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All Journal International Journal of Electrical and Computer Engineering International Journal of Advances in Applied Sciences Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmiah Informatika Komputer Jurnal Psikologi Jurnal Ilmiah Teknologi dan Rekayasa Prosiding KOMMIT Prosiding PESAT Majalah Ilmiah Matematika Komputer Majalah Ilmiah Ekonomi Komputer TELKOMNIKA (Telecommunication Computing Electronics and Control) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer JUITA : Jurnal Informatika Jurnal Ilmiah KOMPUTASI Sistemasi: Jurnal Sistem Informasi Computatio : Journal of Computer Science and Information Systems Jurnal Ilmiah FIFO Informatika Pertanian JURNAL MANAJEMEN INFORMATIKA (JUMIKA) Prosiding Seminar Nasional Darmajaya Petir JUTEKIN (Jurnal Manajemen Informatika) JURTEKSI Journal of Information System, Applied, Management, Accounting and Research Jurnal Teknik Informatika (JUTIF) International Journal of Management Science and Information Technology (IJMSIT) Jurnal Nasional Teknologi Komputer Formosa Journal of Computer and Information Science Jurnal Sistem Informasi International Journal Multidisciplinary Science
Dewi Agushinta R.
Gunadarma University
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Physics Social Sciences

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Teknologi AI pada Budidaya Vanili Menuju Pertanian Pintar: Review Notonegoro, Radityo Hendratmojo Jati; Rahayu, Dewi Agushinta; Ikasari, Diana; Kosasih, Rifki
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 13 No 2: April 2026
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.132

Abstract

Perkembangan teknologi kecerdasan buatan dan penerapan Deep Learning telah memberikan kemudahan dalam identifikasi objek dengan bantuan mesin. Salah satu pendekatan dalam Deep Learning, yaitu Convolutional Neural Network (CNN), memiliki potensi besar untuk diterapkan di sektor pertanian, khususnya dalam pengelolaan penyakit dan hama pada tanaman. Komoditas vanili pada tahun 2022 mengalami peningkatan permintaan global yang signifikan, namun ekspor vanili Indonesia hanya memenuhi 2,63% dari total ekspor dunia. Salah satu penyebab utama rendahnya ketersediaan vanili adalah serangan penyakit dan hama yang menghambat pertumbuhannya. Penelitian ini bertujuan untuk mengeksplorasi penerapan CNN dalam mengidentifikasi penyakit pada tanaman vanili, yaitu Sclerotium, Fusarium, dan Colletotrichum. Metode yang digunakan adalah pelatihan model CNN untuk mengenali gambar tanaman yang sehat dan yang terinfeksi penyakit. Hasil penelitian menunjukkan bahwa model CNN berhasil mengidentifikasi penyakit dengan akurasi keseluruhan sebesar 71%, mencakup tanaman sehat dan yang terinfeksi penyakit. Temuan ini menunjukkan bahwa teknologi CNN dapat menjadi alat yang efektif dalam mendukung deteksi dini penyakit dan pengelolaan tanaman vanili, serta berpotensi meningkatkan produksi komoditas vanili di Indonesia. Abstract The development of artificial intelligence technology and the application of Deep Learning have made object identification easier with machine assistance. One of the approaches in Deep Learning, namely Convolutional Neural Networks (CNN), holds great potential for application in the agricultural sector, particularly in the management of diseases and pests in plants. In 2022, the global demand for vanilla significantly increased, but Indonesia's vanilla exports only accounted for 2.63% of the world's total vanilla exports. One of the main factors behind the low availability of vanilla is the attack of diseases and pests that hinder its growth. This study aims to explore the application of CNN in identifying diseases in vanilla plants, namely Sclerotium, Fusarium, and Colletotrichum. The method used involves training a CNN model to recognize images of healthy plants and those infected with diseases. The results show that the CNN model successfully identified diseases with an overall accuracy of 71%, including both healthy plants and those affected by disease. These findings suggest that CNN technology can be an effective tool in supporting early disease detection and the management of vanilla plants, with the potential to increase vanilla production in Indonesia.
Analysis of PT PLN (Persero)'s New Installation Waiting List Using the K-Means Clustering Algorithm Ernawati Ernawati; Dewi Agushinta R
Formosa Journal of Computer and Information Science Vol. 5 No. 1 (2026): March 2026
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/fjcis.v5i1.16429

