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Rahmadya Trias Handayanto
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rogram Studi Teknik Komputer Fakultas Teknik Universitas Islam 45 Jl. Cut Meutia No. 83 Bekasi 17113
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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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Information System for Data Collection on Building Tools and Materials Using the Rational Unified Process (RUP) Method Siregar, Sahnas Wulandari; Putri, Raissa Amanda
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 2 (2024): September 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i2.9951

Abstract

UD. FLORA records the re-inventory of building equipment that has been sold by reading the transactions one by one in the ledger. A proper way is needed to overcome the problems that occur. This research aims to create an information system software. In making information system software, a method is needed that can carry out the stages from initial design to implementation of the software. This research uses the Rational Unified Process (RUP) method, namely a software development approach that is carried out repeatedly (iterative), focuses on architecture (architecture-centered), is more directed based on use cases (use case driven). This research produces a tool data collection application at UD. FLORA using the RUP method. The existence of an information system for data collection on building equipment using the Rational Unified Process method means that UD. FLORA can be helped in managing building equipment data collection. The system enables real-time transaction recording, providing better insight into inventory status, and supporting more accurate decision-making.
Traffic Congestion Detection Using YOLOv8 Algorithm With CCTV Data Indra Bayu Pangestu; Maimunah, Maimunah; Mukhtar Hanafi
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 2 (2024): September 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i2.9953

Abstract

Community development and growth according to data from the Central Java Statistics Agency regarding the number of vehicles in Central Java Province in 2021 is 20 320 743. The increasing growth of society has caused vehicle density which is a serious problem in urban areas. This study developed a congestion detection system using the YOLOv8 algorithm to analyze traffic density from CCTV footage. Automated detection of traffic congestion is a critical challenge in urban transport management. YOLOv8, a fast and accurate object detection algorithm, is used to identify vehicles and count their number in various areas of the highway. This information is then processed to assess road congestion conditions, with the aim of detecting congestion. The data obtained were tested on two road scenarios and traffic conditions to evaluate the performance of the system. The results showed that the proposed system was able to detect congestion with an accuracy level of 59.2% from several experiments. The use of YOLOv8 enables real-time detection with efficient computing resources, making it a potential solution for large-scale deployment. This research shows that the incorporation of advanced object detection algorithms such as YOLOv8 with CCTV data can provide an effective solution for traffic management in large cities. This system is expected to improve response to congestion, help control traffic, and reduce the negative impact of congestion in urban areas
Comparison of Latent Semantic Analysis (LSA) and Doc2Vec Algorithms of Thesis Similarity Detection Arifin, Rita Wahyuni; Putra, Mardi Yudhi; Putri, Dwi Ismiyana
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 2 (2024): September 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i2.9954

Abstract

This study aims to develop a system for detecting similarities in thesis titles and content to prevent plagiarism and support student originality. The high level of similarity in final projects is a significant concern in academic environments. Two text vectorization methods, Latent Semantic Analysis (LSA) and Doc2Vec, were compared to measure document similarity. Results showed that LSA achieved a very high cosine similarity (99.94%) due to dimensionality reduction that preserved semantic correlations. In contrast, Doc2Vec produced lower similarity scores, with 7.17% for PV-DM and 39.07% for PV-DBOW, indicating richer text representations. This study adopted the CRISP-DM model, which includes Business Understanding, Data Understanding, Data Preparation, Modelling, and Evaluation. The model is expected to strengthen academic integrity and encourage valuable scientific contributions.
Comparison of Apriori and FP-Growth Algorithms in Analyzing Association Rules Mitha Rosadi; Muhammad Siddik Hasibuan
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 2 (2024): September 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i2.9965

