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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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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.
Alexnet Arsitektur Untuk Klasifikasi Jenis Batik Lamongan Erry Anggraini; Miftahus Sholihin; Cindy Suryanti; Titin Nurbella
CYBERNETICS Vol 6, No 02 (2022): CYBERNETICS
Publisher : Universitas Muhammadiyah Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Indonesia memiliki beragam jenis batik yang berasal dari beberapa daerah. Batik dari masing-masing daerah memiliki corak yang dan motif yang berbeda-beda. Salah satu daerah yang menghasilkan batik adalah Lamongan. Batik yang berasal dari Lamongan biasanya lebih dikenal dengan nama batik Sendang, hal ini berkaitan dengan tempat pengrajinnya. Batik Sendang memiliki beberapa motif antara lain petethan, slempang, putihan, gapuro tanjung kodok, dan bandeng lele. Tujuan dari penelitian ini adalah untuk membuat sistem yang mampu melakukan klasifikasi citra batik Lamongan. Penelitian ini menggunakan metode Convolutional Neural Network (CNN) dengan arsitektur Alexnet. Data citra yang digunakan pada penelitian ini adalah citra batik dengan jumlah data adalah 790 yang dibagi menjadi data training sebanyak 576 dan data testing sebanyak 214 yang dibagi ke dalam tiga kelas yaitu kelas petethan, putihan, dan slempang. Hasil dari penelitian ini adalah sistem mampu melakukan klasifikasi jenis batik Lamongan dengan menggunakan arsitektur Alexnet dengan nilai rata-rata sensitiviti 97%, spesifisiti 99%, akurasi 98%, dan precision factor 97%.dimana nilai epoch yang digunakan adalah 75. Kesimpulan yang diperoleh adalah kelas petethan dan putihan mampu dikenali seluruhnya dengan benar, sedangkan untuk kelas slempang, 2 citra dikenali sebagai kelas petethan dan 5 citra dikenali sebagai kelas putihan.
PENINGKATAN KUALITAS PENDIDIK DAN PEMBELAJARAN MENUJU MADRASAH YANG UNGGGUL DAN BERKELANJUTAN Kiki Septaria; Miftahus Sholihin; Abdul Kholiq; Erna Hayati; Vanesta Ikhsana Putri Maulana
Jurnal Berdaya Mandiri Vol. 4 No. 2 (2022): JURNAL BERDAYA MANDIRI (JBM)
Publisher : Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/jbm.v4i2.1742

Abstract

Kualitas madrasah umumnya lebih rendah daripada sekolah negeri baik sekolah dasar, sekolah menengah pertama atau atas, namun hasiil penelitian bahwa kualitas sebuah instansi dapat diukur dengan kualitas pembelajaran di kelas. Kualitas pembelajaran memiliki 2 indikator yang diukur yaitu keterampilan guru dalam merencanakan, melaksanakan, mengevaluasi pembelajaran dan pedagogi yang dimiliki guru. Tujuan kegiatan pengabdian ini merupakan mengukur kualitas pembelajaran di Madrasah Ibtidaiyah Ma'arif NU Sunan Drajat Lamongan (MI Murni) dan mengoptimalkan kelemahan yang diperoleh. Metode yang digunakan dalam pengabdian yaitu FGD, pengembangan isntrumen, validasi, observasi awal, workshop dan observasi akhir. Hasil kegiatan pengabdian ini yaitu meningkatnya keterampilan perencanaan guru pada perancangan proses pembejaran setelah diukur dengan N-Gain, peningkatan keterampilan pelaksanaan kegiatan pembelajaran dengan kriteria sedang, peningkatan kategori sedang dalam keterampilan evaluasi pembelajaran dan peningkatan dengan kategori sedang pada pengetahuan guru secara pedagogi. Kegiatan pengabdian ini mampu meningkatkan kualitas pembelajaran di kelas sehingga kualitas madrasah mampu meningkat secara kelembagaan. Rencana selanjutnya pada kegiatan pengabdian ini adalah peningkatan pembelajaran al-qur’an dan tahfidz yang diajarkan pada madrasah
KLASIFIKASI KUALITAS MUTU TELUR AYAM RAS BERDASARKAN FITUR WARNA DAN TEKSTUR Miftahus Sholihin; M Ghofar Rohman
Jurnal Teknika Vol 10 No 2 (2018)
Publisher : Universitas Islam Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30736/teknika.v10i2.244

Abstract

Egg quality is determined by the quality of the inside and outside of the egg. To find out the quality of eggs canbe by looking at the outside in the form of skin condition, shape, size, and egg weight. In this study a system isdesigned to function to determine the quality of egg quality based on color and texture features. Broadlyspeaking, the system built consists of 4 main processes. This process begins with pre-processing which aims toimprove image quality and also to change the image size. The next process is segmentation to get the egg object.The next process is feature extraction which aims to get the characteristics of each egg object. The last processis a classification that aims to determine the class of egg images entered by the user, the method used is knearest neighbor. The data used in this study were 147 egg images consisting of 85 eggs of data testing and 62eggs of training data. The highest accuracy obtained from this study is 82.3% with a value of 8
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.
IMPLEMENTASI SOM DALAM CLUSTERING HASIL IKAN LAUT KABUPATEN PEKALONGAN Bagus Nur Bakti Aji; Nur Nafi’iyah; Miftahus Sholihin
Jurnal Elektronika Listrik dan Teknologi Informasi Terapan Vol. 2 No. 1 (2020): ELTI Juni
Publisher : LPPM Politeknik Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37338/elti.v2i1.178

