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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 Jurnal Abdimas Terapan 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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Implementation of ResNet50 Based on Transfer Learning for Sugarcane Leaf Disease Detection Ulum, M. Miftah Fatkhul; Sholihin, Miftahus; Mustain, Mustain
EDUTIC Vol 12, No 2: 2025
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/edutic.v12i2.31873

Abstract

Sugarcane (Saccharum officinarum) is a vital commodity in Indonesia’s sugar industry and is highly susceptible to leaf diseases such as Mosaic, RedRot, Rust, and Yellow, which significantly reduce yield quality and quantity. This study proposes an automatic disease classification system using the ResNet50 architecture with a transfer learning approach, offering a more systematic evaluation compared to previous studies that typically tested only a single configuration or focused on other crops. The dataset consists of 3,250 RGB images across five classes after preprocessing and augmentation to address class imbalance. Eight model configurations were evaluated by combining epoch values (20, 40) and learning rates (0.0001, 0.001, 0.01, 0.1). The best performance was achieved by the configuration with 20 epochs and a learning rate of 0.0001, producing an accuracy and F1-score of 97%. The model was further deployed into a Flask-based web application to demonstrate practical usability. However, this study is limited by the use of a single controlled dataset, so model performance may vary under real-field conditions such as different lighting, camera angles, and leaf damage severity. Future research should include field data evaluation to strengthen model generalization.
Penguatan Branding Batik Khas Kota Cilegon Melalui Pelatihan Digital Marketing Sonda, Atia; Wicaksono, Agung Satrio; Sholihin, Miftahus; Mahuda, Isnaini; Arina, Faula; Rahma, Midia; Alisya, Regina Dwirahma; Ichsan, Andhika Muhamad; Faiz, Syukron
Abdimas Mandalika Vol 5, No 2 (2026): Februari
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/am.v5i2.35422

Abstract

Abstract:  Rinara Batik, a micro, small, and medium enterprise (MSME), is one of the producers of traditional batik from Cilegon City. To date, the business has primarily focused on a business-to-business (B2B) model, serving schools, large corporations, and local government institutions as its main clients. While this approach provides business stability, it also limits market reach and has yet to fully strengthen the identity of Cilegon’s batik among the wider public. Therefore, a more effective branding strategy that leverages the potential of digital marketing is needed.This community service program aims to enhance the capacity of MSMEs to develop a strong and competitive brand identity, while also expanding their market from B2B to business-to-customer (B2C). The program was conducted through several stages, including problem identification through discussions, the preparation and delivery of digital marketing and website development training and evaluation through participat satisfaction surveys. The evaluation result indicate a very high level of satisfaction with an overall average scrore of 4,74. Through this program, Rinara Batik is expected to expand its market reach and strengthen the position of Cilegon’s batik.Abstrak: UMKM Rinara Batik merupakan salah satu pelaku usaha batik khas Kota Cilegon yang selama ini berfokus pada model bisnis business to business (B2B) dengan pelanggan utama sekolah, perusahaan besar, dan pemerintah daerah. Meskipun memberikan stabilitas usaha, pola ini membatasi jangkauan pasar dan belum sepenuhnya memperkuat identitas batik khas Kota Cilegon di kalangan masyarakat luas. Oleh karena itu, diperlukan strategi branding yang lebih efektif dengan memanfaatkan potensi digital marketing. Kegiatan pengabdian masyarakat ini bertujuan untuk meningkatkan kapasitas UMKM dalam mengembangkan identitas merek yang kuat, berdaya saing, serta memperluas pasar dari B2B menuju Business to Customer (B2C). Kegiatan pegabdian ini dilakukan melalui tahapan identifikasi masalah melalui diskusi, penyusunan dan penyampaian materi pelatihan digital marketing dan pembuatah website serta evaluasi kegiatan melalui kepuasan peserta untuk mengukur efetivitas pelatihan. Hasil evaluasi kegiatan menunjukkan tingkat kepuasan yang sangat baik dengan rata-rata skor keseluruhan sebesar 4,74. Dengan kegiatan ini, UMKM Rinara Batik diharapkan mampu memperluas jangkauan pasar, meningkatkan penjualan, sekaligus memperkuat posisi batik khas Kota Cilegon.
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.
Hybrid deep learning approach for Indonesian hoax detection: a comparative evaluation with IndoBERT Mujilahwati, Siti; Zamroni, Moh. Rosidi; Sholihin, Miftahus
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.
Penerapan Algoritma K Means Clustering Hasil Tangkap Ikan Di Pelabuhan Brondong Khoirul Muhammad Habib; 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.v5i1.5352

Abstract

Pelabuhan Perikanan Nusantara (PPN) Brondong merupakan salah satu sentra aktivitas perikanan yang memiliki volume tangkapan yang mencapai puluhan ribu ton per tahunnya dengan berbagai macam ikan. Penelitian ini bertujuan untuk menerapkan algoritma K-Means Clustering dalam sistem berbasis web untuk mengelompokkan hasil tangkap ikan di PPN Brondong. Metode K-Means dipilih karena mampu melakukan klasterisasi data secara efektif berdasarkan kemiripan karakteristik. Penelitian ini menggunakan data hasil tangkapan ikan selama tahun 2020–2023. Berdasarkan hasil pengujian yang di lakukan, penerapan algoritma K Means clustering dapat di implementasikan dalam penegelompokan hasil tangkap ikan di PPN Brondong dengan hasil yang di peroleh, terdapat 29 ikan yang tergolong ke dalam kategori C1, 4 ikan yang tergolong kategori C2, 2 ikan yang tergolong kategori C3. Evaluasi performa klasterisasi menggunakan metode Silhouette Coefficient menghasilkan skor 0,78 yang mengindikasikan struktur klaster yang kuat
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.
Co-Authors Abdul Kholiq Abdul Kholiq Agus Setia Budi Ahmad Fauzi Hendratmoko Alfarisi, Muhammad Nur Fikri Alisya, Regina Dwirahma AlMuhibbi, Muhammad Rayendra Anam, M. Khairul Ansori, Yulian Arief Rahman Arief Rahman Arina, Faula Arshad, Mohamad Syafwan Asmaraningtyas, Kinanthi Trah Asshiddieqie, Rafi Ramadhan Atia Sonda Aulia Ikhsan Azizah, Luluk Nur 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 Farizki, Achmad Nurasel FATHARANI, ATIKA Fatkhul Hidayat Fatkhul U, M. Miftah Febriyanti Darnis Firdaus, Muhammad Alvin 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 Mufrody, Moh Adam Mustain Mustain Nafiiyah, Nur nawaf abdillah Nur Nafi'iyah Nur Nafi’iyah Nurroziqin, M Chabib Nurul Aswa Omar Nurul Ftria ApriLliani Octaviana Sari, Mila Pertiwi, Dinda Dwi Anugrah Prastowo, Diko Pratiwi, Putri Septiani Indah Prisma Nanda Prsatama, Febrian Abie Rahayu A Hamid Rahma, Midia Retno Wardhani Rofika Arista Sari, Putri Dina Setia Budi, Agus Sika Azkia, Czidni Silvia Agustin Siti Mujilahwati Sulaiman, Akhmad Nurali Surojuddin, Eko Titin Nurbella Udiansyah, Naufal Arrafi Ulum, M. Miftah Fatkhul Umam, Moch. Zuhrul Vanesta Ikhsana Putri Maulana Wati, Efi Neo WICAKSONO, AGUNG SATRIO Yulian Ansori Zirby, Qonit Zumrotus Shalekhah