Abstract

The problem objectives of this research include the following: To implement Apriori and FP-Growth Algorithms in determining the comparison of association rules and To build a jupyter notebook application model in determining the comparison of association rules of Apriori and FP-Growth Algorithms. This research compares Apriori and FP-Growth algorithms in analyzing association rules, with a focus on implementation and model development in Jupyter Notebook. Through manual calculation using 10 transaction data samples and testing on 38,765 groceries data entries from Kaggle, differences were found in the lift results between itemsets. Apriori algorithm often shows a negative relationship between items, while FP-Growth gives a similar interpretation but with slightly different lift values, showing a different influence in the relationship between items. In addition, FP-Growth proved to be more efficient with a much faster execution time (5.2757 seconds) than Apriori (185.9585 seconds), especially in handling large datasets. The results of this study indicate that the selection of an appropriate algorithm should consider the characteristics of the dataset and the purpose of the analysis.
A Comparative Analysis of MultinomialNB, SVM, and BERT on Garuda Indonesia Twitter Sentiment Prasetyo, Budi; Ahmad Yusuf Al-Majid; Suharjito
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 2 (2024): September 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i2.9966

Abstract

This study investigates customer sentiment towards Garuda Indonesia Airlines (GIA) using sentiment analysis of Twitter data. The research aims to identify prevailing sentiments, uncover common themes in customer feedback, and provide recommendations for improving customer satisfaction and brand loyalty. A dataset of 1,250 tweets from March 2007 to July 2024 was collected and pre-processed, including cleaning, language detection, and tokenization. Sentiment analysis was conducted using three models: MultinomialNB, SVM, and BERT.The results indicate that BERT outperformed both MultinomialNB and SVM in sentiment classification accuracy, achieving 75.6%. This highlights the effectiveness of BERT in capturing contextual meaning within customer reviews. The findings of this research will contribute to a deeper understanding of customer sentiment towards GIA and inform strategies for enhancing customer experience and brand image.
Analyzing Land Suitability for Housing in Bekasi Regency: Managing Farmland Conversion During Urban Growth Herlawati, Herlawati; Handayanto, Rahmadya Trias
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 2 (2024): September 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i2.9968

Abstract

Bekasi Regency is a buffer area for Jakarta and is part of the Jakarta Metropolitan Region (JMR). Along with Karawang, this region is a major rice producer, but it is currently experiencing significant land conversion from agriculture to residential and industrial uses. Preventing this conversion is very challenging due to the high population growth in the area. To address this issue, this study aims to conduct a suitability analysis to identify areas that are unsuitable for agricultural land but still suitable for residential purposes. The factors considered in the suitability analysis include slope, distance to roads, distance to residential areas, distance to facilities and infrastructure, and distance to rivers and irrigation systems. The results of the study identify areas that are unsuitable for agriculture, allowing local governments to focus on these areas as potential sites for new residential developments. The location is situated in the southern part of Bekasi Regency, specifically in the Cikarang area and its surroundings.
Designing a Service Provision Website Using the Design Thinking Method Rasmila, Rasmila; Dilla Nafasari
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 2 (2024): September 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i2.9972

Abstract

Berkarya Abdi Sejahtera is a company that operates in the field of Outsourcing services such as Administration, Data Input, Operator, Warehouse, Labor, Security, Office Boy/Grill, Driver, Technician, Mechanic, and others. One way to increase company development is by using the website. Websites are increasing rapidly along with the number of websites that are used as a tool to promote companies to make them better known. Based on previous research conducted regarding Thrifdoor Business Website Design Using the Design Thinking Approach Method, it states that the creation process uses the Design Thinking method. The aim of this research is to create a website design by innovating using the Design Thinking method. and it is hoped that the design of this website will make it easier for companies to introduce their company. Observation is a process of observing and then recording systematically, logically, objectively and rationally regarding various phenomena in real situations, as well as artificial situations. The author collects and reviews data obtained by direct review and monitoring. Interviews are conducted to obtain data and information in the form of questions and answers from people who are directly involved with the system that is the object of research. Interviews will be conducted with members of PT Berkarya Abdi Sejahtera at the design stage. The 5 stages of design thinking: empathize, define, ideate, prototype, and test.
Android-Based E-commerce Design for Ceramic Sales at Material Stores Using the Up-Selling Method Lili Saputri; Aninda Muliani Harahap
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 2 (2024): September 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i2.9974

