M. Rosidi Zamroni
Program Studi Teknik Informatika, Fakultas Teknik, Universitas Islam Lamongan

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SISTEM PAKAR DIAGNOSA PENYAKIT SAPI SEBAGAI UPAYA PENCEGAHAN PENYEBARAN WABAH PMK DI LAMONGAN Moh. Rosidi Zamroni; Qabilah Cita K. N. S; Agung Wahyudi
JURNAL ILMIAH INFORMATIKA Vol 10 No 02 (2022): Jurnal Ilmiah Informatika (JIF)
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v10i02.6373

Abstract

On May 5, 2022, Indonesia was hit by an outbreak of PMK in livestock. Until now, in August 2022, there are 20 provinces, 215 districts/cities, 1,808 sub-districts and 7,434 villages that are still actively infected with nail and mouth disease (PMK). The emergence of PMK is an epidemic that results in huge losses to cattle farmers. Especially if you do not have knowledge about the transmission of the disease. One of the efforts to prevent the spread of livestock disease is to implement an expert system for diagnosing cattle disease using the forward chaining method. Where this system will help farmers to provide knowledge of disease symptoms and diagnosis of disease, so that farmers are able to take initial action to handle their livestock.
Peningkatan Penjualan Pada Pengrajin Ikat Tenun di Desa Parengan, Kecamatan Maduran, Kabupaten Lamongan dengan E-Commerce Berbasis Web MOH. ROSIDI ZAMRONI; MIFTAHUS SHOLIHIN; SITI MUJILAHWATI; AZZA ABIDATIN BETTALIYAH; RETNO WARDHANI; ERRY ANGGRAINI; M. ZAKI QOMARUDDIN
Prosiding Seminar Sains Nasional dan Teknologi Vol 12, No 1 (2022): VOL 12, NO 1 (2022): PROSIDING SEMINAR NASIONAL SAINS DAN TEKNOLOGI
Publisher : Fakultas Teknik Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/psnst.v12i1.7201

Abstract

Kain tenun ikat menjadi ciri khas Dusun Parengan di Kecamatan Maduran Kabupaten Lamongan. Tidak ada produk pengganti, dan sulit untuk diduplikasi. Selama ini, prosedur pemasaran dilakukan secara manual dengan mengirimkan kain tenun ke daerah terdekat antara lain Surabaya, Bandung, dan Jakarata. Pengumpul atau pemborong akan mendistribusikan komoditas tersebut kepada pihak atau pelanggan lain setelah barang tiba di tempat tujuan. Pelaku UMKM ingin pemasaran mereka lebih luas dan tidak terlalu bergantung pada pengumpul atau pemborong. Memperluas pemasaran produk akan meningkatkan daya beli, yang akan berdampak pada perluasan daya produksi dan berkontribusi pada kesejahteraan masyarakat.Penerapan teknologi informasi yang dapat dimanfaatkan UMKM secara efektif dan berkelanjutan merupakan strategi yang digunakan untuk menjawab permasalahan yang dihadapi UMKM di Desa Parengan, khususnya dalam hal pemasaran produk. Sistem yang dikembangkan berupa aplikasi jual beli online yang dikenal dengan Sistem Informasi Penjualan atau e-commerce. Manfaat menggunakan program e-commerce atau sistem informasi penjualan berbasis web antara lain dapat menjalankan bisnis tenun ikat secara cepat, efektif, dan efisien yang akan meningkatkan penjualan produk kain tenun ikat itu sendiri.
Pembuatan E-Commerce Untuk Meningkatkan Penjualan Pada Pengrajin Ikat Tenun Di Lamongan Moh. Rosidi Zamroni; Miftahus Sholihin; Siti Mujilahwati; Azza Abidatin Bettaliyah; Retno Wardhani; Erry Anggraini
Dedication : Jurnal Pengabdian Masyarakat Vol 7 No 1 (2023)
Publisher : LPPM Universitas PGRI Argopuro Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31537/dedication.v7i1.1036

