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All Journal Pixel : Jurnal Ilmiah Komputer Grafis INOVTEK Polbeng - Seri Informatika Jurnal Eksplora Informatika Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Nasional Komputasi dan Teknologi Informasi JATI (Jurnal Mahasiswa Teknik Informatika) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Jurnal Restikom : Riset Teknik Informatika dan Komputer Jurnal Pendidikan dan Teknologi Indonesia Indexia Jurnal Abdi Masyarakat Indonesia Jurnal Algoritma Jurnal Sains Informatika Terapan (JSIT) KREATIF: Jurnal Pengabdian Masyarakat Nusantara Sewagati: Jurnal Pengabdian Masyarakat Indonesia Profit: Jurnal Manajemen, Bisnis dan Akuntansi Jurnal Ilmiah Teknik Informatika dan Komunikasi Jurnal Inovatif Wira Wacana Indonesian Vocational Research Journal Jurnal TEFSIN ( Jurnal Teknik Informatika dan Sistem Informasi) Kohesi: Jurnal Sains dan Teknologi Jurnal Pengabdian Masyarakat dan Lingkungan Saber: Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi Jurnal Informatika dan Teknik Elektro JURNAL TEKNIK INFORMATIKA DAN KOMPUTER Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Repeater: Publikasi Teknik Informatika dan Jaringan SISFOTENIKA Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika Saturnus: Jurnal Teknologi dan Sistem Informasi FRAMEWORK Jurnal Ilmu Komputer dan Informatika Proceeding Maritime Business Management Conference KREATIF: Jurnal Pengabdian Masyarakat Nusantara Semar: Jurnal Pengabdian Kepada Masyarakat
Soffiana Agustin, Soffiana
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Klasifikasi Citra Batik Menggunakan Local Binary Pattern (LBP) dan Support Vector Machine (SVM) Fatimah, Nuris Sayyidatul; Agustin, Soffiana
Jurnal Algoritma Vol 22 No 1 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-1.2208

Abstract

Image classification is one of the important branches in digital image processing that aims to recognize and classify objects based on certain features. This research seeks to preserve Indonesian batik culture through digital documents of batik motifs that can be applied in museums and research institutions. The main objective of this research is to overcome the difficulty in classifying batik motifs by applying Local Binary Pattern (LBP) as a feature extraction technique and Support Vector Machine (SVM) as a classification algorithm. The batik motifs used are Batik Kawung, Batik Megamendung, and Batik Parang. By using 720 batik images. This research was conducted in four main stages, namely pre-processing, feature extraction, classification and evaluation. The results showed an accuracy of 88.89%, with varying precision, recall, and F1-Score. The results show that texture analysis extracted through LBP contributes significantly to the accuracy of batik motif recognition.
Implementasi Sistem Pergudangan Pada PT Graha Sarana Gresik Berbasis Website Izzul Haq, Fajri; Agustin, Soffiana
Jurnal Inovatif Vol. 4 No. 01 (2025): April 2025
Publisher : Universitas Kristen Wira Wacana Sumba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58300/inovatif.v4i01.1100

Abstract

Sistem pergudangan merupakan salah satu elemen penting dalam mendukung efisiensi operasional perusahaan. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem informasi pergudangan berbasis web yang mampu meningkatkan efisiensi operasional serta memastikan transparansi dan akurasi dalam pengelolaan data pengajuan barang. Metodologi yang digunakan adalah SDLC (System Development Life Cycle) dengan pendekatan iteratif, dimulai dari analisis kebutuhan hingga implementasi sistem. Sistem ini dirancang untuk mendukung pembuatan pengajuan barang oleh Kepala Gudang, validasi berlapis oleh Kepala Divisi dan Direktur Operation, dan pencetakan dokumen pengajuan setelah disetujui. Hasil penelitian menunjukkan bahwa sistem berhasil meningkatkan efisiensi dan struktur dalam alur kerja pengajuan, memberikan manfaat nyata dalam pengelolaan pergudangan. Dengan sistem ini, proses pengajuan menjadi lebih terorganisir dan transparan, sehingga mendukung kebutuhan operasional perusahaan secara keseluruhan.
Feature Extraction using Histogram of Oriented Gradients and Moments with Random Forest Classification for Batik Pattern Detection Azizah, Wafiq; Agustin, Soffiana
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 1 (2025): JANUARY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v14i1.2225

