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PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic
Published by Universitas Islam 45 Bekasi
ISSN : 23033304     EISSN : 26203553     DOI : https://doi.org/10.33558/piksel
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Jurnal PIKSEL diterbitkan oleh Universitas Islam 45 Bekasi untuk mewadahi hasil penelitian di bidang komputer dan informatika. Jurnal ini pertama kali diterbitkan pada tahun 2013 dengan masa terbit 2 kali dalam setahun yaitu pada bulan Januari dan September. Mulai tahun 2014, Jurnal PIKSEL mengalami perubahan masa terbit yaitu setiap bulan Maret dan September namun tetap open access tanpa biaya publikasi. p-ISSN: 2303-3304, e-ISSN: 2620-3553. Available Online Since 2018.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 304 Documents
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Mobile Application for Market Data Collection of Property Tax Object Pratama, Devriady
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 1 (2025): Maret 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i1.10748

Abstract

This research focuses on designing a mobile application for collecting property market data to support Land Value Zone (ZNT) analysis for local governments. Currently, market data collection processes are often conducted manually, which is time-consuming, resource-intensive, and prone to subjectivity. The proposed application leverages mobile technology to enhance the efficiency and effectiveness of field data collection with features such as user authorization, geographic data storage, and multimedia data storage, including images. The research adopts the prototyping method, involving direct interaction between developers and users. Testing results indicate that the application performs its functions effectively and facilitates data collection based on Geospatial Information Systems (GIS). This study suggests further development for other mobile platforms and modules for price analysis based on ZNT.
Comparative Analysis of Triangulation Methods for Optimal Solutions to the Art Gallery Problem Marzal, Jefri; Niken Rarasati; Waladi, Akhiyar; Perdana, Yogi
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 1 (2025): Maret 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i1.10749

Abstract

Triangulation is the process of breaking down an n-sided polygon into triangles and it is necessary in deciding the optimal count and the position of guards in the Art Gallery Problem (AGP) There is a theoretical limit that has been established which states that the number of required guards needed to keep an eye on such a polygon is ⌊n/3⌋ and this research considers this as the limit. Among various triangulation methods, Ear Clipping and Minimum Weight are two primary approaches frequently used to achieve optimal solutions. Nonetheless, its comparison with other methods, more particularly the amount of guards required for the maximum theoretical figure, is still a gap in literature. The aim of this research is to create an AGP simulation program and test it against the theoretical upper bound, determining the number of guards required. 228 simple polygons with vertices varying between 10 and 110 were utilized in this research. The polygons were classified into three groups based on the ratio of convex to concave vertices: less concave vertices, equal amount of concave and convex vertices and vice versa. Result study shows that the Ear Clipping method is significantly superior to Minimum Weight in reducing guard requirements. Practically speaking, these advancements are important for the design of engineering systems such as surveillance systems and the surveillance of public spaces. In the context of building security system design and monitoring of large areas, these conclusions are of utmost importance.
LSTM Parameter Optimization with Genetic Algorithm for Stunting Prediction Muhammad Fikri, Rifqi; Purbasari, Ayi; Zulianto, Arief; Ruluwedrata Rinawan, Fedri; Indra Susanti, Ari
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 1 (2025): Maret 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i1.10761

Abstract

Stunting is caused by a lack of nutrients or sickness, and stunted children may have impaired immune systems, increased mortality rates, and are more prone to endure long-term developmental abnormalities. Stunting prevalence in Indonesia remains concerningly high by the end of 2024. Through the use of integrated health posts, or pos pelayanan terpandu (Posyandu), and the technology-based website iPosyandu, attempts are being made to lower the prevalence of stunting. Using toddler data from iPosyandu, this study proposes a Long-Short Term Memory (LSTM) model for predicting stunting based on WHO standards, categorizing children as tall, normal, stunted, or severly stunted. By using a genetic algorithm (GA) for learning rate hyperparameter tuning, the LSTM model is significantly improved. Five generations, each with five populations, were used for the GA-based optimization, which explored learning rates ranging from 5.23E-04 to 8.83E-03. The results show that 7.82E-03 was the optimal learning rate, producing the greatest accuracy of 91.10%, indicating that this range improves the performance of LSTM models.
Object Detection Using YOLOv5 and OpenCV Subagja , Mifta; Rahman, Ben
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 1 (2025): Maret 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i1.10772

Abstract

Object detection is one of the main tasks in computer vision, aimed at recognizing and localizing objects in images or videos. In this study, we utilize the YOLOv5 model, which is well known for its efficiency in realtime object detection. We implement this method with the help of the OpenCV library for image processing. This research aims to evaluate the performance of YOLOv5 in detecting objects in various types of images, including landscape photos, cat photos, and traffic light images with vehicles. The model is trained using optimization methods with the Adam optimizer and assessed through metrics like accuracy, precision, recall, and IoU. The results indicate that YOLOv5 can detect objects with high accuracy and fast inference time, making it an ideal solution for various applications such as security monitoring, video analysis, and automatic recognition systems. The advantage of YOLOv5 over traditional methods such as histogram equalization and thresholding lies in its ability to perform realtime detection with optimal computational efficiency. Thus, this study demonstrates that YOLOv5 is a suitable choice for implementing deep learningbased object detection systems.
Optimizing Migration of Applications Through Effective Risk Measurement Maniah, Maniah; Mulyati, Erna; Hamidin, Dini
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 1 (2025): Maret 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i1.10800

