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IJID (International Journal on Informatics for Development)
Published by Universitas Islam Negeri Sunan Kalijaga Yogyakarta
ISSN : 22527834     EISSN : 25497448     DOI : -
Core Subject : Science,
Computer Science & IT
One important point in the accreditation of higher education study programs is the availability of a journal that holds the results of research of many investigators. Since the year 2012, Informatics Department has English language. Journal called IJID International Journal on Informatics for Development. IJID Issues accommodate a variety of issues, the latest from the world of science and technology. One of the requirements of a quality journal if the journal is said to focus on one area of science and sustainability of IJID. We accept the scientific literature from the readers. And hopefully these journals can be useful for the development of IT in the world. Informatics Department Faculty of Science and Technology State Islamic University Sunan Kalijaga.
Arjuna Subject : -
Articles 5 Documents
 1 
Search results for , issue "Vol. 13 No. 1 (2024): IJID June" : 5 Documents clear
Design of a Web-Based E-Commerce Sales System for the Economic Empowerment of Tambak Fish Farmers Siburian, Dian Prima Trendi; Hartiyani, Selvi Dwi; Wicaksono, Ardy; Gustina, Sapriani
IJID (International Journal on Informatics for Development) Vol. 13 No. 1 (2024): IJID June
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2024.4440

Abstract

This research addresses the economic challenges of fish farmers in Argomulyo Village, Cangkringan District, by developing a web-based e-commerce sales system. The primary issue identified is the limited market access experienced by these farmers. To address this, the study employs a qualitative research methodology using the Waterfall software development model and gathers data through observation, interviews, literature reviews, and questionnaires. The e-commerce platform aims to enhance economic opportunities for local fish farmers by providing a digital marketplace to overcome limited market access. Quantitative data was collected from 15 respondents using a questionnaire with 10 statements to evaluate the system. The analysis results show that the validity test (R Calculated > R Table) confirms all statements are valid, and reliability is tested with a Cronbach's Alpha of 0.958, exceeding the reference value of 0.6, indicating high reliability. The e-commerce system has proven effective in broadening market reach, boosting sales, and increasing farmers' income. The study results highlight the e-commerce system's positive impact on fish farmers' economic empowerment, demonstrating its potential to foster sustainable growth and market expansion in the digital era. This research provides valuable insights into the use of technology to enhance and advance the lives of farmers in rural communities.
Analysis of Public Sentiment Towards POLRI's Performance using Naive Bayes and K-Nearest Neighbors Handika, Yusuf; Hanif, Isa Faqihuddin; Hasan, Firman Noor
IJID (International Journal on Informatics for Development) Vol. 13 No. 1 (2024): IJID June
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2024.4500

Abstract

Using Twitter as a platform for sharing information includes tracking public perceptions of the performance of the Indonesian National Police (POLRI). Public sentiment assists as a gauge for evaluating POLRI's operational capabilities and supports decision-making processes to enhance the organization's reputation. However, raw public opinion data often requires careful analysis for decision-making. Hence, conducting sentiment analysis of Twitter data is crucial. This analytical process involves extracting and classifying opinions into neutral, positive, and negative sentiments. This study employs two distinct sentiment analysis methods: the Naive Bayes algorithm and the K-Nearest Neighbors. Analysis of 1285 tweets reveals prevailing satisfaction with POLRI's performance, indicated by many positive sentiments. However, there is also a notable number of negative feelings. The assessment from confusion matrix results demonstrate that the Naive Bayes algorithm achieves 99.03% accuracy, while the K-Nearest Neighbors algorithm achieves 95.33% accuracy. By leveraging insights from public opinion data, POLRI can make more accurate and timely decisions, enabling it to better fulfill the community's needs and expectations. This strategic use of data enhances service quality and bolsters POLRI's favorable image among the public fosters more harmonious relationships and enhances public trust in law enforcement agencies.
Sentiment Analysis of TIMNAS Indonesia's Participation in the Asian Cup U23 2024 on X Using Naive Bayes and SVM Fathurrohman, Sewin; Afandi, Irfan Ricky; Hasan, Firman Noor
IJID (International Journal on Informatics for Development) Vol. 13 No. 1 (2024): IJID June
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2024.4504

Abstract

This study aims to analyze the sentiment of the Indonesian public regarding the participation of the Indonesian National Team in the 2024 U-23 Asian Cup through the social media platform X. Sentiment analysis is crucial for understanding public perception and its impact on support for the national team. The research methodology involves collecting user comments on X related to the team's performance during the tournament, followed by data cleaning. The dataset is manually labeled, with 80% used as training data for algorithmic model training and the remaining 20% as test data, classified using Naive Bayes and Support Vector Machine algorithms. The analysis results indicate that the SVM algorithm achieves a higher % accuracy rate of 95% compared to Naive Bayes, which achieves 87%. The majority of the 3367 opinions analyzed express positive or satisfactory sentiments towards the national team's participation. However, there are fewer negative sentiments, highlighting areas requiring team management's attention. This study provides valuable insights into public perception of the Indonesian National Team. Furthermore, these findings can inform policymakers and team managers' decision-making to enhance the team's quality and performance in the future.
Development of Geographic Information Systems in Mapping Village-Owned Enterprises in Sleman Regency Ramadhan, Imam; Arfiani, Ika
IJID (International Journal on Informatics for Development) Vol. 13 No. 1 (2024): IJID June
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2024.4513

Abstract

The population increase in the Special Region of Yogyakarta poses challenges, including developing Village-owned Enterprises or BUM Desa in Sleman Regency to enhance rural community welfare. BUM Desa data management currently relies on manual spreadsheets and lacks a dynamic data storage system, hindering access to accurate information. This study employed the Scrum methodology, gathering data through literature reviews, interviews, and observations to assess the current state of BUM Desa. A product backlog guided the development of a web-based GIS application through sprint planning, resulting in an application that maps BUM Desa locations in the Sleman Regency based on coordinates and provides detailed development classifications. This application enhances data management and decision-making for BUM Desa development, simplifies government data management, and improves public access to BUM Desa locations. Black box testing confirmed its functionality, with 100% validity. End-user computing Satisfaction (EUCS) surveys indicated high user satisfaction, emphasizing the application's usability and alignment with user expectations in providing accurate and accessible BUM Desa information.
Comparison of Single Exponential Smoothing and Double Moving Average Algorithms to Forecast Beef Production Tundo; Rachmat Hidayat Insani; Rasiban; Untung Suropati
IJID (International Journal on Informatics for Development) Vol. 13 No. 1 (2024): IJID June
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2024.4663

Abstract

Beef is considered a high-value commodity as it is an important source of protein. Interest in beef continues to rise. Beef production has risen sharply in the past decade, but declined by 7,240.68 tons in 2020 amid coronavirus lockdowns. After that, in 2021, production reached 16,381.81 tons and continued to increase in 2022 and 2023. A precise method is required to forecast beef production. One way to predict beef production in Jakarta is using the Single Exponential Smoothing and Double Moving Average methods. The two algorithms are compared to get the lowest error rate. The methodology used in this research is the SEMMA (Sample, Explore, Modify, Model, and Assess) methodology. According to SAS Institute Inc., there are five stages in developing a system using the SEMMA methodology. After analyzing using MAPE, it is found that the algorithm with the smallest error value is the Single Exponential Smoothing algorithm with a percentage in the monthly period of 16% while for the annual period, it is 27% compared to other algorithms. The forecasting is quite accurate because the MAPE value for each algorithm used has an error of less than 31%.

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