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Muhammad Wali
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International Journal Software Engineering and Computer Science (IJSECS)
Published by Lembaga Komunitas Informasi Teknologi Aceh
ISSN : 27764869     EISSN : 27763242     DOI : https://doi.org/10.35870/ijsecs
Core Subject : Science,
Computer Science & IT
IJSECS is committed to bridge the theory and practice of information technology and computer science. From innovative ideas to specific algorithms and full system implementations, IJSECS publishes original, peer-reviewed, and high quality articles in the areas of information technology and computer science. IJSECS is a well-indexed scholarly journal and is indispensable reading and references for people working at the cutting edge of information technology and computer science applications..
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 387 Documents
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Developing an Android-Based Online Football News Application Using News API for CV Cipta Rasendriya Bagas Tri Prakoso; R Soelistijadi; Taufiq Dwi Cahyono
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3647

Abstract

Football is the most popular sport in the world with 4 billion fans, including in Indonesia which has the largest fan base. In the digital era, the majority of soccer fans access news via mobile devices because it is more practical than print media. However, limited access that requires users to open several websites to obtain the latest information is an obstacle. CV Cipta Rasendriya, as a football media that focuses on YouTube channels, took the initiative to develop an Android-based football news application. This application aims to make it easier for fans to access the latest news through the integration of the News API which displays real-time news from various trusted sources. Application development is carried out using the System Development Life Cycle (SDLC) Prototyping model, which was chosen because of its advantages in understanding user needs, flexibility to change, and cost efficiency. The results of application testing using the black box method showed a 100% success rate in the main test scenarios, such as news search, current news display, and navigation between pages, all of which functioned as expected. In addition, the UEQ test results showed that the application scored very well on the dimensions of Clarity (2.06), Efficiency (2.03), Attractiveness (1.92), Stimulation (1.81), and Novelty (1.69), as well as a good score on the dimension of Accuracy (1.59). The app provides more benefits than conventional methods by integrating various news into one platform, with a search feature to make it easier for users to find their favorite club news. In addition, this application has the potential to improve the user’s experience in accessing football news in a practical, fast, and relevant manner
Sales Data Visualization for Rumah Berkebun Shopee Store Using Business Intelligence and Google Data Studio Dito Ramadhani; Muhammad Adie Syaputra
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3663

Abstract

This study focuses on the analysis and visualization of sales data from Rumah Berkebun through a Business Intelligence (BI) approach, facilitated by the Google Data Studio platform. Utilizing an interactive dashboard, the research uncovers sales trends for key products such as durian and avocado seeds while identifying prominent seasonal demand variations. The dataset spans a two-year period (2022-2023) and incorporates critical metrics, including total sales, transaction volume, and order cancellation rates. Findings indicate notable seasonal fluctuations, with peak sales recorded in June 2022 and December 2023, alongside dominant market contributions from South Sumatra and Lampung. Conversely, regions like Bali and Nusa Tenggara exhibited substantial declines in sales performance. Quantitative insights were derived using statistical methods such as linear trend analysis and geographic heatmaps to map sales patterns and regional disparities. A significant challenge lies in the elevated order cancellation rates, largely attributed to payment-related obstacles, which hinder customer satisfaction. The adoption of BI has demonstrated its value in optimizing operational efficiency, enabling targeted stock and promotional strategies, and bolstering Rumah Berkebun competitive edge in digital and e-commerce landscapes. These results underscore the critical role of BI technology in fostering data-driven decision-making for online businesses.
Development of an Online Registration System for Loss Recommendation Letters at Temanggung Police Department Galih Yunus Al Anas; Edy Supriyanto
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3691

Abstract

Advancements in information technology have markedly enhanced the efficiency of public services, notably at Temanggung Police Station. Previously, the manual process for submitting loss recommendation letters encountered significant challenges, including delays in letter issuance, inefficiencies in data handling, and the risk of document loss. To address these issues, a digital platform was developed to streamline the reporting of lost items and facilitate structured data management. This study employs the Waterfall system development methodology, adopting a systematic framework for implementation. Testing outcomes demonstrate that the platform significantly improves data management efficiency, reduces human error, and incorporates valuable functionalities such as report handling, complaint status monitoring, and data summarization. Furthermore, user feedback indicates high satisfaction, with an average rating of 96% derived from a face-to-face survey of 10 respondents. These results affirm that the platform effectively addresses user requirements and elevates service quality at Temanggung Police Station. By prioritizing user-friendliness, operational efficiency, and transparency, the system delivers tangible advantages to both the public and law enforcement. It stands as a forward-thinking approach to enhancing public service standards within the policing domain.
Analysis and Visualization of Tracer Study Data Through Kimball Four-Step Method and Tableau Ardiyanto; Yohana Dewi Lulu Widyasari; Satria Perdana Arifin; Yuliska
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3718

