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Rahmadya Trias Handayanto
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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 18 Documents
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Search results for , issue "Vol. 13 No. 1 (2025): Maret 2025" : 18 Documents clear
Implementation of Hardening for Optimization of Wireless Local Area Network Security Rahmat Novrianda Dasmen; Muhammad Reihan Pratama
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.v13i1.9957

Abstract

Computer networks use two main methods for data transmission, namely wired and wireless networks or what is known as a Wireless Local Area Network (WLAN). In WLAN networks, the security standard usually used is the WiFi Protected Access 2 Pre-Shared Key or WPA2-PSK protocol, which utilizes SSID and password. Despite using security mechanisms such as WPA2-PSK, criminal activities such as intrusion into the network still occur. Therefore, it is necessary to improve the network security system to ensure that the WLAN network is more secure and can minimize potential risks to users. This study aims to improve and optimize the WLAN network security system through vulnerability scanning using the Nessus tool to test the level of security on the WLAN network and the application of hardening methods to strengthen and disguise vulnerabilities on the WLAN network, which includes various security techniques such as applying raw firewalls and firewall filters, limiting ports and services used and disabling services that are not needed to minimize vulnerabilities, disabling the Mikrotik neighbor discovery protocol service on the router, and implementing port knocking as an additional layer of security. The results of the study show that applying vulnerability scanning techniques and hardening methods can help minimize the level of risk of vulnerabilities found and make the resilience of the WLAN network more optimal so as to avoid potential intrusions and threats of attacks.
Interactive Learning Media for Early Childhood Education through Android-Based Educational Games using GDLC Method Rahmadi, Lendy; Effendi, M. Junius; Hasibuan, Muhammad Said
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.v13i1.10129

Abstract

The rapid development of technology has influenced various aspects of life, including education. One of the innovations in the field of education is the use of technology-based learning media, such as interactive multimedia, which can enhance students' interest in learning. This research aims to develop an Android-based educational game called Edufun Kids Game, using the Game Development Life Cycle method. (GDLC). This game is designed to help early childhood children recognize letters, numbers, animals, and fruits interactively, creating a fun learning atmosphere and making it easier for educators to deliver the material. The research was conducted at the Tunas Ilmu Early Childhood Education in Pagar Alam City, where the previous learning media was still conventional. The implementation of the Edufun Kids Game shows positive results in increasing children's learning motivation and facilitating a more effective teaching and learning process, as evidenced by beta testing results where 85% of respondents rated the game as helpful for preschoolers in recognizing numbers, letters, animals, and fruits. The use of Android technology allows this application to be easily accessed on mobile devices, providing flexibility for users. The development of Android-based educational games can be an innovative solution to improve the quality of early childhood education
YouTube Streaming Performance Over Wi-Fi: A Resolution-Based Analysis Haries Anom Susetyo Aji Nugroho; Sonhaji; Andika Chandra Prasetyo
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.v13i1.10580

Abstract

The quality of YouTube video streaming services affects the learning process through video streaming. With poor video service quality, it will disrupt the process of obtaining information. Therefore, there is a need for good video service quality following existing service quality standards on the internet network, according to ITU. Streaming video on YouTube consists of several resolutions. The higher the video resolution, the better the video quality but inversely proportional to the greater the internet bandwidth required. This research tries to compare the quality of YouTube video streaming services at 480p and 720p resolutions to find out if there is a significant difference between the two resolutions of video streaming services. The results obtained from this study are to determine whether or not there is a significant difference between 480p and 720p video streaming services as a consideration in determining network service policies. The method used in this research is to observe data collection directly on WiFi spread in the university environment and the data is processed to get quality of service value at 480p and 720p video resolution. Then the results of the data processing are analyzed again with statistical tests to obtain information from the comparison of the two streaming video resolutions in terms of throughput, jitter, delay, and packet loss. The results of the research show that there are no significant differences in delay, jitter, throughput, and packet loss on YouTube video streaming services at 480p and 720p resolutions.
TOPSIS and WP for BLT Decision Support in Srimulyo Abror , Muhamad; Hasibuan, Muhammad Said
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.v13i1.10606