Abstract

Data from sea fish in Pekalongan Regency can be processed, one of which is clustered. Clusters are grouping data based on the same criteria. The purpose of doing clustering is to be able to help in sorting and dividing a situation based on the same criteria. Clustering of marine fish products in Pekalongan Regency will be grouped into three groups, namely: a small group of marine fish products, a medium group of marine fish products, and a large group of marine fish products. The clustering process uses the SOM algorithm, and the data is taken from the website data.go.id/dataset. Data is processed in order to show which fish yields are small, medium and large. The processing process uses variable types of fish, years and results of sea fish that are stored in Excel files and then processed using Matlab. The results show that there are fish species that are classified as low and moderate clusters, namely shrimp, squid, serimping, grouper, turmeric, and ray species. The types of fish that enter the cluster and many are Tigawaja. The types of fish that enter the medium cluster are Beloso, Pihi, Pepetek, and those who enter the low cluster are 18 fish species, while those who enter the low, medium and many clusters are Petek.
Expert System for Ear Disease Using the Nave Bayes Method Pratiwi, Putri Septiani Indah; Rohman, MGhofar; Sholihin, Miftahus
Generation Journal Vol 7 No 2 (2023): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/gj.v7i2.19991

Abstract

An expert system is a type of artificial intelligence application that is used to tackle complex problems that require specialized knowledge. Expert systems can be used in a variety of disciplines, including healthcare, finance, and manufacturing. The aim of this study was to apply the Nave Bayes approach in a website-based ear illness diagnostic system and to determine its accuracy in an expert system for diagnosing ear disease. The naive Bayes approach is implemented in this research because it may assume that each symptom is independent of one another and can thus be used to assess the probability of a condition based on the symptoms that emerge. The results of this study show that the expert system for diagnosing ear disease using the Nave Bayes method is built on a website using the PHP programming language and the database maintained by MySQL, and this application has been tested 10 times, with 9 test data appropriate and 1 test data not appropriate. As a result of testing this application, the accuracy value obtained is 90%.
Modified Alexnet Architecture for Classification of Cassava Based on Leaf Images Sholihin, Miftahus; Md Fudzee, Mohd Farhan; Ismail, Mohd Norasri; Wati, Efi Neo; Arshad, Mohamad Syafwan; Gusman, Taufik
JOIV : International Journal on Informatics Visualization Vol 8, No 3 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.3.2966

Abstract

The objective of this study is to address the drawbacks of conventional classification approaches through the implementation of deep learning, specifically a modified AlexNet. The primary aim of this study is to precisely categorize the four distinct varieties of cassava, namely Manggu, Gajah, Beracun, and Kapok. The cassava dataset was obtained from farmers in Lamongan, Indonesia, and was used as a source of information. Data collection on cassava leaves was carried out with agricultural research specialists. A total of 1,400 images are included in the dataset, with 350 images corresponding to each variety of cassava produced. The central focus of this research lies in a comprehensive evaluation of the modified AlexNet architecture's performance compared to the original AlexNet architecture for cassava classification. Multiple scenarios were examined, involving diverse combinations of learning rates and epochs, to thoroughly assess the robustness and adaptability of the proposed approach. Among the evaluation criteria that were rigorously examined were accuracy, recall, F1 score, and precision. These metrics were used to determine the predictive capabilities of the model as well as its potential utilization in the actual world. The results show that the modified AlexNet design has better performance than the original AlexNet for recall, accuracy, precision, and F-1 score, all achieving a rate of 87%. In situations where a learning rate of 0.0001 and an epoch count of 150 are utilized, the performance of the approach stands out significantly, displaying an excellent level of competency. Nevertheless, it is crucial to recognize that distinct fluctuations in performance were noted within particular contexts and with diverse learning rates.
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.
PERAMALAN SUHU UDARA MENGGUNAKAN ALGORITMA LONG SHORT TERM MEMORY Yulian Ansori; Arief Rahman; Febriyanti Darnis; Miftahus Sholihin
Informatika: Jurnal Teknik Informatika dan Multimedia Vol. 5 No. 1 (2025): MEI : JURNAL INFORMATIKA DAN MULTIMEDIA
Publisher : LPPM Politeknik Pratama Kendal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/informatika.v5i1.1033

Abstract

This study presents an air temperature forecasting model employing the Long Short-Term Memory (LSTM) algorithm to address the challenges posed by climate variability and extreme weather conditions. Historical daily temperature data from NASA POWER—collected between January 1, 2014, and December 31, 2024, in Serang City (totaling 4,018 records)—were used. The data were normalized using a min–max scaling technique and divided into training (70%) and testing (30%) sets. Multiple experimental scenarios were run by varying the number of training epochs and the hidden layer unit counts. The optimal configuration was achieved in Scenario 7, which incorporated two hidden layers, each with 50 units, and employed 30 epochs; this setup yielded a prediction accuracy of 98.4% with a Root Mean Squared Error (RMSE) of 27.11. The results indicate that the LSTM model effectively captures the seasonal variations and long-term trends in air temperature, making it a reliable tool for forecasting and supporting decision-making in climate adaptation strategies. Keywords: Air Temperature Forecasting, Long Short-Term Memory, Deep Learning, Climate Change, Data Normalization.
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