Abstract

Tracer studies serve as a pivotal survey mechanism to assess the efficacy of educational systems and the compatibility of graduates with labor market requirements. This research leverages Big Data technologies alongside Tableau to scrutinize tracer study data gathered from alumni of Politeknik Caltex Riau (PCR) over the period from 2018 to 2022. Employing the Four-Step Kimball methodology, the study regularly undertakes data collection, processing, validation, and storage within a MongoDB database, prior to generating visual representations through Tableau. The analytical framework incorporates descriptive statistics, correlation analysis, and regression models to examine critical variables, including the alignment between academic disciplines and occupational roles, as well as the spatial distribution of graduates across regions. The visualizations produced facilitate data-driven decision-making, enabling enhancements in curriculum design, the advancement of career support services for alumni, and the fortification of ties with industrial stakeholders. Key results reveal a significant positive relationship between graduates' Grade Point Average (GPA) and their income levels, alongside a consistent year-on-year rise in participation rates for tracer studies, with the rate reaching 99.06% by 2022. Furthermore, the findings underscore notable trends in employment sectors and geographic mobility, with 74.58% of alumni employed within Indonesia, predominantly in Riau Province. These outcomes affirm the robustness of the implemented data analysis framework in bolstering policy formulation for educational institutions. Beyond immediate implications, the study highlights the potential of integrating scalable data management systems with advanced visualization tools to address the evolving challenges of alumni tracking and institutional accountability in higher education.
Classification of Apple Ripeness Detection System Using Self-Organizing Map (SOM) Method Tundo; Shindy Apriani; Sugeng
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3734

Abstract

Apple (Malus Domestica) is one of the most popular types of fruit and is in high demand by the public because of its varied flavors. Apples have many nutrients and various vitamins including healthy fats, carbohydrates, proteins, vitamins and many more. The Apple is one of the apple varieties developed in Batu City, Malang and planted in several areas with suitable agroclimates for apple growth. This research uses Anna apple images as datasets. Various ways can be employed to distinguish Anna apples' maturity, including through color image analysis. But to the naked eye, Anna apples are often difficult to distinguish. This research classifies the maturity of Anna apples based on color analysis with the Self-Organizing Map method. Using Google Colab and Python programming language and datasets from kaggle.com as many as 139 datasets, 46% training data, 54% validation data. The Self-Organizing Map method was chosen because of its ability to recognize visual patterns accurately. The accuracy of the results based on the SOM Method performance evaluation metrics namely Quantization Error, Silhouette Score and Topographic Error. Quantization Error RGB (0.004737) is lower than HSV (0.073178) which indicates RGB's ability is effective in representing data in SOM. Silhouette Score HSV (0.704204) is higher than RGB (0.599846) indicating the ability of HSV is slightly better in grouping objects.
Public Sentiment Analysis on the Inauguration of President Prabowo Subianto on Platform X Using the Support Vector Machine (SVM) Algorithm Rosalina Saputri; Sri Lestari
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3787

Abstract

The inauguration of President Prabowo Subianto emerged as a pivotal political event that captured significant public interest and sparked a wide array of reactions across social media, particularly on the X platform (formerly known as Twitter). This research aims to categorize and analyze public sentiment regarding this historic moment by utilizing the Support Vector Machine (SVM) algorithm, a robust machine learning approach for classification tasks. A dataset comprising 1,000 tweets was initially gathered through targeted searches related to the inauguration. Subsequently, the data underwent a rigorous preprocessing phase, which included tokenization to break down text into individual components, stopword removal to eliminate irrelevant terms, filtering to exclude special characters and noise, and Term Frequency-Inverse Document Frequency (TF-IDF) transformation to convert textual data into a numerical format suitable for algorithmic processing. After preprocessing, 909 data points were prepared for further analysis. The dataset was then divided into two subsets: 80% allocated for training the model (727 data points) and 20% reserved for testing its performance (182 data points). The results of sentiment classification indicated that, among the test data, 653 tweets conveyed a positive sentiment toward the inauguration, whereas 74 tweets expressed a negative sentiment. Performance evaluation of the model demonstrated a commendable accuracy rate of 89.82%, alongside a precision of 89.82%, a recall of 100%, and an F1-score of 94.63%. These metrics highlight the model’s strong capability to accurately discern and classify public opinions related to political developments. The elevated recall rate, in particular, signifies the model’s ability to identify all instances of positive sentiment without omission. However, the precision score suggests some room for refinement in reducing misclassifications. The findings underscore the effectiveness of the SVM algorithm in dissecting and interpreting consumer sentiment toward significant political events. This provides a reliable tool for such analyses. Moreover, the outcomes of this study are anticipated to offer a valuable reference point for stakeholders and policymakers in leveraging data-driven approaches to gauge public opinion and monitor economic trends in Indonesia. This research also lays the groundwork for future investigations into sentiment analysis within the digital sphere. This could guide strategic communications and policy formulation based on real-time societal feedback
CapCut Application Model to Boost User Interest in Vehicle Rental Promotions Muhammad Z. Amany; Syarif Hidayat
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3811

