cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Muhammad Wali
Contact Email
muhammadwali@amikindonesia.ac.id
Phone
+6285277777449
Journal Mail Official
ijsecs@lembagakita.org
Editorial Address
Jl. Teuku Nyak Arief No. 7b 23112, Kota Banda Aceh, Banda Aceh, Provinsi Aceh
Location
,
INDONESIA
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
 32   33   34   35   36 
Sentiment Analysis of the TikTok Tokopedia Seller Center Application Using Support Vector Machine (SVM) and Naive Bayes Algorithms Faddilla Aulia Dara; Irfan Pratama
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.v5i1.3463

Abstract

The TikTok Tokopedia Seller Center application is a collaboration between TikTok and Tokopedia designed to help sellers manage their stores and boost sales. Despite offering various features, complaints about poor user experience often appear in reviews on the Google Play Store. This study aims to analyze user sentiment towards the TikTok Tokopedia Seller Center application using a dataset of 2,000 reviews, using the Support Vector Machine (SVM) and Naive Bayes algorithms to classify positive, negative, and neutral sentiments. In addition, this study also attempts to compare the effectiveness of these algorithms in sentiment analysis and evaluate the performance of two weighting methods: TF-IDF and Term Presence. The dataset used was taken by scraping review data on the Google Play Store in Python, as many as 2000 user review datasets. This study found 1,171 negative sentiments, 735 positive sentiments, and 94 neutral sentiments. The results showed that the accuracy of SVM (0.81 and 0.78) was higher than Naive Bayes (0.69 and 0.75). It is hoped that this research can help potential users to find user sentiment towards the application and provide valuable information for application developers to understand user needs and expectations so that developers can improve application features more appropriately and effectively
Sentiment Analysis of Public Comments on YouTube Regarding the Inaugural Speech of the 8th President of Indonesia Using VADER and BERT Methods Alwi Ahmad Bastian; Andreas Perdana
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.v5i1.3472

Abstract

The research examines public reactions toward President Prabowo Subianto first presidential address in 2024 by studying YouTube comment sentiments. By utilizing sentiment analysis methods, this research combines two main approaches: The research combines VADER (Valence Aware Dictionary and Sentiment Reasoner) for initial sentiment labeling through predefined dictionary categories with BERT (Bidirectional Encoder Representations from Transformers) for more advanced classification. The dataset contains 10,306 comments which display a range of public opinions. Positive sentiment represents 4,943 comments which make up 49.26% of the total while neutral sentiment accounts for 4,336 comments at 43.21% and negative sentiment represents 756 comments at 7.53%. The BERT model reached an accuracy level of 97.01% which illustrates its capability to process contextual details and subtle data elements. VADER delivers rapid preliminary labeling results and BERT improves classification precision through its analysis of complex contexts. The study reveals how people perceive the new government while providing chances for creating public opinion monitoring techniques for social and political topics. Researchers, academics, and policymakers will find these findings valuable for comprehending public opinion dynamics during the digital age's continuous evolution
Data Visualization of Kemplang Sales Using Looker Studio at Arion Souvenir Shop Yuda Restu Fauzi; Budi Sutomo
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.v5i1.3486

Abstract

Arion Souvenir Shop, located in Metro City, offers grilled kemplang snacks, a traditional Indonesian delicacy. The shop encounters several challenges, including the difficulty in revealing actual monthly sales trends, identifying the most popular kemplang variants, and detecting the annual sales cycle. Grilled kemplang is available in three variants: jumbo, medium, and small. To address these challenges, this study visualizes kemplang sales data for the years 2022–2024 using Google Looker Studio. The visualization includes various graphical formats such as bar charts, pie charts, pivot tables, and line charts. The results of the analysis show that sales were consistently highest in January across the three years, indicating a strong seasonal trend. Additionally, the small kemplang variant emerged as the most popular choice, consistently outperforming the other variants in monthly sales. The study also observed a slight decline in overall sales over the three-year period. This research contributes significantly to the analysis of local product sales data by leveraging Looker Studio for interactive trend visualization. It provides practical recommendations for local business owners and empirical evidence on the application of data visualization tools in strategic decision-making. The insights gained from this study can help businesses optimize their sales strategies, improve inventory management, and enhance customer engagement
Analysis Acceptance of XYZ Company Digital Membership Using Technology Acceptance Model Skynyrd; Suwarno
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.v5i1.3496

