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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) TIN: TERAPAN INFORMATIKA NUSANTARA Proceeding International Applied Business and Engineering Conference
Fikri Muhaffizh Imani
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Aggregator Backend API With KrakenD Fikri Muhaffizh Imani
International ABEC Vol. 2 (2022): Proceeding International Applied Business and Engineering Conference 2022
Publisher : International ABEC

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (737.692 KB)

Abstract

Implementation of API Gateway to secure and expose backend API as an endpoint that can be accessed by the client is ideal step in developing an integrated system. The client makes a request through an endpoint exposed by API Gateway to get the data needed to display a web page, but the server load will increase if the page requires data from several endpoints that require multiple requests to be made to the server. Vertical scaling can be applied to increase server resources in order to handle these requests, but this solution costs a lot of money. This research was conducted to overcome the problem of multiple requests by clients without having to do vertical scaling by implementing KrakenD as an aggregator backend API to combine several backend API into one and expose the combined results back into a new endpoint. Based on the results of the study, aggregation on several API backends was able to reduce 75% of the request load to the server. This solution can become novel consideration in building an information system that requires data from several different backend API.
Pengembangan Sistem E-Office Menggunakan Metode Rapid Application Development Imani, Fikri Muhaffizh; Saf, Maksum Ro’is Adin
TIN: Terapan Informatika Nusantara Vol 6 No 2 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i2.7704

Abstract

Manual handling of correspondence services using physical documents and informal communication platforms such as WhatsApp remains a common challenge in improving the efficiency and transparency of public sector administration. This condition was also identified at a government-affiliated educational institution, LLDIKTI Region XVII, where traditional processes have led to inefficiencies and limited transparency in administrative interactions with higher education institutions. This study aims to design and develop an E-Office system featuring customizable service request forms, dynamic disposition workflows, and a clearly documented approval history. The system was developed using the Rapid Application Development (RAD) method, which encourages active user involvement throughout the development cycle to ensure that the final product aligns with user needs and can be delivered within a shorter timeframe. The results indicate that the system improves service management by centralizing the submission, approval, and delivery of official correspondence into a single integrated platform. The disposition process also becomes more transparent, allowing universities to track the status of their submissions in real time. In addition, the ability to adjust forms and workflows without modifying the system’s source code makes it highly adaptable to changes in business processes. Black box testing on 10 key functions showed a 100% success rate, confirming the system’s functional reliability.
Reward Scheme Analysis for DQN-Based Adaptive Traffic Signal Control in Road Repair Zones Yoanda Alim Syahbana; Muhammad Wahyudi; Fikri Muhaffizh Imani; Ardianto Wibowo; Fatur Rizky Al-Farisz
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 3 (2026): June 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i3.7381

Abstract

Traffic congestion caused by temporary road repairs often forces bidirectional traffic to alternate through a single lane, leading to increased delays and imbalanced traffic flow. This study investigates the impact of reward scheme design on the performance of a Deep Q-Network (DQN)-based adaptive traffic signal control system in such constrained environments. Using the Simulation of Urban Mobility (SUMO), a traffic scenario involving 1,656 vehicles over 1,800 seconds was modeled to evaluate six reward scheme configurations combining Traffic Flow (TF), Waiting Time (WT), and Average Speed (AS): TF-TF, TF-WT, WT-TF, WT-WT, AS-TF, and AS-WT. The DQN agent, implemented with a two-layer neural network and trained for 50 epochs, dynamically adjusted signal timing to balance traffic from opposing directions. Experimental results indicate that the AS-WT configuration achieved the most balanced performance, producing the best fairness index (1.04) while maintaining stable traffic flow. In contrast, schemes with misaligned or redundant metrics showed significantly poorer performance. These findings highlight the importance of reward design in reinforcement learning-based traffic signal control and suggest that carefully selected reward schemes can improve fairness and efficiency in temporary road repair zones.
Co-Authors Ardianto Wibowo Fatur Rizky Al-Farisz Muhammad Wahyudi Saf, Maksum Ro’is Adin Yoanda Alim Syahbana