Abstract

In the current digital era, social media platforms such as TikTok and Instagram Reels play a crucial role in influencing consumer decisions. This abstract presents a model for leveraging the CapCut application to enhance user interest in car rental promotions through creative video content. The model focuses on producing engaging promotional videos that showcase various cars in captivating contexts, such as casual trips, city adventures, and special events. By utilizing the editing features available in CapCut, users can generate high-quality videos that highlight the benefits of car rental services, including flexibility, affordability, and unique experiences. The study's findings indicate that employing the CapCut application in creating car rental promotional content can significantly boost engagement levels. Creatively edited videos capture users' attention, with an average increase in interactions (likes, shares, comments) of 90% compared to unedited content.
Comparison of Classification of Songket Fabric Types Using AlexNet and VGG19 (Visual Geometry Group) Method Sri Lestari; Nida Apipah
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3815

Abstract

This study aims to evaluate and compare the performance between deep learning models AlexNet and VGG19 in Songket fabric classification. Due to its complex patterns and subtle differences, Songket classification must be accurate. The datasets in this study are various types of Songket images and all datasets are classified by type for easy analysis. After intensive learning and evaluation, VGG19 is a superior classifier than AlexNet. The highest performance is achieved by the VGG19 method in terms of performance measure accuracy, precision, recall, and F1 score, which may be due to the increase in depth and better extraction of some detailed visual features from complex images. Although these results have substantial practical implications, some issues need to be further discussed before optimizing the results. Hyperparameters, such as learning rate or batch size, can be changed to optimize the speed and accuracy of the model. In addition, the diversity of the data should be increased by using data augmentation techniques to ensure that the model generalization to market conditions is possible. More complex additions (lighting changes, texture distortion simulation, or others) can also contribute to improving the robustness of the trained model to these disturbances. The conclusion of the research is the importance of improving the accuracy and usefulness of single fabric classification. This will result in its application in heritage preservation and textile development.
Interactive Learning Media for Mastering Lampung Language Vocabulary in 4th-5th Grade Elementary School Using the ADDIE Model Haryuning Tias; Usep Saprudin
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3854

Abstract

The teaching of the Lampung language at the elementary school level continues to encounter significant obstacles, particularly the limited ability of students to master vocabulary due to teaching methods that lack dynamism and interactivity. This research aims to develop an interactive learning media application to enhance the daily vocabulary proficiency in the Lampung language among fourth and fifth-grade students at SD Negeri 1 Surabaya Udik. The application was developed using the ADDIE model, which encompasses five key stages—analysis, design, development, implementation, and evaluation—as a framework for instructional system design. It incorporates interactive features such as learning materials, educational videos, quizzes, and digital exercises, accessible across various devices. Findings reveal that the use of this interactive learning application significantly boosts students’ engagement and enthusiasm for learning the Lampung language, while also facilitating a more effective grasp of vocabulary. The application’s impact was assessed through a pre-test and post-test method applied to fourth and fifth-grade students, demonstrating a marked improvement in vocabulary mastery compared to traditional teaching approaches. This study adopts a quasi-experimental approach with a pre-test and post-test design without a comparison group, testing students before and after using the application. The application is anticipated to serve as a novel solution in supporting the preservation of regional languages through a technology-driven learning strategy.
IoT-Based Plant Irrigation System in the Setu Babakan Tourism Area Landscape Waskita Cahya; Filda Angellia; Yuli Prasetya; M. Febriansyah
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3871

Abstract

Sustainability of green landscape management in the Setu Babakan tourism and recreation area is threatened by low-efficiency water use and a suboptimal system of plant care. In the age of the internet, the Internet of Things (IoT) presents us with a modern solution to a manual watering system. This study focuses on developing and deploying an IoT-supported plant watering system to create an environmentally-friendly and scenic view of tourist attractions. The device has a sprinkler head, an ESP32 microcontroller and a soil moisture probe to monitor soil condition. The collected information is sent to a server through MQTT. The data is presented on a web platform that can be accessed from a computer and smartphone. This research methodology includes hardware, software, and field testing developments. The findings show that when the soil is dry, the system can automate plant watering and control soil moisture quality, saving labor. Low investment, flexible construction, high efficiency. This system can improve landscape management efficiency, but also promote the sustainable development of tourist destinations. The importance of this subject in relation to environmental protection and the modern means and methods of environmental protection technology is obvious. The originality of this work is that an IoT-based watering system in the Setu Babakan tourist area could increase 35% of water use efficiency compared to conventional watering (control), p < 0.05 (statistically significant difference), which indicates that this IoT-based watering system could make resource and plant health conservation in the Setu Babakan area.

Page 35 of 39 | Total Record : 387

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