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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Ilmiah Matrik Jurnal Restikom : Riset Teknik Informatika dan Komputer Insand Comtech : Information Science and Computer Technology Journal The Indonesian Journal of Computer Science Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Pengabdian Masyarakat Al-Fatimah Joong-Ki
Jamilatul Badriyah
Universitas Madura
Religion Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Environmental Science Social Sciences

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Prediksi Curah Hujan Menggunakan Long Short Term Memory Jamilatul Badriyah; Arna Fariza; Tri Harsono
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 3 (2022): Juli 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i3.4008

Abstract

The importance of predicting rainfall in fields that require rainfall information such as in agriculture, transportation and industry. Prediction of rainfall with statistics is done to solve the problems of this paper, thus this paper proposes prediction of rainfall using Long Short Term Memory in the case study: Surabaya City. The data used is rainfall data at two Surabaya stations, namely the Perak Meteorological Station I and the Tanjung Perak Maritime Meteorology Station from 2015 to 2020. The prediction test was carried out using the Long Short Term Memory algorithm with accuracy measurement results MSE 0.489, MAE 0.537 and R2 0.497. from these results prove that the Long Short Term Memory algorithm is better than previous studies.
Penerapan Dimensi Reduksi Pada Machine Learning Dalam Klasifikasi Kanker Payudara Berdasarkan Parameter Medis Jamilatul Badriyah; Nilam Ramadhani; Agung Muliawan; Khanun Roisatul Ummah; Ata Amrullah
Jurnal RESTIKOM : Riset Teknik Informatika dan Komputer Vol 6 No 3 (2024): Desember
Publisher : Program Studi Teknik Informatika Universitas Nusa Putra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/restikom.v6i3.379

Abstract

Kanker payudara adalah salah satu penyakit mematikan yang menyerang wanita karena jaringan payudara tumbuh tidak terkendali. Penelitian ini bertujuan untuk menerapkan teknik machine learning dalam klasifikasi kanker payudara untuk mendukung diagnosis yang lebih cepat dan akurat. Data yang digunakan dalam penelitian ini mencakup berbagai parameter medis seperti panjang radius, cekungan, jumlah titik cekung, posisi simetri, dimensi fraktal, luas, kehalusan dan lainnya. Metode yang digunakan dalam penelitian ini meliputi teknik klasifikasi seperti Deep learning dan Neural Network dengan kombinasi dimensi reduksi menggunakan Principal Component Analysis (PCA). Penggunaan dimensi reduksi dalam mengurangi kompleksitas data dan meningkatkan kinerja model. Hasil dari penelitian ini menunjukkan bahwa dimensi reduksi menggunakan Principal Component Analysis pada machine learning dapat meningkatkan akurasi kinerja model dengan akurasi tertinggi 96,84 pada Deep Learning
Empowering Odheng Artisans through Strengthening Entrepreneurship and Branding of Traditional Products in West Pademawu Aulia, Ismi Fitri; Faris, Mohammad; Subhan, Subhan; Syahadatina, Rika; Hasaniyah, Alfi; Putri, Devi Lestari Pramita; Badriyah, Jamilatul
Jurnal Pengabdian Masyarakat Al-Fatimah Vol. 2 No. 1 (2025): Edisi III, Juni 2025
Publisher : Institut Agama Islam Al-Fatimah Bojonegoro

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

Abstract

Odheng craftsmanship is a distinctive cultural heritage of Madura that continues to be preserved; however, it faces significant challenges in the modern era, particularly in terms of business management and marketing. In West Pademawu Village, Pamekasan Regency, most artisans still operate their businesses conventionally, lacking adequate knowledge of entrepreneurship and product branding strategies. This community service program aims to empower odheng artisans by strengthening their entrepreneurial capacity and developing product branding. The implementation method consists of three stages: preparation, implementation, and evaluation. Activities were carried out participatively through counseling, training, and direct mentoring approaches. The results show an increase in participants' motivation and understanding related to business management and basic financial recordkeeping. Furthermore, the artisans have begun to utilize digital platforms such as Instagram, Facebook, and marketplaces (Shopee, TikTok Shop) for product promotion and sales. Evaluation was conducted through online monitoring and indicated that the targets for participation, skills improvement, and sustainability were significantly achieved. This program demonstrates that training- and mentoring-based interventions can enhance the competitiveness of local products and promote community economic independence. Through the integration of local and digital approaches, odheng product branding has been successfully improved, transforming it not only into a cultural symbol but also into a valuable economic commodity
EFEKTIVITAS SISTEM PENGELOLAAN TIKET ELEKTORNIK DI KAWASAN WISATA LOKAL BERBASIS QR CODE Rachman, Anang Faktchur; Rachmatullah, Sholeh; Badriyah, Jamilatul; Mansyur, Muhammad Umar; Wirayanti, Sri
Insand Comtech : Information Science and Computer Technology Journal Vol 10, No 1 (2025): Insand Comtech
Publisher : Universitas Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53712/jic.v10i1.2629

