Article Per Year (5 Year)
p-Index From 2021 - 2026
8.09
P-Index
This Author published in this journals
All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Manajemen Terapan dan Keuangan JURNAL SISTEM INFORMASI BISNIS Jurnal Pendidikan dan Pengajaran AL KAUNIYAH Elkom: Jurnal Elektronika dan Komputer Indonesian Journal of Artificial Intelligence and Data Mining JSiI (Jurnal Sistem Informasi) Jurnal Ilmiah Media Sisfo Jurnal Nasional Komputasi dan Teknologi Informasi Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Journal of Information System,Graphics, Hospitality and Technology Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Nasional Ilmu Komputer Information System Journal (INFOS) Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Jurnal Sains Teknologi dan Sistem Informasi JSIKTI (Jurnal Sistem Informasi dan Komputer Terapan Indonesia) JUSTIN (Jurnal Sistem dan Teknologi Informasi) Brilliance: Research of Artificial Intelligence KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika MATHunesa: Jurnal Ilmiah Matematika Algoritme Jurnal Mahasiswa Teknik Informatika Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Pustaka Aktiva : Pusat Akses Kajian Akuntansi, Manajemen, Investasi, dan Valuta Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Karya Abdi Masyarakat Journal of Business Studies and Management Review Journal of Fish Health MIMBAR INTEGRITAS J-Icon : Jurnal Komputer dan Informatika Journal of Software Engineering and Information System (SEIS) Jurnal Pengabdian Masyarakat Pinang Masak Jurnal Sistem Informasi dan Ilmu Komputer Journal of Management and Innovation Entrepreneurship (JMIE) JUPEMA Jurnal Indonesia : Manajemen Informatika dan Komunikasi International Journal of Computer Technology and Science Akademika Jurnal Ilmu Komputer dan Teknologi Informasi Tesseract: International Journal of Geometry and Applied Mathematics EdLib Journal (Education and Library Journal) Indonesian Journal on Learning and Advanced Education (IJOLAE) JUSS (Jurnal Sains dan Sistem Informasi)
Utomo, Pradita Eko Prasetyo
Univeristas Jambi
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities 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 Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Neuroscience Physics Public Health Social Sciences Transportation Other

Published : 69 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 69 Documents
Search

 3   4   5   6   7 
Pemodelan Prediksi Magnitudo Gempa Bumi di Indonesia Periode 2023–2025 Menggunakan Algoritma Naive Bayes M. Faris Daffarindra; Akhiyar Waladi; Pradita Eko Prasetyo Utomo; Ulfa Khaira
KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Vol 7, No 1 (2026)
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.kernel.2026.v7i1.8399

Abstract

Prediksi gempa bumi sangat penting untuk mitigasi bencana di Indonesia sebagai salah satu negara paling aktif seismik di dunia. Penelitian ini menerapkan algoritma Gaussian Naïve Bayes untuk mengklasifikasikan magnitudo gempa menggunakan data BMKG periode 2023-2025. Setelah pra-pemrosesan 30.000 rekaman, diperoleh 23.979 data valid dengan enam variabel prediktor: lintang, bujur, kedalaman, phasecount, azimuth gap, dan jenis magnitudo. Magnitudo dikelompokkan menjadi Ringan ( 3,0), Sedang (3,0-4,9), dan Kuat (≥ 5,0). Model mencapai akurasi 71,68% dengan precision 0,77 dan recall 0,66 pada kelas Sedang, serta recall 0,78 pada kelas Ringan. Validasi 5-fold cross-validation menghasilkan rata-rata akurasi 68,78% (±7,32%). Perbandingan dengan Random Forest (83,63%) dan SVM (79,15%) menunjukkan hanya Naïve Bayes yang mampu mendeteksi kelas Kuat (precision = 0,18; recall = 0,25). Kebaruan penelitian ini terletak pada evaluasi komparatif tiga algoritma dan analisis kritis asumsi independensi fitur Naïve Bayes terhadap data seismik nyata. Model ini layak sebagai alat skrining awal dalam sistem peringatan dini.
Prediksi Nilai Ekspor Migas Indonesia menggunakan Metode ARIMA Hasby Kuswanto; Pradita Eko Prasetyo Utomo; Ulfa Khaira; Akhiyar Waladi
SATESI: Jurnal Sains Teknologi dan Sistem Informasi Vol. 5 No. 1 (2025): April 2025
Publisher : Yayasan Pendidikan Penelitian Pengabdian ALGERO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/satesi.v5i1.4103