Abstract

The preservation of traditional batik patterns, often transmitted orally and through direct practice across generations, faces significant challenges in the modern era. Globalization introduces the risk of cultural homogenization, potentially diminishing the uniqueness and diversity of these patterns. Furthermore, the manual recognition of batik motifs is labor- intensive, time-consuming, and requires specialized expertise, rendering it unsuitable for large-scale preservation initiatives. Consequently, the development of technology-based solutions capable of documenting, analyzing, and recognizing batik patterns with efficiency and precision is imperative for safeguarding this cultural heritage. This study aims to address these challenges by developing an automated system for recognizing batik patterns, focusing on Javanese batik motifs—Kawung, Megamendung, and Parang—which serve as foundational designs for the evolution of batik in other regions. The proposed methodology integrates two feature extraction techniques, Histogram of Oriented Gradients (HOG) and Texture Moments, with the Random Forest machine learning algorithm. The research process encompasses four key stages: pre-processing, feature extraction, classification, and system evaluation, where the accuracy of individual and combined feature extraction methods is analyzed. Experimental results reveal that the HOG method achieves an accuracy of 78.99%, while the Texture Moments method yields 81.88%. Notably, the combination of these two methods enhances system performance, achieving the highest accuracy of 86.23%, representing a 4.65% improvement over the single methods. These findings underscore the efficacy of integrating HOG and Texture Moments with the Random Forest algorithm for automated batik pattern recognition.
Implementasi Metode Optical Character Recognition (OCR) untuk Deteksi Karakter pada Citra Plat Nomor Kendaraan Bermotor Mohammad Ridwan Bayu Pratama; Asrorul Faradis; Soffiana Agustin
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 4 (2025): Juli : Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i4.938

Abstract

Manual collection of vehicle license plates is often inefficient and prone to errors, so an automatic identification system is needed. This research aims to implement and evaluate the performance of a license plate character detection system, focusing on the accuracy comparison between black and white base plates in Indonesia. The method used is Optical Character Recognition (OCR) with image preprocessing workflow including Grayscale, Gaussian Blur, and edge detection implemented in Google Colab. The system was tested using 100 primary data samples consisting of 50 black base plates and 50 white base plates. The findings showed that the system achieved a combined average accuracy of 84.36%. Specifically, it was found that the accuracy on the black base plate (85.40%) was slightly superior to that on the white base plate (83.32%). The implication of this study is that the change in license plate standards has a measurable technical impact on the ANPR system, where the findings can serve as a foundation for developers to calibrate the system to be reliable on both plate types during the transition period.
Peramalan Harga Bitcoin Menggunakan Metode Moving Average Asrorul Faradis; Raditya Thabroni Romadhon; Soffiana Agustin
Saturnus: Jurnal Teknologi dan Sistem Informasi Vol. 3 No. 3 (2025): Juli: Saturnus: Jurnal Teknologi dan Sistem Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/saturnus.v3i3.952

Abstract

Bitcoin is one of the most prominent digital assets in the modern financial era due to its high volatility and huge profit potential. However, its extreme price volatility also makes it a high-risk asset, so a reliable forecasting approach is needed to help investors make more rational decisions. This study aims to forecast Bitcoin price using the Moving Average (MA) method, specifically MA3, by utilizing monthly historical data of Bitcoin price in USD currency obtained from investing.com website. The MA3 method was chosen for its ability to smooth out short-term fluctuations and identify the direction of price trends. The forecasting process is performed by calculating the average of the last three months' prices for each point in time and compared to the actual price to evaluate its accuracy. The evaluation is done using various prediction error metrics, namely Error, Absolute Error, Squared Error, and Percentage Error. The results of the analysis show that the MA method provides a fairly representative picture of price trends and can be used as an early indicator in short-term investment strategies. Thus, the Moving Average method proves to be a simple but effective prediction tool, especially for novice investors in the dynamic crypto asset market.
Perbandingan Metode Monte Carlo dan Single Moving Average dalam Memprediksi Penjualan di Toko Shokifatin Cahyani Putri, Erna Dwita Sari; Syah Putra, Muhammad Madavi; Agustin, Soffiana
Framework : Jurnal Ilmu Komputer dan Informatika Vol 3 No 02 (2025): Framework : Jurnal Teknik Informatika
Publisher : Universitas Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33506/framework.v3i02.4571

