered moderate, a simple backtesting simulation indicates a positive profitability potential of 2.88% with a win rate of 48.39%. The output of this research also includes a web-based system prototype that integrates a Python backend with a visual interface for real-time monitoring of prediction signals.
RESTful API Development for Student Schedule and Attendance Management in a Higher Education Environment Rizky Parlika; Abidin Sulaiman; Riky Hermawan
Jurnal Serumpun Teknik Informatika Vol. 1 No. 2 (2026): April 2026
Publisher : Yayasan Ibrahim Learning Centre Agam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66485/jsti.v1i1.22

Abstract

This study presents the development of a RESTful API service to support student schedule and attendance management in a higher education environment. The research is motivated by the fact that schedule management and attendance recording are often still handled manually or by stand-alone applications, which complicates recap processes, attendance monitoring, and integration with existing academic information systems. The proposed system is implemented using the Laravel framework and MySQL database, where student, lecturer, course, schedule, and attendance entities are modeled in a structured way and exposed through RESTful endpoints over HTTP with JSON data format. The research adopts a software engineering approach consisting of requirement analysis, system design, implementation, and testing using Postman on a local development environment. The experimental results show that all CRUD operations and attendance recording functions work as expected, producing consistent JSON responses with appropriate HTTP status codes, indicating that the developed API is suitable to be used as a foundation for future integration with web and mobile applications
Implementation of Multi-Criteria Decision Making in PPPK Recruitment at the Department of Public Works, Spatial Planning, Housing, Settlement Areas, and Land Affairs of Riau Province Andrianto Saputra; Octadino Haryadi
Jurnal Serumpun Teknik Informatika Vol. 1 No. 2 (2026): April 2026
Publisher : Yayasan Ibrahim Learning Centre Agam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66485/jsti.v1i2.23

Abstract

The recruitment process of Government Employees with Work Agreements (PPPK) at the Department of Public Works, Spatial Planning, Housing, Settlement Areas, and Land Affairs of Riau Province requires an objective and transparent evaluation system. This study aims to implement the Multi-Criteria Decision Making (MCDM) method as a decision support system to determine the most suitable PPPK candidates. The assessment is conducted based on several criteria, including educational qualifications, competencies, work experience, and selection results. Each criterion is assigned a weight according to its level of importance to produce an objective ranking of candidates. The results show that the MCDM method can support decision-makers in the PPPK recruitment process in a systematic, consistent, and accountable manner.

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