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All Journal International Journal of Advances in Applied Sciences TEKNIK INFORMATIKA Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Ilmiah Kursor JOIV : International Journal on Informatics Visualization JURNAL MEDIA INFORMATIKA BUDIDARMA JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI CYBERNETICS KOMPUTEK Jurnal Elektronika Listrik dan Teknologi Informasi Terapan Generation Journal Jurnal Teknika JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Jurnal Berdaya Mandiri Jurnal Teknik Informatika (JUTIF) Joutica : Journal of Informatic Unisla INFORMATIKA Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Ilmiah Edutic : Pendidikan dan Informatika Journal of Artificial Intelligence and Digital Business Dedication : Jurnal Pengabdian Masyarakat Abdimas Mandalika Journal of Mathematics, Computation and Statistics (JMATHCOS) Jurnal Publikasi Ilmu Komputer dan Multimedia
Miftahus Sholihin
Universitas Islam Lamongan
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Implementasi Metode Least Square Untuk Prediksi Hasil Panen Ikan Kerapu Cantang (Studi Kasus : Desa Labuhan Kecamatan Brondong Kabupaten Lamongan) nawaf abdillah; Miftahus Sholihin; Agus Setia Budi
Jurnal Publikasi Ilmu Komputer dan Multimedia Vol. 5 No. 1 (2026): Januari: Jurnal Publikasi Ilmu Komputer dan Multimedia
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupikom.v5i1.5353

Abstract

Desa Labuhan, kecamatan brondong, kabupaten lamongan, merupakan salah satu produsen utama ikan kerapu di jawa timur. Desa ini memiliki potensi besar dalam perikanan budidaya kerapu yang memberikan dampak signifikan pada peningkatan hasil perikanan dan ekonomi masyarakat. Tujuan penelitian ini untuk merancang sebuah sistem berbasis web yang dapat membantu pembudidaya ikan kerapu cantang untuk memprediksi hasil panennya. Pada penelitian ini metode yang digunakan adalah Least square. Data yang digunakan adalah data hasil panen dari tahun 2019 sampai 2024 yang terdiri dari lahan 1 dan lahan 2, yang akan digunakan untuk memprediksi hasil panen enam tahun kedepan. Hasil pengujian dari hasil panen tersebut dengan menggunakan metode Least square pada lahan 1 memiliki tingkat akurasi sebesar 96,47% dan lahan 2 memiliki tingkat akurasi sebesar 95,79%. Sehingga dapat disimpulkan bahwa hasil ramalan tersebut termasuk dalam kategori yang sangat baik sesuai dengan hasil akurasi yang di peroleh dan nilai MAPE yang di peroleh.
Penerapan Metode Double Exponential Smoothing untuk Memprediksi Penggunaan HIPPAM (Studi Kasus; Himpunan Pemakaian Air Masda) Octaviana Sari, Mila; Miftahus Sholihin; Agus Setia Budi
Jurnal Publikasi Ilmu Komputer dan Multimedia Vol. 5 No. 1 (2026): Januari: Jurnal Publikasi Ilmu Komputer dan Multimedia
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupikom.v5i1.5354

Abstract

Clean water is an essential resource, yet its distribution often faces challenges due to population growth, seasonal changes, and consumption patterns. The Public Water Users Association (HIPPAM) in Dengok Hamlet, Kandangsemangkon Village, Lamongan Regency, plays a vital role in meeting the community’s daily water needs. This study applies the Double Exponential Smoothing (DES) method to forecast HIPPAM water demand. Consumption data from 2020 to 2024 were used, with smoothing parameters alpha (α) and beta (β) set between 0 and 1. The forecasting performance was evaluated using MAPE (Mean Absolute Percentage Error), MAD (Mean Absolute Deviation), and MSE (Mean Squared Error). Results show that the DES method achieved high accuracy, with MAPE values below 1%. Furthermore, the forecasting system was implemented as a web-based application, enabling HIPPAM managers to monitor and plan water distribution more effectively.
Sistem Pengenalan Wajah Siswa Dengan Metode You Only Look Once Version 3 Hidayat, Fatkhul; Miftahus Sholihin; Agus Setia Budi
Jurnal Publikasi Ilmu Komputer dan Multimedia Vol. 5 No. 1 (2026): Januari: Jurnal Publikasi Ilmu Komputer dan Multimedia
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupikom.v5i1.5433

Abstract

Penelitian ini mengimplementasikan You Only Look Once Version 3 untuk sistempengenalan wajah siswa menggunakan dataset berisi 200 citra wajah yang dibagi menjadi data latih,validasi, dan uji. Model dilatih dengan bobot pralatih YOLOv3 menggunakan learning rate sebesar0,001, batch size 16, 80 epoch, serta early stopping untuk mencegah overfitting. Hasil evaluasimenunjukkan Accuracy sebesar 100,00%, Precision sebesar 48,76%, Recall sebesar 100,00%, F1-scoresebesar 65,55%, dan mAP@0.5 sebesar 68,35%. Nilai-nilai ini menunjukkan bahwa model memilikikinerja yang baik dalam mendeteksi dan mengenali wajah siswa, meskipun aspek precision masih perluditingkatkan. Sistem diimplementasikan dalam bentuk aplikasi web berbasis Flask yang terintegrasidengan MySQL, sehingga mendukung proses identifikasi siswa secara otomatis, cepat, dan efisien.
Hybrid deep learning approach for Indonesian hoax detection: a comparative evaluation with IndoBERT Siti Mujilahwati; Moh. Rosidi Zamroni; Miftahus Sholihin
International Journal of Advances in Applied Sciences Vol 15, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i1.pp322-332

