Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : journal of system and computer engineering

Performance Analysis of API in Google Cloud Storage Service Integration Namruddin, Respaty; Sam, Rafiqa Mulia Indah Sari; Syamsuddin, Rajul Waahid; A, Amiruddin; Kunaefi, Aang
Journal of System and Computer Engineering Vol 6 No 1 (2025): JSCE: January 2025
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v6i1.1637

Abstract

Google Cloud Storage (GCS) is one of the leading cloud storage services that supports large-scale data management through API integration. APIs allow applications to upload, download, and manage data in real-time. This study aims to analyze the performance of APIs in integration with GCS using response time, throughput, and latency parameters. Tests were conducted on various scenarios, including massive data transfer, distributed data management, and caching usage. The results showed that the average API response time reached 120 ms under normal conditions and increased to 180 ms under high load. Throughput reached an average of 400 MB/s, but decreased when the number of simultaneous requests increased. The average server latency was recorded at 60 ms and can be optimized with caching technology. Implementation of strategies such as Content Delivery Network (CDN) and request header optimization can improve performance by up to 30%. This study provides practical guidance for developers to optimally utilize GCS APIs in large-scale data management.
Performance Evaluation of IoT-Based AC Control Using Multi-Modal Fuzzy Sensors A, Amiruddin; Arda, Abdul Latief; Jalil, Abdul; Achmad, Andani; Sahibu, Supriadi; Yuyun, Yuyun
Journal of System and Computer Engineering Vol 7 No 2 (2026): JSCE: April 2026
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v7i2.2649

Abstract

his study addresses the challenge of controlling Air Conditioner (AC) temperature in enclosed spaces in tropical climates, where improper operation often leads to thermal discomfort and excessive energy consumption. The research aims to develop and implement an Internet of Things (IoT)-based system for monitoring and controlling AC temperature by integrating multi-modal sensors and applying a fuzzy logic approach. The proposed system employs a DHT22 sensor to measure temperature and humidity, a thermopile sensor to capture human body temperature, and a PIR sensor to detect occupancy and movement within the room. Sensor data are processed using an ESP32 microcontroller with FreeRTOS-based multitasking and transmitted to the Blynk platform for real-time monitoring. Decision-making is carried out using fuzzy logic based on the temperature difference (ΔT) between body temperature and ambient conditions to automatically regulate AC operation. Experimental results indicate that the system performs reliably and provides adaptive control, achieving a fuzzy logic accuracy of 64.34% under real-world conditions. Furthermore, the automated control mechanism reduces energy consumption by 35.7% compared to conventional manual operation. Overall, the findings confirm that the integration of multi-modal sensing, IoT technology, and fuzzy logic can effectively enhance energy efficiency while maintaining thermal comfort in indoor environments.