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All Journal Jurnal sistem informasi, Teknologi informasi dan komputer Jurnal Pendidikan Informatika dan Sains Tadarus: Jurnal Pendidikan Islam Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Teknoinfo Tibuana : Journal of Applied Industrial Engineering JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Mantik Jurnal Tekinkom (Teknik Informasi dan Komputer) Infotek : Jurnal Informatika dan Teknologi Academia Open Jurnal Abdimas ADPI Sains dan Teknologi Jurnal Abdimas Bina Bangsa PELS (Procedia of Engineering and Life Science) Jurnal Sistem Informasi Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Jurnal Informatika Polinema (JIP) Indonesian Journal of Applied Technology Kanigara Journal of Technology and System Information Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Journal of Information Technology Smatika Jurnal : STIKI Informatika Jurnal
Ika Ratna Indra Astutik
Universitas Muhammadiyah Sidoarjo
Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation Other

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Identifikasi Penyakit Daun Durian Menggunakan Penerapan Algoritma Residual Network (RESNET-50) Ramadhan, Arga Satria; Rahmawati, Yunianita; Indra Astutik, Ika ratna; Sumarno
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 2 (2025): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v8i2.30293

Abstract

Durian is one of Indonesia’s leading horticultural commodities, but its productivity can decline due to leaf diseases that are difficult for farmers to identify visually. This study aims to develop an automated durian leaf disease classification system using a deep learning algorithm based on the ResNet-50 architecture. The dataset consists of 420 durian leaf images classified into four categories: Algal Leaf Spot, Leaf Blight, Leaf Spot, and No Disease, collected from the Roboflow platform. Preprocessing steps included annotation, augmentation, and resizing the images to 240x240 pixels.The model was trained using TensorFlow with pretrained ImageNet weights. Three data split scenarios (70:20:10, 75:15:10, and 80:10:10) were applied using both binary and multiclass classification approaches. Model performance was evaluated using confusion matrix and metrics such as accuracy, precision, recall, and F1-score. The best binary classification result achieved 99.8% accuracy and 99.9% F1-score, while the best multiclass result achieved 99.6% accuracy and 96.9% macro F1-score. These results demonstrate that ResNet-50 is effective in accurately detecting durian leaf diseases and can be implemented in mobile applications to assist farmers in early diagnosis and improving crop productivity.
language Inggris Moch Bagus Tri Cahyo; Hamzah Setiawan; Ika Ratna Indra Astutik
J-INTECH ( Journal of Information and Technology) Vol 13 No 02 (2025): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v13i02.2083

Abstract

This study aims to analyze the differences in scalability and performance between a traditional monolithic system hosted on a Virtual Private Server (VPS) and a cloud-native serverless architecture using AWS services for an automotive workshop information system. An experimental method was employed using a post-test only control group design. Performance testing was conducted with K6 as the stress testing tool under a ramp-up load pattern of up to 60 Virtual Users (VU) to simulate peak traffic conditions, while Grafana was used for real-time monitoring and visualization of system metrics.The results indicate that under peak load scenarios, the cloud-native architecture reduced the average response time by 89.1% (from 6.05 seconds to 657.10 milliseconds) and eliminated the error rate completely (from 0.154% to 0%), compared to the monolithic system. Additionally, the throughput improved by 38.2%, demonstrating better responsiveness and stability. These findings confirm that serverless cloud-native systems offer superior scalability and reliability in handling dynamic and high-demand workloads, making them well-suited for public service platforms such as automotive workshop information systems.
SISTEM INFORMASI PENJUALAN PADA COUNTER TJAHAYA CELL BERBASIS WEB Bakhtiar, Muhammad Yahya; Indra Astutik, Ika Ratna
Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Vol. 6 No. 1 (2022): PROSIDING SEMINAR NASIONAL INOVASI TEKNOLOGI TAHUN 2022
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/inotek.v6i1.2462

Abstract

Saat ini, masyarakat lebih menyukai belanja secara online terutama di Indonesia karena menawarkan banyak keuntungan salah satunya masyarakat dalam membeli barang tidak perlu datang ke tokonya (offline). Tujuan penelitian ini adalah merancang sistem informasi penjualan secara online pada toko Tjahaya Cell sehingga dapat meningkatkan penjualan barangnya, tidak hanya di wilayah sekitar toko tapi diseluruh Indonesia. Dimana, saat ini penjualan di toko tersebut masih dilakukan secara offline yaitu masyarakat harus datang ke toko untuk membeli barang. Metode yang digunakan untuk mengembangkan sistem informasi yaitu menggunakan metode waterfall dengan tahapan antara lain : 1) Requirement Analisis, 2)System Design, 3) Implementation, 4) Integration & Testin, 5) Operation & Maintenance. Bahasa pemrograman menggunakan Hypertext Prepocessor (PHP) dan database MySQL. Hasil dari penelitian bahwa sistem informasi dapat meningkatkan penjualan barang di toko Tjahaya Cell serta mampu memberikan informasi secara cepat dan akurat.
Klasifikasi Pola Peminjam Buku Bedarsarkan Profesi Menggunakan Algoritma Naïve Bayes Febri Rosita Dewi; Ade Eviyanti; Arif Senja Fitriani; Ika Ratna Indra Astutik
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 15 No 02 (2025): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v15i02.1661