Abstract

This study aims to predict Indonesia's oil and gas (migas) export values using the Seasonal Autoregressive Integrated Moving Average (SARIMA) and Long Short-Term Memory (LSTM) methods. Time series data from Statistics Indonesia (BPS) was utilized to develop an optimal prediction model. The selected SARIMA model, SARIMA(1,1,1)(1,1,1,12), was chosen based on the lowest Akaike Information Criterion (AIC) value. Meanwhile, the LSTM model was developed to capture more complex patterns in time series data. The forecasting results indicate that the SARIMA model provides higher accuracy compared to LSTM based on the Mean Absolute Percentage Error (MAPE), although LSTM demonstrated lower Mean Squared Error (MSE) and Root Mean Squared Error (RMSE). This study emphasizes that the choice of forecasting model should align with the characteristics of the data, where SARIMA is more suitable for oil and gas export data with seasonal patterns. These forecasting results can be utilized to support economic policy planning, optimize investments in the oil and gas sector, and mitigate global market fluctuation risks.
Implementasi Sistem Pencatatan Dan Monitoring Kekeruhan Air Berbasis IoT Pada lembaga Penyedia Air Fachrul Sukmadinata; Pradita Eko Prasetyo Utomo; Muhammad Razi A
Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Vol. 5 No. 1 (2026): EDISI JANUARI 2026
Publisher : STMIK Triguna Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jursi.v5i1.12394

Abstract

Air bersih merupakan kebutuhan dasar yang sangat penting bagi masyarakat dan harus dikelola dengan baik untuk menjamin ketersediaan serta kualitasnya. Pengelolaan layanan air bersih umumnya dilakukan oleh lembaga penyedia air, salah satunya adalah PAM Tirta Tempino. Namun dalam operasionalnya, lembaga ini masih menghadapi kendala pada proses pencatatan pemakaian air, pengelolaan data pelanggan, dan penanganan pengaduan yang masih dilakukan secara manual. Kondisi ini berpotensi menimbulkan keterlambatan informasi, ketidaktepatan data, dan kurangnya transparansi layanan. Selain itu, belum tersedia sistem yang mampu memantau tingkat kekeruhan air secara realtime. Penelitian ini bertujuan mengembangkan sistem informasi berbasis web yang terintegrasi dengan sensor kekeruhan untuk mendukung proses kerja PAM Tirta Tempino. Pengembangan dilakukan menggunakan metode Rapid Application Development melalui beberapa iterasi. Sistem yang dihasilkan menyediakan fitur pencatatan pemakaian air, pengelolaan pelanggan, pengaduan, pembayaran, serta monitoring kekeruhan air secara realtime. Hasil pengujian Black Box Testing menunjukkan bahwa seluruh 31 fungsi sistem berjalan dengan tingkat keberhasilan 100%. Temuan ini menunjukkan bahwa sistem mampu meningkatkan akurasi pencatatan, efisiensi operasional, dan kualitas layanan pada PAM Tirta Tempino.
Analisis Dan Perancangan Sistem Pencatatan Dan Pemantauan Kekeruhan Air Berbasis Website Ikvi Akmal Rivaldi; Pradita Eko Prasetyo Utomo; Muhammad Razi A
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 8 No 1 (2026): Januari 2026
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v8i1.2355