Abstract

Tenun ikat desa Parengan Kecamatan Maduran Kabupaten Lamongan memiliki kekhasan dan keunikan tersendiri, sulit ditiru dan tidak ada produk pengganti. Selama ini proses pemasaran dilakukan secara manual. Para pelaku UMKM menginginkan pemasarannya meluas ke daerah-daerah lain yang tidak hanya tergantung oleh pengepul atau pemborong saja. Jika pemasaran produk dapat meluas, maka akan meningkatkan daya beli sehingga berdampak pada daya produksi yang meningkat dan juga bisa membawa kesejahteraan bagi masyarakat pelaku usaha. Pendekatan yang digunakan untuk mengatasi permasalahan yang ada di UMKM desa Parengan khususnya dalam hal pemasaran produk adalah dengan menerapkan teknologi informasi yang dapat dimanfaatkan secara maksimal dan berkelanjutan oleh UMKM. Bentuk sistem yang dibuat adalah e-commerce yang merupakan aplikasi jual beli online. Keuntungan yang didapat dengan adanya aplikasi e-commerce antara lain: bisnis kain tenun ikat dapat dilakukan dengan cepat, efektif, dan hemat, sehingga akan berdampak pada peningkatan penjualan produk kain tenun ikat itu sendiri.
METODE JARINGAN SYARAF TIRUAN UNTUK MEMPREDIKSI PENJUALAN PAKAIAN PADA DISTRO DI LAMONGAN Zamroni, M. Rosidi; Mujilahwati, Siti
Jurnal Mnemonic Vol 5 No 1 (2022): Mnemonic Vol. 5 No. 1
Publisher : Teknik Informatika, Institut Teknologi Nasional malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/mnemonic.v5i1.4459

Abstract

The most important indicator in business is the amount of sales. The magnitude of the level of sales affects the profits earned by the company which also affects the competition in business competition. To determine a marketing strategy, it is necessary to make accurate predictions about future market conditions, so the authors initiate forecasting using the Backpropagation Neural Network method. Beckpropagation is an algorithm that can train the network in the previous situation. The training will adjust the weights in the network as new inputs for predicting sales. The pattern used is 12-10-1, meaning that there are 12 input sales values for 12 months, 10 neurons in the hidden layer, and 1 sales output value during the following month. The results of this study were obtained at epoch 211 with an MSE value of 0.00098405, an accuracy of 79.14%, while an MSE of 0.2139.
PENINGKATAN PEREKONOMIAN UMKM MELALUI PENGEMBANGAN SISTEM INFORMASI WISATA PANTAI PENGKOLAN DI DESA KANDANGSEMANGKON Mujilahwati, Siti; Sholihin, Miftahus; Zamroni, M.Rosidi; Alfarisi, Muhammad Nur Fikri; Firdaus, Muhammad Alvin; Zirby, Qonit; AlMuhibbi, Muhammad Rayendra; Mufrody, Moh Adam; Prsatama, Febrian Abie; Nurroziqin, M Chabib; Farizki, Achmad Nurasel
Jurnal Abdimas Terapan Vol. 4 No. 1 (2024): JURNAL ABDIMAS TERAPAN (NOVEMBER)
Publisher : Program Vokasi Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56190/jat.v4i1.66

Abstract

Kandangsemangkon Village, situated on the northern coast of Lamongan Regency, exhibits considerable potential for tourism development, largely due to its proximity to the notable Pengkolan Beach. However, the absence of effective promotional strategies and a lack of visibility represent a significant challenge in the development of tourism and the empowerment of local micro, small, and medium-sized enterprises (MSMEs). The objective of this community service program is to enhance the visibility of Pengkolan Beach and bolster the local economy through the establishment of a comprehensive tourism information system website. A series of activities, including field surveys, website development, training for MSMEs, and digital promotion, has enabled the creation of an effective platform for introducing the tourism potential and local products of the area to a wider audience. While there is no specific measurement regarding visibility, the positive response from the community and MSME actors indicates that this website has had a significant impact. The results of this program demonstrate an increase in the promotion of tourist destinations and sales of MSME products. To ensure the sustainability of this program, it is essential to prioritize website maintenance, continued training, and the enhancement of tourism infrastructure. Consequently, Kandangsemangkon Village can continue to develop as a renowned tourist destination, which will ultimately reinforce the local economy and community welfare.
DETECTION OF BULLYING CONTENT IN ONLINE NEWS USING A COMBINATION OF RoBERTa-BiLSTM Zamroni, Moh. Rosidi; Hamid, Rahayu A; Mujilahwati, Siti; Sholihin, Miftahus; Leksana, Dinar Mahdalena
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 1 (2025): JUTIF Volume 6, Number 1, February 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.1.4140

