Article Per Year (5 Year)
p-Index From 2021 - 2026
3.087
P-Index
This Author published in this journals
All Journal Foristek International Journal of Advances in Intelligent Informatics JOURNAL OF APPLIED INFORMATICS AND COMPUTING Paedagoria : Jurnal Kajian, Penelitian dan Pengembangan Kependidikan JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) CCIT (Creative Communication and Innovative Technology) Journal EDUMATIC: Jurnal Pendidikan Informatika IAIC Transactions on Sustainable Digital Innovation (ITSDI) Innovative: Journal Of Social Science Research The Indonesian Journal of Computer Science SISFOTENIKA Bomba: Jurnal Pembangunan Daerah
Septiano Anggun Pratama
Universitas Tadulako
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Public Health Social Sciences Transportation Veterinary Other

Published : 22 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : CCIT (Creative Communication and Innovative Technology) Journal

 1 
Business Process Analysis in the Financial System of PT. Oti Eya Abadi With Business Process Modelling and Notation (BPMN) Method Hanama, Ikhsan Wahyudin; Pratama, Septiano Anggun; Joefrie, Yuri Yudhaswana; Lapatta, Nouval Trezandy
CCIT (Creative Communication and Innovative Technology) Journal Vol 18 No 2 (2025): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/ccit.v18i1.3487

Abstract

Every company certainly needs an information system for ease of work management in a company organization. As in the problems faced by the company PT. Oti Eya Abadi who needs an information system that can create and print company cash as efficiently as possible so that leaders and employees who manage the company's financial cash do not make manual formats in excel anymore and obtain cash data formats automatically from the information system. In order to achieve a sequential but still efficient system flow in the use of information systems, an analysis is made related to the business process flow of the information system with a description in the form of Business Process Modelling and Notation (BPMN). By describing BPMN, the creation of an information system can be made more directed in each access feature so that when the information system is completed it can be used with access that is easier for users to understand and more efficient in using an information system, including the financial information system of PT. Oti Eya Abadi.
CNN Algorithm for Herbal Leaf Classification Using MobileNetV2 and ResNet50V2 Pagiu, Harry T.; Kasim, Anita Ahmad; Lapatta, Nouval Trezandy; Pratama, Septiano Anggun; Laila, Rahma
CCIT (Creative Communication and Innovative Technology) Journal Vol 18 No 2 (2025): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/ccit.v18i2.3776

Abstract

Indonesia is home to over 30,000 types of herbal plants, with approximately 1,200 species utilized as raw materials for alternative and traditional medicine. Leaves play a crucial role in herbal medicine preparation. However, many people struggle to identify different herbal leaves due to their similar appearances, making classification difficult. Each leaf possesses unique characteristics such as shape, size, midrib, stalk, blade, and type, which can be used for differentiation. To assist in identifying herbal leaves, a classification system based on image recognition is essential. Convolutional Neural Networks (CNN) are deep learning algorithms designed for processing two-dimensional image data. Model performance can be enhanced through transfer learning, with MobileNetV2 and ResNet50V2 being widely used architectures. These pretrained models have been trained to recognize images with high accuracy. This study focuses on classifying herbal plants based on leaf shape using CNN architectures from MobileNetV2 and ResNet50V2. The evaluation results show that the MobileNetV2 architecture, with a 90%:10% data split, achieved an accuracy of 98.51%, precision of 98.92%, recall of 98.51%, and an F1-score of 98.56%. These findings indicate that CNN with transfer learning can effectively classify herbal leaves with high accuracy.
Co-Authors Ain, Moch. Zukhruf Anita Ahmad Kasim Ar Lamasitudju, Chairunnisa AR. Lamasitudju, Charunnisa Ardiyansyah, Rizka Arsita, Tiara Juli Chairunnisa Ar. Lamasitudju Deny Wiria Nugraha Dwi Shinta Angreni Fahmil, Fahmil Faldiansyah, Faldiansyah Hanama, Ikhsan Wahyudin Iskandar Iskandar Komang, Gusti Laila, Rahma Manoppo, Maryam Mohammad Yazdi Pusadan Muhammad Akbar Nanda, Rifqi Nouval Trezandy Lapatta Nurasyah Dewi Napitupulu Pagiu, Harry T. Putri, Fadiah Suryani Rahmah Laila Reinaldy Mansa, Jeremy Rifki, Moh Rini Septiani Rinianty, Rinianty Rizka Ardiansyah Ryfial Azhar, Ryfial Ryka Marina Walanda Saleh, Muhammad Taufik Sasuwuk, James Rio Siddiq Assegaf, Djafar Siti Fitriana Syahrullah Syahrullah Syaiful Hendra Ulhak, Muhamad Zia Wahyu Setiawan Wawagalang, A. Nolly Sandra Wirdayanti Yuri Yudhaswana Joefrie Yusuf Anshori