Abstract

The utilization of web-based information systems has been widely adopted to facilitate easier user access to information. Specifically, PAM Tirta Tempino requires a system to manage customer meter recording data and monitor water turbidity quickly and accurately. Therefore, this study aims to design and develop a web-based Information System for Recording and Monitoring Water Turbidity that ensures accessibility for users anytime and anywhere. The system development utilizes the Rapid Application Development (RAD) method. The result of this research is a web-based information system architectural design modeled using Unified Modeling Language (UML), allowing users (Head, Officer, and Customer) to manage and view data according to their respective access rights. Furthermore, the design was verified using the Requirement Traceability Matrix (RTM), yielding valid results which demonstrate that the design fulfills all specified requirements.
PEMBERDAYAAN KELOMPOK SADAR WISATA GUCI EMAS MUARO PIJOAN MELALUI IMPLEMENTASI SISTEM INFORMASI DESA WISATA Pradita Eko Prasetyo Utomo; Tedjo Sukmono; Tia Wulandari; Benedika Ferdian Hutabarat; Dawam Suprayogi
MIMBAR INTEGRITAS : Jurnal Pengabdian Vol 5 No 1 (2026): JANUARI 2026
Publisher : Biro Administrasi dan Akademik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36841/mimbarintegritas.v5i1.7640

Abstract

Desa Muaro Pijoan di Kabupaten Muaro Jambi memiliki potensi wisata berbasis kearifan lokal melalui kawasan Lubuk Larangan Guci Emas, namun promosi digitalnya masih terbatas. Kegiatan pengabdian ini bertujuan mengimplementasikan sistem informasi desa wisata berbasis web dan media sosial untuk memperkuat strategi promosi serta meningkatkan kapasitas digital Kelompok Sadar Wisata (Pokdarwis) Guci Emas. Metode pelaksanaan menggunakan pendekatan partisipatif melalui pelatihan literasi digital, pendampingan pembuatan website, serta produksi konten promosi digital. Hasil kegiatan meliputi terbentuknya website https://lubukguciemas.com, aktivasi akun media sosial resmi, modul pelatihan, serta peningkatan kemampuan mitra dalam mengelola konten secara mandiri. Program ini terbukti efektif dalam memperkuat promosi wisata berbasis teknologi dan kearifan lokal, sekaligus menjadi model replikasi pengembangan desa wisata digital di Provinsi Jambi.
CLUSTERING WILAYAH DI INDONESIA BERDASARKAN KUALITAS PENDIDIKAN MENGGUNAKAN ALGORITMA FUZZY C-MEANS Gema Fitria Anwar; Ulfa Khaira; Pradita Eko Prasetyo Utomo
Information System Journal Vol. 8 No. 02 (2025): Information System Journal (INFOS)
Publisher : Universitas Amikom Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24076/infosjournal.2025v8i02.2442

Abstract

Pendidikan merupakan kebutuhan mendasar yang berperan penting dalam membentuk kualitas sumber daya manusia serta menentukan masa depan bangsa. Hasil PISA (Program for International Student Assessment) 2018 menunjukkan kualitas pendidikan Indonesia masih memprihatinkan dengan peringkat 74 dan skor 1.146. Meskipun pada PISA 2022 posisi Indonesia meningkat lima peringkat, skor turun menjadi 1.108 dan tetap berada di bawah rata-rata negara peserta. Upaya peningkatan kualitas pendidikan salah satunya dapat dilakukan melalui pemerataan kualitas di setiap provinsi. Penelitian ini bertujuan untuk mengidentifikasi pengelompokan provinsi di Indonesia berdasarkan kualitas pendidikan menggunakan algoritma Fuzzy C-Means. Data yang digunakan mencakup enam indikator Pendidikan APK, APM, APS, AMH, RLS, dan HLS pada 34 provinsi selama periode 2022–2024 yang diperoleh dari Badan Pusat Statistik (BPS). Hasil analisis menunjukkan bahwa jumlah Cluster optimal setiap tahun adalah dua Cluster berdasarkan nilai Partition Coefficient Index, yaitu 0.8905128 (2022), 0.8822183 (2023), dan 0.8602231 (2024). Tahun 2022 dan 2023 menunjukkan pola pengelompokan yang konsisten dengan 15 provinsi pada Cluster 1 dan 19 provinsi pada Cluster 2. Pada tahun 2024 terjadi perubahan komposisi, di mana Cluster 1 berkurang menjadi 14 provinsi dan Cluster 2 meningkat menjadi 20 provinsi.  
Prediksi Indeks Harga Saham Gabungan (IHSG) Menggunakan Algoritma Autoregressive Integrated Moving Average (ARIMA) Khaira, Ulfa; Utomo, Pradita Eko Prasetyo; Suratno, Tri; Gulo, Pikir Claudia Septiani
JUSS (Jurnal Sains dan Sistem Informasi) Vol. 2 No. 2 (2019): Jurnal Sains dan Sistem Informasi
Publisher : Prodi Sistem Informasi FST Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/juss.v2i2.8449