Abstract

This research aims to build a bullying-themed online news classification system with a combined approach of RoBERTa embedding and BiLSTM. RoBERTa is used to generate context-rich text representations, while BiLSTM captures temporal relationships between words, thereby improving classification performance. The research dataset consisted of news from reputable portals such as Kompas.com, Detik.com, and iNews.com, labeled according to keywords relevant to the theme of bullying. The results of the experiment showed that the model achieved 95.2% accuracy, 98.2% precision, 93.6% recall, and 95.8% F1-score. Although there are few prediction errors (false positives and false negatives), this model shows excellent performance in detecting and classifying bullying-themed news. The main contribution of this research is the development of a new approach that combines RoBERTa and BiLSTM for the classification of complex bullying-themed news. This approach not only improves the accuracy of classification but can also be implemented in automated systems to detect negative content. Thus, this research has the potential to support the creation of a healthier digital space and encourage more responsible media practices.
Peningkatan Kualitas Guru Melalui Komunitas: Pelatihan dan Pendampingan Penyusunan Perangkat Pembelajaran Untuk Mendukung SDGs-4 Septaria, Kiki; Fatharani, Atika; Sholihin, Miftahus; Kholiq, Abdul; Zamroni, Moh. Rosidi; Hendratmoko, Ahmad Fauzi; Hayati, Erna; Azizah, Luluk Nur; Leksana, Dinar Mahdalena
Jurnal Abdimas Terapan Vol. 4 No. 2 (2025): JURNAL ABDIMAS TERAPAN (MEI)
Publisher : Program Vokasi Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56190/jat.v4i2.84

Abstract

Peningkatan kualitas guru merupakan elemen krusial dalam mewujudkan pendidikan berkualitas yang sejalan dengan prinsip SDGs-4. Meski demikian, banyak guru menghadapi tantangan dalam menyusun perangkat pembelajaran berbasis Kurikulum Merdeka, terutama dalam mengintegrasikan nilai-nilai keberlanjutan, inklusivitas, dan teknologi pembelajaran. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk memberikan pelatihan dan pendampingan kepada guru di Madrasah Aliyah Negeri (MAN) 1 Lamongan dalam menyusun perangkat pembelajaran yang relevan dan inovatif. Metode kegiatan mencakup identifikasi kebutuhan guru, pelatihan intensif, pendampingan berkelanjutan, evaluasi, serta publikasi dan penyebarluasan hasil kegiatan. Dampak dari kegiatan ini menunjukkan bahwa kompetensi guru dalam menyusun perangkat pembelajaran yang sesuai dengan Kurikulum Merdeka telah meningkat secara signifikan. Terdapat 90% guru berhasil membuat perangkat pembelajaran yang berkualitas, serta 75% guru mampu meningkatkan keterampilan teknologinya. Kegiatan ini juga menciptakan dampak jangka panjang dengan membentuk komunitas belajar guru sebagai wadah pengembangan profesional berkelanjutan dan penyebaran praktik terbaik kepada guru-guru lain di wilayah sekitar. Manfaat dari kegiatan ini tidak hanya memperkuat kapasitas guru di MAN 1 Lamongan, tetapi juga memberikan kontribusi signifikan terhadap pengembangan pendidikan berbasis SDGs-4 di tingkat lokal dan nasional.
Evaluating BiLSTM  Performance with BERT, RoBERTa, and DistilBERT in Online Bullying News Detection Zamroni, Moh. Rosidi; Sholihin, Miftahus; Hayati, Erna; Rahayu A Hamid; Nurul Aswa Omar
JURNAL TEKNIK INFORMATIKA Vol. 18 No. 2: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v18i2.42459