Abstract

The current study explores the acceptance of XYZ Company’s digital membership program in the light of the Technology Acceptance Model (TAM). The objective is to find some key values that predict user adoption, focusing mainly on the predictors of Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) in behavioral intention (BI). Data was collected from 378 respondents and Structural Equation Modeling (SEM) was used on the data obtained. The data provides evidence for the significant effects of PU and PEOU on BI as expected, underlining how important these constructions are to influence user acceptance. The study extends the TAM with other variables such as Trust, data privacy, and user experience (UX) to provide a broader understanding. These variables are important, especially in the case of a digital membership program operated by a company, for the technological requirements that need to satisfy multiple customers and match those needs with industry constraints. The study findings reveal a significant mediating effect of UX on the relationship between PEOU and PU, as well as a moderating impact of trust and data privacy on the relationship between PEOU and PU, which in turn creates a more satisfying level of assurance and satisfaction. While the findings inform, in a very specific way what Company XYZ can do from a management perspective to improve the user experience and enhance the benefits of its digital membership program and user adoption/engagement. In line with the academic literature, this study places TAM into the context of corporate digital membership offering relevant knowledge and practical recommendations for organizations to replicate similar initiatives. The strategic implications of these results demonstrate the importance for companies to design their digital solutions according to user expectations and needs, to consistently deliver optimal customer value and satisfaction in a highly competitive sales environment.
Forecasting Chili Prices in Metro City Using Long Short-Term Memory (LSTM) Gusti Made Gunadi; Andreas Perdana
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.v5i1.3526

Abstract

Cayenne pepper is one of the important commodities in the staple market in Indonesia which has a vital role in people's daily lives. Fluctuations in the price of cayenne pepper are often a challenge that impacts farmers and consumers, causing uncertainty in production and distribution planning. This research aims to develop a cayenne pepper price prediction model using the Long Short-Term Memory (LSTM) method, utilizing historical data from the data.metrokota.go.id portal for the period October 2023 to October 2024. By using LSTM, this model successfully captures long-term patterns in cayenne price data, with a Final Validation Loss of 0.00249 which indicates a high level of accuracy. The prediction results are expected to help farmers determine the optimal selling time, traders in managing stocks efficiently, and policy makers in formulating strategies to mitigate the impact of price fluctuations. In addition, this study highlights practical implications for stabilizing commodity markets, particularly in Metro City, as well as the relevance of these findings to be applied to other agricultural commodities.
Utilizing IoT Technology for Soil Moisture Management through Integration of pH and Moisture Sensors in an Android Application for Rice Farming Budi Sutomo; Tri Aristi Saputri; Ilham Wahyu Satria
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.v5i1.3538

Abstract

In this study, to help address the challenges involved in rice production (especially optimizing soil and crops in dryland areas that are prone to water scarcity and variable soil pH), we leveraged IoT technology. An IoT soil moisture and pH monitoring system to track soil moisture status in real time using ESP8266 microcontroller along with dedicated sensors coupled with Blynk as a user interface. The system provides instant alerts to farmers on mobile devices about irrigation and soil pH modifications, thereby minimizing the direct dependence on time-consuming maintenance of vegetation monitoring. The results from a trial of 28 upland rice plots in dryland agricultural areas showed that the irrigation alert system provided timely irrigation alerts, improved water use efficiency by up to 30% and increased yield by 15–20% compared to conventional techniques. The significance of these findings in terms of practical applications are water resource management, optimal soil conditions for rice farming and to promote sustainable agricultural practices on the other hand. Furthermore, the system can be applied to other crops in a similar manner to enhance food security at national and local scales despite climate change and resource constraints.
Forecasting New Student Admissions at Muhammadiyah Elementary School Metro Using the Weighted Moving Average Method Clara Tintan Melati; Budi Sutomo
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.v5i1.3541

Abstract

SD Muhammadiyah Metro Lampung was established in 1968 with the Decree of the Muhammadiyah Education, Teaching, and Culture Council Number 664/I-057/LP-68/1977. Since then, this institution has emphasized the importance of providing quality education and creating an environment that supports the development of students. The purpose of this study is to predict the acceptance of new students in the coming period, so that it can be the basis for compiling a more appropriate educational planning strategy that is in accordance with real needs. To realize all of this, the main analysis tool is the Weighted Moving Average (WMA). This method is different from other modeling methods such as exponential smoothing and ARIMA because this method provides greater weight based on current data, so that estimates are more sensitive to current trends and more credible as a decision-making tool. The results of the WMA forecast provide schools with the opportunity to estimate the need for resources needed (including teaching staff, supporting facilities, and classroom allocation) to ensure that the education process is running well and correctly. In addition, this technique is a way to assess developing or abolishing admission policies. However, forecasts are only as good as historical data and cannot predict the presence of external factors that affect outcomes
Android-Based Inventory System for Sitayu Paint Shop to Optimize Goods Management Muhamad Alda; Silvi Indryani; Diah Ayu Rina Sari; Tasya syalsabilla; Maulidya Putri Kinanti Ritonga
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.v5i1.3584