Abstract

As centers of literacy and learning, libraries face challenges in understanding book lending patterns to meet the needs of diverse users. The main problem faced is the lack of data-based analysis in optimizing library services and collections. This research aims to classify book borrowing patterns based on profession using the Naive Bayes algorithm, utilizing data from the Sidoarjo Library Service in 2023. The data consists of 4476 transactions with attributes such as profession, book category, and level of reading interest. This research was conducted in several phases, namely data collection preprocessing, processing using Gaussian and Multinomial Naive Bayes algorithms, and model evaluation. By testing on various data ratios (90:10, 80:20, 75:25, and 50:50), the results show that Gaussian Naive Bayes provides the highest accuracy of 97% in the random dataset scenario. The main findings show that students, university students and housewives dominate the high reading interest category, while doctors and researchers have lower reading interest. The unique value of this research is in its application of. data-based analysis to support library management. The research results provide strategic insight for developing more responsive data-based services, optimizing collections according to professional needs, and increasing the effectiveness of literacy programs. This research is anticipated to serve as the initial phase in utilizing data mining technology to overcome modern challenges in library management.
Analisis Sentimen Komentar YouTube MV K-Pop Menggunakan Naïve Bayes: Studi Kasus Jung Jaehyun ‘Horizon’ Addriana Fatma Putri Indah Sari; Ade Eviyanti; Ika Ratna Indra Astutik
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 15 No 02 (2025): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v15i02.1691

Abstract

This research aims to analyze the sentiment of YouTube comments on the music video "Horizon" by Jung Jaehyun by applying the Naïve Bayes and Support Vector Machine (SVM). As a global phenomenon, K-pop serves as an intriguing subject for understanding interaction patterns and fan opinions on social media platforms, particularly YouTube. A total of 2,391 Indonesian-language comments were collected using the YouTube API and processed through preprocessing stages such as data cleaning, tokenization, normalization, and the removal of common stopwords. After manually labeling the comments for positive and negative sentiments, the data was analyzed using the Naïve Bayes algorithm, known for its simplicity, speed, and effectiveness with small datasets, and compared with SVM equipped with a linear kernel. The study found that while SVM with a linear kernel achieved the highest accuracy of 98% and excelled in handling imbalanced data, Naïve Bayes still delivered competitive results with an accuracy of 97%. The advantages of Naïve Bayes, including ease of implementation, computational efficiency, and performance on small datasets, make it an effective choice for similar sentiment analysis cases. Both algorithms demonstrated good performance in predicting sentiments, as shown in their confusion matrices, although challenges persisted with the negative class. This research contributes to sentiment analysis methodologies by highlighting that Naïve Bayes is an efficient and relevant algorithm for preliminary exploration, while SVM is more reliable for performance optimization on complex datasets. The findings are particularly relevant to the music industry in understanding fan sentiment as an indicator of success.
Sistem Pakar Berbasis Web untuk Diagnosis Penyakit Paru Anak dengan Forward Chaining Mochammad Raflie Lazuardi; Ika Ratna Indra Astutik; Ade Eviyanti
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 15 No 02 (2025): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v15i02.1738

Abstract

This research aims to design an expert system using the forward chaining method to facilitate the early diagnosis of lung diseases in children, such as tuberculosis, pneumonia, and bronchitis. The system is designed to help the community, especially in areas with limited access to healthcare services, in recognizing symptoms independently. The methodology uses the stages of the Expert System Development Life Cycle (ESDLC), including problem identification, knowledge acquisition from experts, design, and testing using black box techniques. This system is capable of detecting symptoms, matching them with a rule base, and providing an initial diagnosis along with recommended actions. The implementation results show that the system can support quick and accurate medical decision-making, as well as enhance public health awareness through internet-based access.
Co-Authors Addriana Fatma Putri Indah Sari Ade Eviyanti Aisha Hanif Alfian Maulana Fajar Alfitra Oktavian Arif Senja Fitriani Ary Putranto Bakhtiar, Muhammad Yahya Billy Al Ghazian Ramadhan Akbar Danang Firmansyah David Eka Ramadhan Dina Dwi Oktavia Rini Dwi Saka Dharmawan Dwiki Aulia Akbar Eko Fahmi Rosyada Evi Rinata Farrell Ega Santoso Febri Rosita Dewi Feri Tirtoni Fika Fatmala Hamzah Setiawan Hamzah Setiawan Hindarto Imanudin, Giri Fajar Indahyanti , Uce Isnaini Rodiyah Istikomah, Istikomah Istya, Riska Adi Jefry Fernando Joko Susilo Joko Susilo Khasanah, Asmaul MARIA BINTANG Meis Andhiarini, Rugaya Moch Bagus Tri Cahyo Moch Eko Budi Setiawan Mochamad Alfan Rosid Mochammad Bisri Mustofa Mochammad Raflie Lazuardi Mohammad Suryawinata Muhammad Nur Kholis Muhammad Reza Pahlevi Nurdyansyah Nuril Lutvi Azizah Prasetyana, Dwi Gilang Ramadhan Ramadhan, Arga Satria Riyan Fikri Ruri Aditya Pratama Rusdy Yusmiawan Putra Sukma Aji Sumarno Supriyadi Supriyadi Supriyadi Taufiki Ma'rufan Taurusta, Cindy Tutut Anjarsari Uce Indahyanti Uce Indahyanti Wignya Radhitya, Yudhistira Wiwik Sulistiyowati Yeni Kurnia Wati Yulian Findawati Yunianita Rahmawati Yunianita Rahmawati, Yunianita Zaenal Zaenal