Abstract

This study examines the performance of BiLSTM combined with three transformer-based word embeddings—BERT, RoBERTa, and DistilBERT—in classifying bullying news in online media. BiLSTM was chosen for its significant advantages in processing text sequences compared to traditional RNN and LSTM models. The study used a dataset of 2,800 articles from three major Indonesian news portals, with 2,000 articles for training and 800 for testing, labeled using the lexicon method. The testing results showed that the combination of BiLSTM and RoBERTa achieved the best performance, with an accuracy of 94% and a near-perfect precision of 99%. Statistical significance tests confirmed that BiLSTM with RoBERTa performs significantly better than with BERT or DistilBERT. These findings suggest that the BiLSTM and RoBERTa combination is the most effective for classifying bullying news, especially for new or unseen data. This research contributes to the development of automatic bullying content detection systems to enhance content moderation on news platforms.
DETEKSI DEPRESI PADA SISWA BERBASIS WEB (STUDI KASUS: MTs TERPADU RAUDLATUL QUR’AN LAMONGAN) Sholihin, Miftahus; Leksana, Dinar Mahdalena; Hayati, Erna; Kholiq, Abdul; Zamroni, M. Rosidi; Anam, M. Khairul; Sulaiman, Akhmad Nurali; Umam, Moch. Zuhrul; Fatkhul U, M. Miftah; Prastowo, Diko
Jurnal Abdimas Terapan Vol. 3 No. 2 (2024): JURNAL ABDIMAS TERAPAN (MEI)
Publisher : Program Vokasi Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56190/jat.v3i2.58

Abstract

This Students' mental health in the school environment is becoming increasingly important. Depression, as a severe mental health disorder, can have a negative impact on students' well-being and academic achievement if it is not detected and treated appropriately and quickly. This service program aims to detect depression in MTs Roudlatul Qur'an students as early as possible to reduce the risk of ongoing depression. This can be done by building a website-based system that students can use to detect depression independently. This system was created to make it easier for students to recognize the early symptoms of depression by selecting the symptoms according to what they are experiencing. With this system, it is hoped that it can prevent depression as early as possible for students and teachers quickly and more efficiently, thereby reducing students who are at risk of experiencing depression. Apart from that, the system provides valuable information for students and teachers to understand depression more deeply and find ways to overcome it. Through this program, it is hoped that awareness of the importance of mental health in the school environment can increase and create a healthier and more supportive learning environment for all students.
Fine-Tuned Transfer Learning with InceptionV3 for Automated Detection of Grapevine Leaf Diseases Sholihin, Miftahus; Zamroni, Moh. Rosidi; Anifah, Lilik; Fudzee, Mohd Farhan Md; Ismail, Mohd Norasri
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.4717

Abstract

Grape leaf diseases pose a major threat to vineyard productivity, making early and accurate detection essential for modern grape plantation management. Despite advancements in computer vision, challenges remain in differentiating diseases with visually similar symptoms. This study addresses that gap by developing a grape leaf disease classification system using a fine-tuned deep learning model based on the InceptionV3 architecture. Three training scenarios were conducted with fixed parameters batch size of 32 and learning rate of 0.001while varying the number of epochs (25, 50, and 75). Results showed a consistent improvement in classification accuracy with increased training epochs, reaching 98.64%, 98.78%, and 99.09% respectively. Confusion matrix analysis revealed that most misclassifications occurred between visually similar diseases such as Black Rot and ESCA, but error rates declined as the number of epochs increased. Rather than merely applying transfer learning, this research highlights the impact of systematic tuning specifically epoch count optimization in enhancing model accuracy for difficult to distinguish disease classes. These findings underscore the urgency of developing high performance, automated disease detection tools to support precision agriculture and sustainable crop health monitoring.