Abstract

There are various types of investment in Indonesia, one of which is the Indeks Harga Saham Gabungan (IHSG) or in English it is called the Indonesia Composite Index, ICI, or IDX Composite. IHSG is an important parameter to consider when making an investment considering that IHSG is a joint stock. This study aims to predict the price of the IHSG with data mining techniques using an algorithm that can be used as a reference for investors when making an investment. ARIMA is a model for generating estimates from historical data. Data in this study were collected from the monthly IHSG from January 4, 2010 - November 26, 2019. Based on the correlation plot, two autocorrelations (lag 1, lag 32) were found to be significant. This model can predict with an average percentage error of 0.004 so that this prediction is considered good enough to predict the stock price of the IHSG.
Analisis Sentimen Online Review Pengguna Bukalapak Menggunakan Metode Algoritma TF-IDF Utomo, Pradita Eko Prasetyo; Manaar, Manaar; Khaira, Ulfa; Suratno, Tri
JUSS (Jurnal Sains dan Sistem Informasi) Vol. 2 No. 2 (2019): Jurnal Sains dan Sistem Informasi
Publisher : Prodi Sistem Informasi FST Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/juss.v2i2.8469

Abstract

Bukalapak is one of the Customer-To Customer (C2C) e-commerce models. This model is the most widely applied and found on e-commerce sites in Indonesia. The Customer-To Customer (C2C) market is currently still dominant in Indonesia's online retail market. Data collected from Euromonitor estimates that the C2C market contributed 3% of the retail market in Indonesia in 2017, while the B2C market contributed 1.7%. One text mining analysis is that sentiment analysis can be applied to companies that issue a product or service and provide services to receive opinions (feedback) from consumers for the product. Sentiment analysis is applied to classify positive, negative, and neutral feedback from consumers so as to speed up and simplify the company's task to review their product deficiencies. The researcher conducted further analysis on Bukalapak user reviews to find out how user comments or opinions were on Bukalapak using the TF-IDF Algorithm method. And it can be concluded that based on customer review reviews in Bukalapak have a good rating or perception of this Vans shoe product. Can be seen from the results of Sentiments, Sentiment Visualization and WordCloud Visualization which shows that positive reviews have a higher frequency of 70%.
Perbandingan Efficientnetv2 Dan Mobilenetv3 Pada Cnn Untuk Klasifikasi Gambar Asli Dan Gambar Ai Sandi, Danish Wiedi Marchello; Utomo, Pradita Eko Prasetyo; Khaira, Ulfa
JUSS (Jurnal Sains dan Sistem Informasi) Vol. 9 No. 1 (2026): Jurnal Sains dan Sistem Informasi
Publisher : Prodi Sistem Informasi FST Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/juss.v9i1.58864