Abstract

In today's rapidly growing digital era, information systems are one of the important aspects of managing a business. Especially in the trading industry, such as ceramic sales, the use of information technology can provide a significant competitive advantage. UD Sinar Debora is a shop engaged in the sale of materials. In terms of sales, UD Sinar Debora Sibolga has also experienced a significant increase, especially in the ceramic sales section. The problem faced at the ceramic material shop is that the promotions carried out have not been effective, only done conventionally, buying and selling transactions are still done manually. Therefore, it is necessary to have a web-based digital marketing application as a strategy to expand marketing and facilitate sales reach. To overcome the above problems, it is necessary to have a product marketing strategy, one of which is Up Selling. This method is used to increase sales achievement by introducing new products or other best products. By using the upselling method, UD Sinar Debora material store can implement a digital marketing strategy with clear direction and evaluation.
Implementation of the Framework for the Application System Thinking (FAST) Method on the Management Information System of the Al-Ittihad Mosque Ronny Ramadhan Hasibuan; Samsudin
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 2 (2024): September 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i2.9975

Abstract

The purpose of this research is to implement the FAST (Framework for The Aplication System Thingking) method on the mosque management information system. And to build and design a mosque management information system by applying the FAST (Framework for The Aplication System Thingking) method for decision making in the reminder system. The results of the study concluded that the existence of this Mosque Management Information system can help activities in the mosque, this system can manage the rental process, khatib reminders, information on BKM activities and the BKM can easily manage activities and make it easier for the community to get information and will save more time and costs, so that what is needed by the community will be better.
Classification of Traffic Violations Using the Naïve Bayes Algorithm at Padang City Police Febrera , Gerryliyus; Prianggono, Jarot
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 2 (2024): September 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i2.10018

Abstract

Traffic violations have been increasing each year. According to data from the Padang City Police from 2018 to 2023, there were 128,913 traffic violation cases. This is not a small number, and it is time for the police to start utilizing machine learning (ML) technology to evaluate traffic violation cases, as ML can identify hidden patterns or information that cannot be detected manually by conventional statistics or by traffic officers. This research aims to classify traffic violations using the Naïve Bayes algorithm at the Padang City Police by conducting evaluations and comparisons using different dataset ratios. The best algorithm obtained from the comparison will then be analyzed, and the research findings are expected to serve as a reference for the relevant authorities. This research is quantitative in nature, using an experimental method. The data sources or information were obtained from traffic ticket documentation at the Padang City Police and questionnaires distributed to traffic officers of the Padang City Police. The research results show that the Naïve Bayes (NB) algorithm can be used to classify traffic violations at the Padang City Police. The performance test results of the Naïve Bayes (NB) algorithm using all comparison algorithms with different training and testing dataset ratios resulted in 100% accuracy. However, during cross-validation, the Naïve Bayes algorithm achieved the highest accuracy only with training and testing dataset ratios of 80%:20% and 90%:10%. This is due to the large dataset size in this research, which is more than 100,000 entries. The evaluation results of the Naïve Bayes algorithm show that the best model is achieved with the Naïve Bayes algorithm using an 80% training and 20% testing dataset split. Although the performance is similarly high with a 90%:10% training and testing ratio, the researcher chose the 80%:20% training and testing ratio as the best algorithm for reasons of efficiency during training. The argument is that even with just 80%, it is able to predict/classify 20%, which is more efficient than training 90% to predict/classify 10%. Another finding from this implementation is that with a large dataset of 100,000 entries or more, high and stable performance can be achieved, so this research also suggests that to achieve good results from traffic violation classification, the dataset should be above 100,000 entries.

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