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Jurnal Informatika: Jurnal Pengembangan IT
Published by Politeknik Harapan Bersama Tegal
ISSN : 24775126     EISSN : 25489356     DOI : https://doi.org/10.30591
Core Subject : Science,
Computer Science & IT
The scope encompasses the Informatics Engineering, Computer Engineering and information Systems., but not limited to, the following scope: 1. Information Systems Information management e-Government E-business and e-Commerce Spatial Information Systems Geographical Information Systems IT Governance and Audits IT Service Management IT Project Management Information System Development Research Methods of Information Systems Software Quality Assurance 2. Computer Engineering Intelligent Systems Network Protocol and Management Robotic Computer Security Information Security and Privacy Information Forensics Network Security Protection Systems 3. Informatics Engineering Software Engineering Soft Computing Data Mining Information Retrieval Multimedia Technology Mobile Computing Artificial Intelligence Games Programming Computer Vision Image Processing, Embedded System Augmented/ Virtual Reality Image Processing Speech Recognition
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 13 Documents
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Search results for , issue "Vol 9, No 3 (2024)" : 13 Documents clear
Teknologi Computer Vision untuk melakukan Deteksi dan Penentuan Kualitas Bibit Ayam Day Old Chicks Syaddam, Syaddam; Soeksin, Sasando Dewi; Nizar, Raihan
Jurnal Informatika: Jurnal Pengembangan IT Vol 9, No 3 (2024)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v9i3.7923

Abstract

This research is motivated by the importance of chicken animal protein for child growth, development, immunity, intelligence, and the prevention of stunting. This research aims to design and implement an object detection system using a series of 4 nodes, namely Raspberry Pi, ESP32-CAM, Arduino, and ESP32, to identify chickens based on their physical characteristics. This research utilizes computer vision and artificial intelligence methodology, particularly the Convolutional Neural Network approach, to detect characteristics of DOC chickens, such as feathers, eyes, and legs. The implementation results show that the object detection system built using these four nodes can detect objects according to the existing labels. This system can identify DOC chickens with characteristics such as clean feathers, bright eyes, and bright and undamaged legs. Testing was conducted under various movement conditions of the detection objects, and the results show that the system can work well in recognizing the target objects. In the trial section, the objects used were chickens that fit the DOC characteristic category. The trial results show that the built object detection system can detect DOC chickens with suitable physical characteristics. This can assist farmers in selecting and cultivating quality chickens. Five trial tests were conducted, which showed varying detection performance.
Analisis Sentimen Twitter Terhadap Pemindahan Ibu Kota Negara Menggunakan Support Vector Machine Saputri, Gita Aprinda; Alita, Debby
Jurnal Informatika: Jurnal Pengembangan IT Vol 9, No 3 (2024)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v9i3.6612

Abstract

The Indonesian government announced plans to move the capital from Jakarta to East Kalimantan due to the high population burden and economic contribution on the island of Java. Statistical data shows that the island of Java has a large population, reaching 151.59 million people or around 56.10% of the total population of Indonesia, and will provide a large participation in national GDP in 2021. Moving the capital city is seen as a step. . for the sake of equal distribution of population and economy throughout Indonesia. Rapid urbanization on the island of Java, especially in the buffer areas of the capital city of Jakarta, is one of the main reasons behind this decision. This research uses data from the social media platform Twitter to analyze sentiment using 2 categories, namely positive and negative sentiment regarding the relocation of the National Capital, analyzed using the Support Vector Machine method. In this study, the SVM kernel type was used, namely a linear kernel with an accuracy of 92.70%, then improved with Stratified k-Fold Cross Validation, getting 100% accuracy in iterations 1 and 5. The classification results using the Support Vector Machine method are statedthat the linear kernel has better accuracy. This sentiment analysis provides insight into the public's views on the proposed measure. This research can be used as material for consideration of future government policy regarding relocating the capital city.
E-learning Academy Untuk Meningkatkan Kapasitas SDM Di Lingkungan Perusahaan Transportasi X Andarsyah, Roni; Prianto, Cahyo
Jurnal Informatika: Jurnal Pengembangan IT Vol 9, No 3 (2024)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v9i3.7835

Abstract

 Services in the field of land transportation services are still a sector needed by the community for mobility and economic growth. The main problem faced by Transportation Company X in developing human resources (HR) is the uneven skills and knowledge between generations in the organizational structure. Gen X dominates with 57.36%, Gen Y (38.34%) and Gen Z (4.29%). This has an impact on the ability to adapt to the demands of the modern transportation industry. This research aims to develop and implement an e-Learning Academy, to increase the capacity of X Transportation Company's human resources. This research methodology uses SCRUM framework in learning system development, with agile approach that allows adaptation to changes quickly and efficiently. E-Learning Academy features video-based learning and interactive elements that allow employees to learn independently, thus maximizing knowledge transfer and improving skills in various fields. Survey results after testing by users through user acceptance test activities show that on the Ease of Navigation aspect, 55% of respondents stated “strongly agree” the application is easy to use”. The aspect of Confidence in Application Capabilities, the results are 55% of respondents “strongly agree” this application believes it can improve HR skills and abilities. For the Quality of Main Features, 36% of respondents stated “strongly agree” the main features in this application are easy to use and the remaining 64% stated “agree”. On the aspect of Impact on HR Improvement, 46% of respondents “strongly agree” this application has a positive impact and the remaining 54% of respondents stated “agree”. Finally, on the aspect of Benefit for the Company, 36% of respondents “strongly agree” that this application is useful and the remaining 64% stated “agree”. This platform can be accessed across all business sectors so that it becomes a strategic tool that helps Transportation Company X achieve its goals and improve its public transportation services.

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