Abstract

The rapid advancement of generative artificial intelligence, particularly Generative Adversarial Networks and Diffusion Models, has enabled the creation of synthetic images with a visual quality that is increasingly difficult to distinguish from authentic photographs, raising concerns over misinformation, media manipulation, and digital identity misuse. This study implements a Convolutional Neural Network (CNN) to classify real and AI-generated images and compares the performance of two transfer learning architectures, EfficientNetV2-B0 and MobileNetV3-Large, against a CNN trained from scratch. The dataset consists of 10,930 images collected from two Kaggle repositories, comprising 5,508 AI-generated images and 5,422 real images, which were split into 80% training, 10% validation, and 10% testing data, resized to 224x224 pixels, and augmented prior to training using a batch size of 32, a maximum of 20 epochs, a learning rate of 0.001, and the Adam optimizer. The experimental results show that MobileNetV3-Large achieved the best performance with a training accuracy of 96.84%, a validation accuracy of 96.25%, a testing accuracy of 96.71%, and a testing loss of 0.1031, outperforming EfficientNetV2-B0 (94.41% testing accuracy) and the CNN trained from scratch (91.58% testing accuracy). Hyperparameter experiments further confirm that a batch size of 32 combined with 20 training epochs produces the most stable convergence across all three architectures. The best-performing model was subsequently deployed as a REST API using the Flask framework to support real-time image classification. These findings indicate that transfer learning, particularly with the MobileNetV3-Large architecture, provides an effective and computationally efficient approach for detecting AI-generated images
Co-Authors Abidin, Zainil Ade Octavia Afifa, Afifa Lutfia Fakhira Akhiyar Waladi Amanda Iza Sofiani Arsa, Daniel Aryani, Reni Aryawan, Made Gitra Aulia Dwiza Puteri Ayu Indryani Azhari SN Benedika Ferdian Hutabarat Bisma Aulia Cepi Ramdan Cepi Ramdan Chika Efansa Chit, Suwannit Chareen Dawam Suprayogi Dedy Setiawan Desi Musfiroh Dewa, Raldi Fitra Dinda Fatimah Sarah Dwi Agus Kurniawan Dwi Kurniawan Dwi Suryahartati Edi Saputra Edi Saputra Efansa, Chika Elisa, Edi Fachrul Sukmadinata Fitri Dwi Lestari Fitri, Lucky Enggraini Gema Fitria Anwar Ghaitsa Althafah Wandira Ghaitsa Althafah Wandira Gulo, Pikir Claudia Septiani Hadaya, M. Syahan Afdhal Haloho, Ica Yunarti Haloho Hasanatul Iftitah Hasby Kuswanto Ikvi Akmal Rivaldi Ilhami, Mohamad Ilhami, Mohammad Imelda Raudati Imelda Raudati Indra Weni Jaya, Asirman Jefri Marzal Jefri Marzal Jodion Siburian Khaira, Ulfa Lucky Enggraini Fitri Lutvianita, Febby M. Faris Daffarindra M. Rizky Ardiansyah Putra M. Taufik Hidayat Mahadewa, Agung Mahmudin, Riyan Manaar, Manaar Mauladi Mauladi, Mauladi Mh. Khathamy Fhadlullah Haq Syahlevy Mochammad Farisi Muhammad Iqbal Muhammad Nabil Muhammad Razi A Muksin Alfalah Mutia Fadhila Putri Mutia Fadhila Putri mutia fadhila putri, mutia fadhila Nasution, Mukhtada Billah Nazwa Eka Hervy Novita Sari Novita Sari Putra, Tri Syukria Putra, Yahya Nugraha Putri Hazmawati Putri, Anastasya Alya Ragil Johanda Rahayu Rahayu Rayandra Asyhar Reni Triyaningsih Repaldi Handi Saputra Reza Safitri Rivaldi, Ikvi Akmal Rizka Octavia Sandra Rizky Janatul Magwa Rizqa Raaiqa Bintana Sahrial Salmah Nur Zahra Salman Jumaili Salsabila, Adinda Desiska Sandi, Danish Wiedi Marchello SAUDAGAR, FERDIAZ Sigit Indrawijaya Simanjuntak, Januar SRI RAHAYU Suhartini, Sugih Sukma, Silvia Antana Sulfiyandi Sulfiyandi Suwannit Chareen Chit Sylvia Kartika Wulan Bhayangkari Tasia Maidi Saputri Tasia Maidi Saputri Tedjo Sukmono Teguh Sumarsono Tia Wulandari Tri Suratno Tri Syukria Putra Ulfa Khaira, Ulfa Wahyu, Ofel Idhan Winando Parbo Kusuma Yenny Yuniarti Yoppie Wulanda Yosika Dian Saputri Yovita, Kristian Yuhana Yuhana Yusnita, Erli