Abstract

Srimulyo Village, situated in Anak Ratu Aji District, Central Lampung Regency, faces difficulties in ensuring an accurate and efficient process for determining recipients of Direct Cash Assistance (BLT). The current manual system often results in errors and perceived inequities. This research explores the application of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method alongside the Weighted Product (WP) method to enhance decision-making in selecting BLT recipients. TOPSIS is employed to identify optimal alternatives based on their closeness to a positive ideal solution, while WP emphasizes the importance of criteria through assigned weights. The findings indicate that integrating these two methods yields recommendations that are more objective, transparent, and efficient. The TOPSIS approach enables the system to rank alternatives by assessing their proximity to the ideal solution, facilitating data-driven decision-making. Meanwhile, the WP method ensures that each criterion's importance is appropriately weighted, thereby increasing the reliability of the results. This dual-method approach not only minimizes human error but also promotes fairness in the selection process. The proposed integrated system offers a practical solution to improve the accuracy of social assistance distribution in Srimulyo Village. By adopting these decision-support methods, local authorities can establish a more equitable, reliable, and efficient mechanism for BLT allocation, ensuring that aid reaches the individuals who need it most.
Design and Development of a Feeding Control System for Fish in Cultivation Ponds Sudibyo, Novi Herawadi; Nugroho , Bayu; Ade, Danang; Hasibuan , MS; F, Imam; Riandi , Riandi; Jalur, Bayu
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.v13i1.10614

Abstract

Fish farming is one of the crucial sectors in supporting food security and the community's economy. However, one of the primary challenges faced by fish farmers is managing feed distribution efficiently and on time. This study aims to design and develop an automated fish feeding control system for cultivation ponds. The system is designed using a microcontroller as the central controller, equipped with a timer sensor and a motor to distribute feed according to a predefined schedule. Testing was conducted to measure the accuracy of feed distribution, the system's reliability under various environmental conditions, and its impact on fish growth. The results show that the developed system can provide feed automatically and consistently based on the set schedule, with a very low error rate in feed distribution. Additionally, the system improves feed utilization efficiency and minimizes waste, contributing to reduced operational costs. This automated control system is expected to be an effective solution to support fish farming activities, enhance productivity, and promote the adoption of technology in the aquaculture sector
Sentiment Analysis of Free Nutritious Meal Programme on Social Media X using Linear Regression and Random Forest Algorithms Hermansyah, Idi; Hasibuan, Muhammad Said
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.v13i1.10633

Abstract

This study analyzes public sentiment towards the Free Nutritional Food Program on social media platform X using Linear Regression and Random Forest algorithms. By collecting data from Twitter and employing sentiment analysis methods based on natural language processing, this research aims to measure societal perceptions and compare the effectiveness of both algorithms in sentiment classification. The results indicate that Random Forest outperforms Linear Regression with an accuracy of 0.85 and a recall of 0.97, compared to Linear Regression, which achieves an accuracy of 0.83 and a recall of 0.91. While Linear Regression excels in precision with a score of 0.86, whereas Random Forest records 0.85, overall, Random Forest achieves a higher F1-Score of 0.90 compared to Linear Regression's score of 0.88. These findings provide important insights for governments and policymakers in responding to public opinion and designing more effective interventions to enhance the program
Sentiment Analysis of Mobile Banking Reviews Using Machine Learning Models Rahayu, Sri; Hasibuan, Muhammad Said
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.v13i1.10677