Abstract

The spread of hoaxes in Indonesia has escalated significantly, with over 12,547 cases recorded between 2018 and 2023. Low public literacy and uncontrolled information flow contribute to the rapid dissemination of false content that fuels disinformation and social unrest. Previous studies have utilized artificial intelligence (AI) approaches such as Indonesia bidirectional encoder representations from Transformers (IndoBERT) and deep learning models like long short-term memory (LSTM), bidirectional LSTM (BiLSTM), convolutional neural network (CNN), and Transformer-based methods. However, most relied on a single modeling paradigm and did not address the trade-offs between classification performance and computational efficiency. This study proposes a hybrid architecture that integrates IndoBERT with bidirectional gated recurrent unit (BiGRU) and BiLSTM to enhance Indonesian hoax detection. Using 4,312 news articles and 10-fold cross-validation, we compare the performance of IndoBERT–BiGRU, IndoBERT–BiLSTM, and the proposed hybrid IndoBERT–BiGRU BiLSTM model. Evaluation metrics include accuracy, precision, recall, F1 score, and training time. The hybrid model achieved the best performance with 98.73% accuracy, 99.01% recall, 98.04% precision, and 98.98% F1 score, while also reducing training time compared to single models. These findings demonstrate that combining BiGRU and BiLSTM within the IndoBERT framework effectively balances performance and efficiency, making it a robust solution for Indonesian text classification.
Baby Supplies Sales Prediction System using the Single Exponential Smoothing Method at Little Queen Baby Shop Silvia Agustin; Miftahus Sholihin; Agus Setia Budi
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.1824

Abstract

The increasing demand for baby equipment in Indonesia in recent years has created significant business opportunities for the retail sector, including Little Queen Baby Shop. However, seasonal fluctuations in demand often lead to stock management problems such as overstock and out of stock, which affect storage costs and customer satisfaction. This research aims to design and develop a sales prediction system for baby products using the Single Exponential Smoothing (SES) method as a solution to minimize forecasting errors and support data-driven decision-making. The research method involved collecting secondary sales data from January to November 2024, which was then processed using the SES algorithm with a smoothing parameter (α) to determine the optimal prediction values with the lowest error rate. The system was developed as a web-based application using PHP programming language and MySQL database, equipped with features such as transaction recording, stock management, sales analysis, and prediction reports for upcoming periods. The implementation results show that the SES-based prediction system provides sufficiently accurate forecasts, as indicated by low values of Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE), and Mean Squared Error (MSE). This system enables Little Queen Baby Shop to optimize stock management, reduce the risk of losses due to excessive or insufficient inventory, and improve both operational efficiency and customer satisfaction.
Co-Authors Abdul Kholiq Agus Setia Budi Agus Setia Budi Alisya, Regina Dwirahma Ansori, Yulian Arief Rahman Arief Rahman Arina, Faula Arshad, Mohamad Syafwan Asmaraningtyas, Kinanthi Trah Asshiddieqie, Rafi Ramadhan Atia Sonda Aulia Ikhsan Azza Abidatin Bettaliyah AZZA ABIDATIN BETTALIYAH Bagus Nur Bakti Aji Bagus Nur Bakti Aji Cindy Suryanti Darnis, Febriyanti Delano, M. Fabian Reinhard Dinar Mahdalena Leksana 1 Erna Hayati Erna Hayati, Erna Erry Anggraini ERRY ANGGRAINI Faiz, Syukron Fatkhul Hidayat Febriyanti Darnis Fudzee, Mohd Farhan Md Gusman, Taufik Hamid, Rahayu A Ichsan, Andhika Muhamad Ismail, Mohd Norasri Izz, Aiz Ahmad Fa’iz Dliya’ul Khoirul Muhammad Habib KIKI SEPTARIA Lilik Anifah M. Ghofar Rohman M. Rosidi Zamroni M. ZAKI QOMARUDDIN Mahuda, Isnaini Masruroh MASRUROH Megawati Indriani Mohd Farhan MD Fudzee, Mohd Farhan Mustain Mustain Nafiiyah, Nur nawaf abdillah Nur Nafi'iyah Nur Nafi’iyah Nurul Aswa Omar Nurul Ftria ApriLliani Octaviana Sari, Mila Pertiwi, Dinda Dwi Anugrah Pratiwi, Putri Septiani Indah Prisma Nanda Rahayu A Hamid Rahma, Midia Retno Wardhani Rofika Arista Sari, Putri Dina Setia Budi, Agus Sika Azkia, Czidni Silvia Agustin Siti Mujilahwati Surojuddin, Eko Titin Nurbella Udiansyah, Naufal Arrafi Ulum, M. Miftah Fatkhul Vanesta Ikhsana Putri Maulana Wati, Efi Neo WICAKSONO, AGUNG SATRIO Yulian Ansori Zumrotus Shalekhah