Abstract

Kebutuhan rumah tangga akan Minyak, gas LPG, dan bensin sangat penting untuk aktivitas sehari-hari. Hal ini membuka peluang bisnis bagi retailer dalam menyediakan produk-produk tersebut, seperti Toko Shokifatin. Namun, penjualan di toko ini bersifat fluktuatif, kadang tinggi dalam satu hari dan bisa juga tidak ada penjualan sama sekali di hari lain. Ketidakpastian ini menyulitkan pengelola toko untuk menentukan waktu dan jumlah restok yang tepat. Penelitian ini bertujuan membandingkan dua metode peramalan penjualan, yakni metode Monte Carlo dan metode Single Moving Average. Pendekatan kuantitatif digunakan dengan data penjualan Toko Shokifatin sebagai bahan analisis. Berdasarkan hasil penelitian, diketahui bahwa kedua metode mampu melakukan peramalan dengan baik. berdasarkan nilai Error(Tingkat kesalahan) Dengan demikian, metode Single Moving Average direkomendasikan sebagai pendekatan peramalan yang lebih akurat untuk mendukung pengelolaan stok di Toko Shokifatin.
Deteksi Penyakit Daun Tomat Berbasis Warna Dan Tekstur Dengan Algoritma K-Nearest Neighbor : Deteksi Penyakit Daun Tomat Berbasis Warna Dan Tekstur Dengan Algoritma K-Nearest Neighbor Cahyani Putri, Erna Dwita Sari; Syah Putra, Muhammad Madavi; Agustin, Soffiana
Framework : Jurnal Ilmu Komputer dan Informatika Vol 3 No 02 (2025): Framework : Jurnal Teknik Informatika
Publisher : Universitas Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33506/framework.v3i02.4644

Abstract

Penelitian klasifikasi penyakit daun tomat ini sangat penting dilakukan mengingat tomat (Solanum lycopersicum) merupakan salah satu komoditas hortikultura utama di Indonesia yang memiliki nilai ekonomi dan gizi tinggi. Namun, produktivitas tomat seringkali terancam oleh berbagai penyakit daun yang secara signifikan dapat menurunkan hasil panen dan berdampak negatif pada pendapatan petani serta suplai pangan nasional. Penelitian ini bertujuan untuk mengembangkan sistem deteksi penyakit daun tomat dengan menggunakan ekstraksi fitur tekstur berdasarkan Local Binary Pattern (LBP) Uniform serta fitur ruang warna HSV. Kedua fitur tersebut kemudian digabungkan untuk klasifikasi menggunakan algoritma K-Nearest Neighbor (KNN). Dataset berisi 200 citra daun tomat yang mencakup empat kelas penyakit berbeda, yang diambil dalam berbagai kondisi pencahayaan dan latar belakang untuk merefleksikan variasi nyata di lapangan. Hasil evaluasi menunjukkan bahwa fitur tekstur memberikan performa klasifikasi terbaik dengan akurasi maksimum 0,85 pada K=3, sedangkan fitur warna secara individual memiliki akurasi lebih rendah dan kurang stabil. Penggabungan kedua fitur ini mampu mempertahankan akurasi yang tinggi sekaligus meningkatkan kestabilan klasifikasi di beberapa kelas penyakit. Penelitian ini menunjukkan potensi signifikan dari penggabungan fitur tekstur dan warna dalam meningkatkan ketepatan deteksi penyakit daun tomat, yang diharapkan dapat mendukung pemantauan dan pengelolaan tanaman secara lebih efektif, serta berkontribusi pada pengembangan pertanian berkelanjutan di masa depan dengan dukungan teknologi terkini.
Pelatihan Ms. Power Point untuk Melatih Keterampilan Pengurus Daerah Aisyiyah Se Kabupaten Gresik Rakhma Devi, Putri Aisyiyah; Soffiana Agustin
Jurnal Pengabdian Masyarakat dan Lingkungan (JPML) Vol. 4 No. 1 (2025): Jurnal Pengabdian Masyarakat dan Lingkungan (JPML)
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30587/jpml.v4i1.9686