Abstract

The Android-based Paint Shop Inventory Information System was developed to overcome the challenges of managing stock in Sitayu Paint more accurately, efficiently, and organized. This research aims to optimize the process of recording, monitoring, and inventory administration through a mobile application that can be accessed at any time. Using the waterfall development method, this research includes the stages of needs analysis, system design, implementation, verification, and maintenance. The app offers a variety of key features such as minimum stock notifications to prevent stockouts, integrated sales reports, and simple data analysis to support strategic decision-making. The system allows store staff to monitor and update inventory data in real-time, providing high flexibility in daily operations. The implementation results show that the application is able to reduce the risk of recording errors to speed up the work process. and improve time efficiency in inventory management. In addition, this system supports management in developing business strategies based on more organized and relevant data. With the application of this digital technology, Sitayu Paint has succeeded in increasing customer satisfaction through guaranteed product availability and more professional operations. This research makes a significant contribution to modern inventory management in the retail sector, especially paint shops, with the potential for development for the integration of further features such as stock demand prediction
Optimization of Energy Efficiency and Hatchability Rates in IoT-Based Egg Incubators Muhammad Ferdiansyah; Lika Mariya; Siti Kholifah K
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.v5i1.3633

Abstract

This study aims to develop an Internet of Things (IoT)-based egg incubator integrated with renewable energy to enhance operational efficiency and hatching success rates. The system utilizes an ESP32 microcontroller to regulate temperature and humidity automatically, with a 100 Wp solar panel as the primary energy source. Testing results demonstrate that the IoT-based system maintains optimal temperature and humidity levels more effectively than conventional systems, achieving a 92% hatching success rate, which surpasses the 85% success rate of traditional incubators. Additionally, the integration of solar panels reduces dependency on conventional electricity and lowers operational costs by 30%, making it a more energy-efficient and sustainable solution. These findings highlight the potential of combining IoT automation and renewable energy to improve production efficiency, reduce costs, and support sustainable livestock management. The success of this system paves the way for further advancements in IoT and renewable energy applications in the agricultural sector, with potential scalability for both small-scale farmers and large-scale poultry industries, fostering digital transformation in more efficient and eco-friendly food production.
Digital Promotion Strategy for SMEs Using Motion Graphics: A Case Study of Metro Snack Anis Kholif Meilani; Ada Udi Firmansyah
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.v5i1.3636

Abstract

Metro Snack is a micro, small, and medium enterprise (MSME) engaged in the production of banana chips, a signature souvenir from Lampung. Amid the rise of the digital era, the demand for creative and innovative promotional tools has become crucial for broadening market reach and enhancing competitive edge. This research seeks to develop animation-based promotional material employing motion graphics techniques through the Multimedia Development Life Cycle (MDLC) framework, encompassing stages such as concept formulation, design, material gathering, production, testing, and distribution. The development process utilized software including Canva for crafting visual components like logos and preliminary designs. It also used FlipaClip for creating 2D animations depicting banana chip production stages, and CapCut for video editing, incorporating visual effects, music, and narration. The outcome is a 1-minute 32-second promotional video that effectively showcases the unique strengths of Metro Snack’s products in an engaging and clear manner. This video has been uploaded to Instagram (@metro_snack_) with plans for expansion to other digital platforms. Findings indicate that motion graphics-based promotional videos boost brand awareness by up to 30% within the first month following distribution, as evidenced by social media engagement metrics such as likes and comments. This study aims to serve as a reference for other MSMEs in leveraging digital marketing strategies to strengthen competitiveness and drive sales growth.

Page 34 of 39 | Total Record : 387

 32   33   34   35   36 

Filter by Year

2021 2025


Reset
Filter By Issues
All Issue Vol. 5 No. 3 (2025): DECEMBER 2025 Vol. 5 No. 2 (2025): AUGUST 2025 Vol. 5 No. 1 (2025): APRIL 2025 Vol. 4 No. 3 (2024): DECEMBER 2024 Vol. 4 No. 2 (2024): AUGUST 2024 Vol. 4 No. 1 (2024): APRIL 2024 Vol. 3 No. 3 (2023): DECEMBER 2023 Vol. 3 No. 2 (2023): AUGUST 2023 Vol. 3 No. 1 (2023): APRIL 2023 Vol. 2 No. 2 (2022): OCTOBER 2022 Vol. 2 No. 1 (2022): MAY 2022 Vol. 1 No. 2 (2021): AUGUST 2021 Vol. 1 No. 1 (2021): APRIL 2021 More Issue