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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Natural Science: Journal of Science and Technology Proceeding International Conference on Information Technology and Business JUITA : Jurnal Informatika CESS (Journal of Computer Engineering, System and Science) International Journal on Livable Space SemanTIK : Teknik Informasi JURNAL ILMIAH MATEMATIKA DAN TERAPAN Jurnal Sisfokom (Sistem Informasi dan Komputer) Technomedia Journal ILKOM Jurnal Ilmiah JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) CCIT (Creative Communication and Innovative Technology) Journal Indonesian Journal of Electrical Engineering and Computer Science Advance Sustainable Science, Engineering and Technology (ASSET) International Journal on Livable Space Applied Engineering and Technology Teknomatika: Jurnal Informatika dan Komputer Tadulako Science and Technology Journal Sasambo: Jurnal Abdimas (Journal of Community Service)
Anita Ahmad Kasim
Jurusan Teknologi Informasi, Fakultas Teknik, Universitas Tadulako Palu
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Social Sciences Other

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Journal : CCIT (Creative Communication and Innovative Technology) Journal

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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.
Evaluating IT Service Capability of Palu BPS Website Using COBIT 5 Framework Ningsih, Alief Surya; Lapatta, Nouval Trezandy; Laila, Rahmah; Kasim, Anita Ahmad; Joefrie, Yuri Yudhaswana; Anshori, Yusuf
CCIT (Creative Communication and Innovative Technology) Journal Vol 19 No 1 (2026): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/ccit.v19i1.3909

Abstract

This research assesses the IT service capability of the official website of the Palu City Central Bureau of Statistics (BPS) by applying the COBIT 5 framework. The assessment is centered on four key processes from the Deliver, Service, and Support (DSS) as well as Monitor, Evaluate, and Assess (MEA) domains—namely DSS01 (Manage Operations), DSS02 (Manage Service Requests and Incidents), DSS06 (Manage Business Process Controls), and MEA01 (Monitor, Evaluate, and Assess Performance and Conformance). Data were collected through structured interviews, observation sessions with website administrators, and an analysis of supporting documents to determine the current capability levels and compare them with the desired target level of 3. The results show that DSS01 and MEA01 have reached capability level 2, indicating that the processes are defined but not consistently standardized. Meanwhile, DSS02 and DSS06 remain at level 1, indicating reactive operations with limited documentation. The average capability level of 1.5 suggests that there is room for significant improvement in terms of documentation, process formalization, and the use of enabling technologies. Based on these findings, this study recommends targeted improvements to enhance the overall performance and reliability of digital public services, as well as to support better IT governance and e-government practices.
Co-Authors A.A. Ketut Agung Cahyawan W Agus Harjoko Aimar Anand Amriana Amriana Amriana Amriana Anisa Yulandari Anita Bakri, Muhammad Bakri Deni Luvi Jayanto Dwi Shinta Angreni Elyana Aulia Chandra Fachrozi, Ahmad Hajra Rasmita Ngemba Hardianti Hardianti, Hardianti Hendriyanto Nofri Imbang I Wayan Sudarsana Irwan Mahmudi Istinganatul Nguluwiyah Kasaedja, Tafania Natalia Laila, Rahma Lamasitudju, Chairunnisa Maghfirat Maghfirat Maghfirat, Maghfirat Mohammad Yazdi Pusadan Muhammad Bakri MUHAMMAD BAKRI Mutia Ningsih, Alief Surya Nouval Trezandy Lapatta Noviana Noviana Nuraedah Pagiu, Harry T. Putra, Ryan Adi Rahmah Laila Rahmawati Rahmawati Raziyan Dwi Pathan Rizka Ardiansyah Ryfial Azhar, Ryfial Sabarudin Saputra Selvy Musdalifah Septiano Anggun Pratama Sri Khaerawati Nur Syahrullah Syahrullah Syahrullah Syaiful Hendra Therry, Alvin Christian Davidson Timbang, Gator Uswary, Jonathan Albert Uyun Mubarak , Siti Wirdayanti Yuri Yudhaswana Joefrie Yusuf Anshori Zulnabil Zulnabil