Abstract

The Microsoft PowerPoint presentation program for Aisyiyah members in Gresik Regency aims to improve digital literacy among women in Islamic community organizations. Through this training, participants will learn the basics of using PowerPoint, such as creating slides, inserting media, and using animations. The training format includes demonstrations, Q&A sessions, and practical exercises. The results of the activity showed that participants were highly motivated and able to apply the skills they learned to organizational activities. The training not only improved the technical skills of the women but also enabled them to carry out their organizational tasks more actively and professionally. This initiative is a strategic step to encourage the digitalization of organizations and strengthen the role of women in modern society.
Pengembangan Karakter Entrepreneur Siswa Melalui Pelatihan Kewirausahaan di SMK Inisial X di Gresik Akhmad Wasiur Rizqi; Elly Ismiyah; Soffiana Agustin; Ahmad Fauzal Ibnu Amalik; M. Fauzan Eksando Pramaisyah
SEWAGATI: Jurnal Pengabdian Masyarakat Indonesia Vol. 4 No. 3 (2025): September : Jurnal Pengabdian Masyarakat Indonesia
Publisher : BADAN PENERBIT STIEPARI PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56910/sewagati.v4i3.3081

Abstract

Entrepreneurship training is an effective solution to foster and develop entrepreneurial character in students. This community service activity was implemented at Initial X Vocational High School in Gresik Regency, addressing the issue of students’ limited understanding of entrepreneurship principles and practices, despite some having experience assisting in family businesses. The primary objective of this program was to enhance students' motivation, broaden their entrepreneurial insights, and equip them with essential entrepreneurial skills through structured training sessions. The method of implementation included a combination of lectures, interactive discussions, question and answer sessions, hands-on practice, and intensive mentoring. The training process was divided into several stages: a pre-test to assess initial knowledge, delivery of materials, field practice to apply the concepts, and a post-test to measure the progress of the participants. The success of the program was measured by the level of participation from the partners, the activeness of the participants during the training, and the increase in knowledge and skills after the sessions. The results indicated a significant improvement in students’ understanding of entrepreneurial concepts, with a noticeable growth in their entrepreneurial character. Moreover, the students showed an increase in motivation to pursue entrepreneurship and were more confident in managing and designing businesses effectively. Through this training, students developed a better grasp of business principles and practices, which will help them become more independent and capable of running their own businesses. This community service initiative not only equipped students with valuable entrepreneurial knowledge but also laid the foundation for them to pursue entrepreneurial ventures in the future, contributing to the development of a more entrepreneurial mindset among the youth in the region.
Pelatihan Kesadaran Lingkungan melalui Pemanfaatan Biopori dan Komposter bagi Jenjang SMK X Bungah Purwanto, Purwanto; Amalik, Ahmad Fauzal Ibnu; Rizqy, Nadaa Syifa Abyan; Ningrum, Dzakiah Widya; Rasyid, Harunur; Agustin, Soffiana
Jurnal Abdi Masyarakat Indonesia Vol 5 No 5 (2025): JAMSI - September 2025
Publisher : CV Firmos