Abstract

This study examines the application of the K-means clustering algorithm to analyze new installation waiting list data obtained from the last three months of 2024. Only entries categorized under new installation requests were selected as the primary dataset. The analysis began by determining the optimal number of clusters: a high volume of new installation waiting lists (C1), a medium volume (C2), and a low volume (C3). Data mining processes were carried out using the RapidMiner tool, producing the following results: 6 UIDs/UIWs were classified into the high cluster (C1), 7 into the medium cluster (C2), and 9 into the low cluster (C3). The clustering performance was subsequently validated using the Davies–Bouldin Index, yielding a final score of 0.486, consistent with the RapidMiner output.
Performance Analysis of the SimInvest Application Programming Interface Using Load Testing Cut Dahri Fajrina El Qahar; Dewi Agushinta Rahayu; Lana Sularto
International Journal of Management Science and Information Technology Vol. 6 No. 1 (2026): January - June 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i1.7215

Abstract

This study evaluates the performance capacity of the SimInvest application programming interface (API), with emphasis on stock transaction and portfolio services that are frequently accessed during peak market activity. The study used an applied performance-testing design through Apache JMeter by simulating concurrent user loads of 100, 500, 1,000, 2,000, and 4,000 users. The observed indicators were response time, transactions per second, and error rate. The findings show that the application remained usable under 100 and 500 concurrent users, with low aggregate error rates of 4.80% and 4.48%, although several history-related endpoints already showed failed requests. When the load reached 1,000 users, the total error rate increased to 53.17%, indicating a clear decline in service reliability. Under 2,000 and 4,000 users, the system recorded error rates of 49.04% and 65.32%, with repeated failures in Account Cash, Cash Withdrawal, Order List, Portfolio, RDN History, RDN Info, and Trade List services. These findings indicate that the present infrastructure requires API optimization, query tuning, server-capacity improvement, load balancing, and real-time monitoring to maintain reliable fintech services during traffic spikes.
Co-Authors -, Hustinawaty Abdollah, Mohd Faizal Achmad Benny Mutiara Adam Huda Nugraha Aditia Arga Pratama Ahmad Hidayat Akbar, Rizky Alif Ahmad Syamsudduha Andi Shahreza Harahap Anggari, Elevanita Anindito Yoga Pratama Anindito Yoga Pratama Anindito Yoga Pratama Anindito Yoga Pratama Antonius Angga Kurniawan Ardhani Reswari Yudistari Armita Widyasuri Aziz, RZ. Abdul Besty Ghina Cut Dahri Fajrina El Qahar Cyntya Widyarsih Delvita Dita Putri Anggrayni Diana Ikasari Diana Tri Susetianigtias Dini Sundani Dyah Pratiwi Emirul Bahar Ernawati Ernawati Ety Sutanty Fajar Nugraha Ferina Ferdianti Fitrianingsih Fitrianingsih Gagah Lanang Ramadhan Grace Desi Geoloni Hafiz Ma'ruf Hanifah Aprilia Nur’aini Haniyah Haniyah Hardianti, Ayu Harya Iswara A.W. Henny Medyawati Henny Medyawati Henri Muel Herry Sussanto Hustinawaty Hustinawaty, Hustinawaty Ihsan Jatnika Ika Setiowati Suprihatin Indira Mahayani Irianto Irianto Irwan Bastian Jhordy Wong Johanna Sindya Widjaya Jonathan Hindharta Khoirul Islam Lana Sularto Lia Ambarwati Lintang Yuniar Banowosari Lintang Yuniar Banowosari M. Abdul Mukhyi Mariono Reksoprodjo Martina Octavia Mega Maralisa Putri Metty Mustikasari Muhammad Edy Supriyadi Murniyati Murniyati Neneng Winarsih Ngakasah, Siti Aliyah Notonegoro, Radityo Hendratmojo Jati Nursanta, Edy Octavia, Martina Paranita Asnur Paujiah, Syifah Putri, Rizka Yulianti Regy Dwi Septian Remi Senjaya Remi Senjaya riamande jelita tambunan Rifki Kosasih Rindani, Fiena Rizka Yulianti Putri Rodiah Rodiah Rr. Dharma Tintri Edi Raras Rustam M. Ali Sandi Agung Sarifuddin Madenda Satria, Agung Sigit Widiarto Soeltan Zaki Sova, Erma Sri Rahayu Puspita Sari Sriyanto, Sriyanto sugrio dwi darmawan Suryadi H. S. Suryadi Harmanto Trihapningsari, Denisha Vega Valentine Yahya Novi Andi Cuhwanto Yoga Yuniadi Yogi Oktopianto Yurista Vipriyanti Yusuf Triyuswoyo Yuti Dewita Arimbi Zuriati, Zuriati