Abstract

Kawasan wisata lokal saat ini menjadi tujuan destinasi wisata yang menarik minat masyarak domestik. Kawasan wisata lokal telah menyaksikan peningkatan besar dalam jumlah pengunjung dalam beberapa tahun terakhir. Namun, pengelolaan area wisata ini masih menghadapi beberapa kendala, seperti antrian panjang untuk membeli tiket dan setiap pengunjung mendapatkan 1 tiket yang berakibat pemborosan kertas tiket serta  pengumpulan data kunjungan yang tidak efektif. Tujuan penelitian ini adalah untuk menjelaskan pentingnya efektifitas penggunaan sistem tiket elektronik untuk mengelola kawasan wisata lokal. Teknologi digital yang digununakan berbasis QR Code ini memungkinkan pengunjung membeli tiket melalui internet, menghindari antrian panjang, penghematan kertas tiket, dan mempercepat proses masuk ke kawasan wisata. metodelogi yang digunakan untuk pengembangkan sistem ini dengan pendekatan Systems development life cycle (SDLC). Sistem ini menunjukkan bagaimana teknologi dapat digunakan untuk meningkatkan efisiensi operasional dalam pengelolaan tiket, rekap data kunjungan dengan lebih akurat dan efisien yang memungkinkan pengambilan keputusan dan analisis yang lebih baik. Hasilnya pengunjung dapat mengakses kawasan wisata lokal dengan lebih cepat dan mudah tanpa harus menunggu lama untuk membeli tiket melalui sistem pengelolaan tiket elektronik.
Analisis Perbandingan Performa Model ConvLSTM dan LRCN dalam Pengenalan Aktivitas Gerak Manusia Amir Hamzah; Jamilatul Badriyah
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 3 No. 3 (2025): Agustus : Neptunus : Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v3i3.991

Abstract

This study compares the performance of two deep learning models, namely Convolutional Long Short-Term Memory (ConvLSTM) and Long-term Recurrent Convolutional Network (LRCN), in the task of recognizing human activity from videos. Human activity recognition is an important field in computer vision with many applications, such as security monitoring, human-computer interaction, and social media-based video analysis. ConvLSTM is a model that combines convolution operations with long-term memory LSTM, thus capable of capturing spatial and temporal information simultaneously. This approach is ideal for processing video data sequences that have spatial and temporal dimensions. On the other hand, LRCN combines the power of spatial feature extraction from Convolutional Neural Network (CNN) and temporal sequence modeling through Recurrent Neural Network (RNN), specifically LSTM, to understand movement patterns in videos. The study used the UCF50 dataset consisting of 50 activity classes, but was limited to five classes for the focus of the experiment. The dataset was divided into 80% for training and 20% for testing, and the model was drilled for 50 epochs using early stopping to prevent overfitting. The results show that both models have high training performance. ConvLSTM achieved a training accuracy of around 98% and a validation accuracy of 90%, while LRCN achieved a training accuracy of 99.5% and a validation accuracy of 88%. Although ConvLSTM demonstrated good stability on the validation data, further testing using TikTok videos as real-world data showed that LRCN had a higher confidence level in recognizing activities, with most predictions achieving confidence scores above 80%. This difference in performance indicates that while ConvLSTM excels in generalizing on training data, LRCN is more robust to real-world data variations.
Optimasi Kontras Dan Ketajaman Citra Pada Pengenalan Makanan Indonesia Berbasis Machine Learning Ummah, Khanun Roisatul; Priyawati, Diah; Badriyah, Jamilatul
Jurnal Ilmiah Matrik Vol. 27 No. 2 (2025): Jurnal Ilmiah Matrik
Publisher : Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/g9afej42

Abstract

Indonesia has a rich culinary diversity, encompassing various types of food from different regions. In the current era of technological advancement, the application of artificial intelligence has grown significantly across multiple sectors, including in the identification of Indonesian food images. This research provides the impact of various image preprocessing techniques on the AI-based food identification system. The preprocessing methods examined include Zero Component Analysis (ZCA), Histogram Equalization (HE), Contrast Stretching, and Image Sharpening. The evaluation of these preprocessing methods was conducted to determine which technique provides the best performance in assisting the identification of Indonesian food using a Convolutional Neural Network (CNN) with a ResNet-50 transfer learning model. Performance measurement was carried out using a confusion matrix by calculating Accuracy, precision, recall, and F1-score. The results of this research show that the use of the Image Sharpening method yields higher accuracy and precision on the testing data compared to other methods, those are 0.9748 and 0.98, respectively. Next, a high level of accuracy was also demonstrated by the Contrast Stretching method, with an accuracy score of 0.9712.
Analysis of Gamification Implementation on Student Motivation and Learning Outcomes Burhan, Rifa'atul Mahmudah; Jamilatul Badriyah
The Indonesian Journal of Computer Science Vol. 14 No. 5 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i5.4995