Abstract

With the increasing use of mobile banking applications in Indonesia, understanding user reviews and feedback has become increasingly important for banks to enhance the services and performance of the applications they offer. This research aims to analyze user sentiment towards the mobile banking applications BCA, BNI, Brimo, and Byond by BSI, and to compare the effectiveness of the Random Forest, K-Nearest Neighbor (KNN), Naive Bayes, and Support Vector Machine (SVM) algorithms. The data used consists of user reviews obtained from Google Play Store through web scraping techniques, with 4,000 samples of reviews divided into training data (80%) and testing data (20%). The pre-processing process is conducted to prepare the data, which includes stopword removal and tokenization, using the Bag of Words (BoW) method.Based on the labeling results that can be seen in the visualization stage, it is known that the Byond by BSI Mobile application has a positive sentiment with 540 more reviews and a negative sentiment with 528 fewer reviews compared to other mobile banking applications. In the form of a comparative matrix graph, the Random Forest algorithm has a higher accuracy value of 0.58 for the BCA application and 0.74 for the Brimo application, while Naive Bayes has an accuracy value of 0.71, which is greater for the BNI mobile banking application, and Support Vector Machine has an accuracy value of 0.74, which is higher for the Byond by BSI mobile banking application. From the explanations above, it means that the Random Forest algorithm is capable of classifying efficiently and effectively compared to the other three algorithms. With the results of this research, it is hoped to provide important insights for mobile banking application developers to improve service quality based on user feedback, as well as to recommend the use of Random Forest for more accurate and reliable sentiment analysis.
Blanket Pixel-Based Segmentation for Detecting Object Geometry Sucipto, Putra Wisnu Agung; Wibowo, Danang Arengga; Firasanti , Annisa; Bakri , Muhammad Amin; Yaqin , Khusnul
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.v13i1.10727

Abstract

This study aims to develop a blanket pixel-based approach to construct object geometry for image segmentation. Object geometry can be formed from a collection of pixels generated from the edge detection process. However, edge pixels that will be included in a segment must go through an identification process to determine their identity, with a reference segment as a reference for labeling. This work proposes the terminology of blanket pixels, namely pixels that surround a pixel that does not yet have an identity due to being isolated from the surrounding segments, as a spatial exoskeleton for the labeling process. This approach has been tested, and the results show that we successfully detect the structure of tilapia egg circles with clear fortifications when the scanning radius parameter is set to 10 pixels and the proximity between the surrounding pixels and the labeled pixels is 11.8 pixels. Out of 114 egg circles, this method successfully detected 105 eggs, with 9 small eggs (2–3 pixels in diameter) undetected, resulting in a detection ratio of 92.11%. The blanket pixel approach effectively recognizes and reclassifies isolated pixel labels. This approach supports the process of labeling pixels in areas with significant ambiguity.
Long Short Term Memory-Based Marine Data Prediction with Pearson Correlation Mukhlis, Mukhlis; Jaya, Indra; Nurdiati, Sri; Priandana, Karlisa; Hermadi, Irman
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.v13i1.10731

Abstract

Marine data prediction plays a vital role in supporting decision-making in the field of marine environment and resources. However, the complexity of marine data, which is nonlinear and dynamic, is a significant challenge in producing accurate predictions. This study aims to explore the role of Long Short-Term Memory (LSTM) models in computer systems to predict marine data, focusing on Pearson Correlation analysis. The methods applied include collecting historical marine data, implementing LSTM models for prediction, and evaluating performance using metrics such as Mean Absolute Error (MAE). In addition, Pearson Correlation analysis is used to understand the relationship between variables in marine data. The results show that the LSTM model is able to produce predictions with a low error rate with a composition of training data and testing data of 80:20, resulting in Sea Surface Temperature (SST) = 0.0053, Sea Surface Salinity (SSS) = 0.0026, sea Surface Height (SSH) = 0.0061 and CHL-a = 0.0002 and shows a significant relationship between variables through Multivariate correlation analysis. This research contributes to the development of marine data-based prediction systems and provides implications for the world of marine resource research and management.
Sentiment Analysis of YouTube Comments Using Machine Learning Models Susanti, Erma; Maimunah, Maimunah; Nugroho, Setiya
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.v13i1.10743

Abstract

The documentary video “115. You Are Human Too” from the #MenjadiManusia YouTube channel raises mental health issues with an empathic narrative approach. Social media plays a role in shaping public understanding, but opinions vary from support to stigma. This study analyzed the sentiment of 1,350 comments on the video using the YouTube API. Comments were classified into positive, negative and neutral sentiments using the IndoBERT model after preprocessing. Four machine learning algorithms were compared: Naïve Bayes, Random Forest, Support Vector Machine (SVM), and Extra Trees. Results showed that SVM had the highest accuracy (79.67%), followed by Random Forest (78.02%), Extra Trees (75.27%), and Naïve Bayes (70.33%). This analysis reveals patterns of public opinion on mental health, which can serve as a reference for academics, health practitioners, and policy makers in designing more effective communication strategies. In addition, this research is expected to increase public understanding of mental health and encourage more inclusive discussions on social media.

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