Abstract

Cloud Computing is a service that provides network storage space and computer resources using an internet connection as an access medium. The process of migrating to cloud computing goes through several stages sequentially and continuously, but sometimes the process of migrating to cloud computing faces obstacles or even failure, this is of course a risk for cloud service users. For this reason, before migrating to the cloud, it is necessary to prepare well, because if not, it will cause losses which will have a risk impact on the company. An effort to minimize risks for cloud service users is to carry out a risk assessment. The aim of this research is to create a model for risk assessment of logistics business applications in cloud migration. The risk value measurement model developed adopts the risk management model from the ISACA Risk IT Framework, the risk management process part of the ISO 31000 standard and adopts the phases of the OCTAVE method. Based on the method of measuring risk values from the results of this research, companies will know how much risk is likely to arise due to the use of cloud data centers, so that risk mitigation can be carried out immediately. This will have an impact on increasing the security of cloud services, and this is the main thing in increasing public confidence in using cloud services.
Web-Based Bandwidth Configuration Automation Using Scheduling Algorithm Handayani, Dwipa; Hendharsetiawan, Andy Achmad; Maulana, Muhammad Ismam
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 1 (2025): Maret 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i1.10806

Abstract

PT Mora Telematics Indonesia continues to be committed to providing the best service to satisfy customers, both in terms of the quality of the products offered and the responsiveness in handling requests. However, the process of requesting bandwidth on demand, especially in activating requests that still use conventional configurations, causes inefficiencies and the potential for human error. This can reduce customer satisfaction and hinder the speed of response to bandwidth upgrade requests. As an alternative, a solution is designed in the form of a bandwidth configuration automation system based on the priority scheduling algorithm with the aim of increasing efficiency and accuracy in managing bandwidth requests on demand. This application was developed using a waterfall development model and based on a unified modeling language with a website platform to ensure ease of use. Application functionality testing shows satisfactory performance in each process, both at the billing and NOC levels, and the priority scheduling algorithm is proven to be able to read the end-date on the bandwidth on demand data correctly
Data Security in Social Assistance Applications Using the AES-128 Algorithm Yusuf, Dani
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 1 (2025): Maret 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i1.10825

Abstract

Social assistance is one of the government's programs aimed at helping people in need. However, the process of applying for social assistance often faces issues related to data security, particularly the personal data of aid recipients. This research aims to implement the Advanced Encryption Standard (AES) algorithm with a 128-bit key (AES-128) in the social assistance application system to enhance data security. The system development method used is the prototype approach, which allows for iterative and participatory system development. The results show that the implementation of AES-128 can effectively secure sensitive data, such as identification numbers, addresses, and financial information. This system is expected to be a solution for increasing public trust in the social assistance application process.
Fine-Tuning Large Language Model (LLM) for Chatbot with Additional Data Sources Herlawati, Herlawati; Handayanto, Rahmadya Trias
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 1 (2025): Maret 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i1.10832

Abstract

Currently, Large Language Models (LLMs) are gaining popularity in implementation and research, with numerous open-source models available for use. One notable example is the AI-powered chat application, which leverages pre-trained LLMs to provide accurate and relevant information to users. By utilizing fine-tuning technology, this model can be tailored to specific student registration data, making it easier for prospective students to access the necessary information. Research findings indicate that this model achieves high accuracy in providing answers based on the inputted information. One of its advantages is its ability to generate training data through a Llama-based chat application, resulting in a more interactive and engaging user experience.
Early Detection System for Stunting in Toddlers using an Arduino-based Ultrasonic Sensor based on Body Height Rofiah, Syahbaniar; Kurniawan, Ade
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 2 (2025): September 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i2.10922

Abstract

Stunting is a very important public health problem because it can have a big impact on a generation. One of them is the risk factor of nutrition and food intake that is not fulfilled in toddlers. For this reason, a system is needed to find out earlier the growth and development period of toddlers so that stunting symptoms can be detected as early as possible so that it can provide solutions to overcome these problems. The proposer's linkage from previous research in 2018 focusing on elementary school children and toddlers is included in the research roadmap from 2018-2028. For this reason, an early detection system is designed with the stages of designing a height measuring device, toddler weight using an ultrasonic sensor and information detecting stunting is displayed on an LCD screen integrated with Arduino. The software development method uses prototypes and testing for accuracy in toddler height using Mean Absolute Percentage Error (MAPE) with a value of 2% and from the results of testing 10 toddlers, there were 3 children in the stunted category.
Financial Help Seeking and Career Adaptability Model Using Artificial Neural Network for MSMEs to Support Economic Retnoningsih, Endang; Samin, Samin
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 2 (2025): September 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i2.10928

Abstract

Help seeking and career adaptability are important factors that influence the success of achieving goals. The study aims to develop a model of the relationship pattern between financial help seeking and career adaptability specifically for MSMEs. Help seeking as an input variable and career adaptability factors as output variables, each variable is used as a model in an Artificial Neural Network. The study considers the relationship between financial help seeking and career adaptability, namely financial help seeking helps MSMEs obtain information and support from other parties to overcome problems faced and career adaptability as a result of MSMEs overcoming problems to survive running their businesses. The development of the financial help seeking and career adaptability model in the study used the Artificial Neural Network (ANN) algorithm classification method. The model built can be useful for predicting how MSMEs seek help solutions when experiencing financial difficulties related to developing their businesses and the sustainability of continuing their businesses.

Page 29 of 31 | Total Record : 304

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