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54082/jamsi.2146

Abstract

Pengelolaan sampah organik di sekolah menjadi salah satu indikator penting dalam mewujudkan pendidikan berkelanjutan dan penanaman jiwa cinta lingkungan volume sampah organik yang tinggi di SMK X Bungah menuntut adanya solusi berbasis partisipasi siswa. Kegiatan pengabdian ini bertujuan untuk meningkatkan kesadaran dan keterampilan siswa dalam mengelola sampah organik melalui penerapan teknologi lubang resapan biopori dan komposter. Metode yang digunakan adalah Focus Group Discussion (FGD), yang memungkinkan siswa mengidentifikasi masalah, merumuskan solusi, dan mempraktikkan langsung teknologi tersebut. Evaluasi dilakukan melalui pre-test dan post-test serta observasi keterampilan praktik. Hasil menunjukkan peningkatan pengetahuan siswa sebesar 78%, keterampilan praktik 82%, dan penurunan volume sampah organik di lingkungan sekolah. Peningkatan ini tidak hanya mencerminkan keberhasilan transfer pengetahuan, tetapi juga keberhasilan membangun kemampuan psikomotorik. Siswa tidak sebatas memahami teori, tetapi juga mampu menghasilkan produk nyata yang dapat langsung dimanfaatkan di lingkungan sekolah. Program ini diharapkan dapat menjadi model implementasi pendidikan lingkungan berbasis aksi di sekolah kejuruan, keberhasilan program menjadi peluang untuk integrasi pembentukan tim lingkungan sekolah, serta pengembangan kemitraan dengan pemerintah desa dalam mewujudkan pengelolaan sampah terpadu dan berkelanjutan.
Co-Authors AA Sudharmawan, AA Abdillah, Hanif Abyan Rizqy, Nadaa Syifa Ach Alfan Shahri Ahmad Fauzal Ibnu Amalik Ahmad Hendi Suffyan Hadi Ahmad Muzaki Ainul Faradisa Akhmad Wasiur Rizqi Al Husain, Gymnastiar Ishaq Amalik, Ahmad Fauzal Ibnu Ani Dijah Rahajoe Anita Sari arif arizal Asrorul Faradis AYU WULANDARI Azizah, Wafiq Bimantara Panji Saputra Cahyani Putri, Erna Dwita Sari Choyr Mukhlasin Candra Sakti Dano Fadilah Amelya Rizki Deny Andesta Dhidu Usrin Yadani Dhidu Usrin Yadani Elin Rosalin Elly Ismiyah Ernawati Ernawati Fahmi Fauzi Abdullah Fahmy Ardhiansyah Fahmy Ardhiansyah Fajar Wibowo, Cahyo Farhan Rizqullah Bagaskara Fatimah, Nuris Sayyidatul Fikrul Azizi, Muhammad Firda Mauludiyah Arfianti Firmansyah, Abdul Hafizh Gumilang, Agung Haq, Fajri Izzul Haris, Mohammad Harunur Rosyid Herlando Prayitno Ilham Teguh Prayudha Izzul Haq, Fajri Jaemsyien Devgan Oktawijaya Jatmiko, Wasis Putro LAILATUL FITRIA M. Fauzan Eksando Pramaisyah Maulana Ansaris, Fatur Maulana Feri Setyawan Maulana Firdaus Moch. Nuruddin Moh. Fahrudin Rifqi Moh. Jufriyanto Moh. Jufriyanto Mohammad Ridwan Bayu Pratama Muhammad Chozami Muhammad Fikri Anwar Muhammad Fikrul Azizi Muhammad Manu Muhammad Syaichuddin Muhammad Syaifudin Mujidah, Muna Nabilah Fitriani Naufal, Muhammad Nawwaf Ningrum, Dzakiah Widya Nisa', Widiana Kholisatun Nizam Masbakhi Zain Nur Afiq Eka Putra Nur Azizah Nuris Sayyidatul Fatimah Nurul Mudhofar Oktawijaya, Jaemsyien Devgan P. Eko Prasetyo Purwanto Purwanto Raditya Thabroni Romadhon Rahim, Nur Nafilah Rakhmadhan Rizky Brillian Rasyid, Harunur Rayhan, Ega Rifki, Achmad Rizqy, Nadaa Syifa Abyan Said Salim Dahdah Sanyoto, Ongky Dwi Setyawan, Maulana Feri Sirojul Qulub, Muhammad Syah Putra, Muhammad Madavi Syahbana, Ahmad Naufal Triyunita Nur Hayati Tsani, Ghalby Muhammad Tsaqofi Bintang Muslimah Tsaqofi Bintang Muslimah Umi Chotijah Wafiq Azizah Yulia Ayu Nastiti Yulia Rahmawati, Yulia