Abstract

This study aims to analyze the effect of applying gamification methods on student motivation and learning outcomes in computer architecture and organization courses. The study was conducted using a quantitative approach with an experimental design to obtain valid data. Based on the research conducted, it can be concluded that the application of gamification methods has a significant positive impact on student motivation and understanding. Specifically, the use of gamification increased the average motivation score by 27.3, compared to an increase of 6.1 in conditions without gamification. Similarly, the aspect of understanding experienced an average increase of 27.1 with the application of gamification, while without gamification it only reached 5.4. In general, the results of this study indicate that the use of gamification in the learning process has a greater impact on increasing student motivation and understanding compared to conventional learning methods without gamification.
Pemberdayaan Masyarakat Pesisir Melalui Diversifikasi Produk Olahan Hasil Laut Di Desa Padelegan, Pamekasan Rina Susanti; Jamilatul Badriyah; Rayyan Muhammad
Joong-Ki : Jurnal Pengabdian Masyarakat Vol. 5 No. 1: November 2025
Publisher : CV. Ulil Albab Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/joongki.v5i1.11888

Abstract

Masyarakat pesisir Desa Padelegan, Kecamatan Pademawu, Kabupaten Pamekasan, sebagian besar bermata pencaharian sebagai nelayan tradisional dengan pendapatan yang fluktuatif dan relatif rendah. Hasil tangkapan mereka umumnya dijual segar, sehingga nilai tambahnya sangat terbatas. Kondisi ini diperparah oleh keterbatasan keterampilan pengolahan, minimnya literasi kewirausahaan, dan akses pasar lokal. Oleh karena itu, diperlukan strategi pemberdayaan berbasis diversifikasi produk olahan laut untuk meningkatkan kapasitas ekonomi masyarakat. Kegiatan pengabdian kepada masyarakat ini dilaksanakan dengan pendekatan partisipatif melalui beberapa tahapan, meliputi: (1) persiapan berupa survei kebutuhan dan diskusi kelompok terfokus (FGD), (2) pelatihan teknis pembuatan produk olahan seperti abon ikan, kerupuk ikan, nugget ikan, dan bakso ikan, (3) pendampingan manajerial terkait pencatatan keuangan, pengemasan, dan sertifikasi halal/PIRT, serta (4) pemasaran melalui media sosial, marketplace lokal, dan kerja sama dengan koperasi desa. Evaluasi dilakukan dengan metode pre-test dan post-test untuk menilai keterampilan, analisis sensori produk, dan perbandingan pendapatan sebelum dan sesudah program. Hasil kegiatan menunjukkan peningkatan signifikan dalam keterampilan teknis dan manajerial masyarakat, dengan skor rata-rata pra-tes 45 meningkat menjadi 82 pada pasca-tes. Pendapatan rata-rata per rumah tangga peserta meningkat sekitar 25–30%, dari £70 menjadi £100–£110 per bulan. Pengujian sensoris menunjukkan bahwa nugget ikan menerima skor tertinggi untuk rasa (4,6), sementara kerupuk ikan unggul dalam hal tekstur (4,5). Selain itu, kelompok usaha bersama bernama Padelegan Sejahtera dibentuk, memperkuat lembaga ekonomi lokal. Kesimpulannya, diversifikasi produk laut telah terbukti efektif dalam meningkatkan keterampilan, pendapatan, dan kemandirian usaha masyarakat pesisir. Untuk keberlanjutan, dukungan lintas sektor, penguatan sertifikasi mutu, dan lembaga lokal diperlukan agar bisnis masyarakat dapat berkembang lebih kompetitif.
Co-Authors Agung Muliawan Amir Hamzah Arna Fariza Ata Amrullah Aulia, Ismi Fitri Burhan, Rifa'atul Mahmudah Diah Priyawati Hasaniyah, Alfi Khanun Roisatul Ummah Mansyur, Muhammad Umar Mohammad Faris, Mohammad Putri, Devi lestari Pramita Rachman, Anang Faktchur Rachmatullah, Sholeh Ramadhani, Nilam Rayyan Muhammad Rina Susanti Subhan Subhan Syahadatina, Rika Tri Harsono Wirayanti, Sri