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Gedung Fakultas Sains dan Teknologi Lt. 4 Jurusan Teknik Informatika Jl. A.H. Nasution No. 105 Cibiru Bandung 40614 Telp. (022) 7800525 / Fax (022) 7803936 Email : jurnal@if.uinsgd.ac.id
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JOIN (Jurnal Online Informatika)
Published by Universitas Islam Negeri Sunan Gunung Djati Bandung
ISSN : 25281682     EISSN : 25279165     DOI : 10.15575/join
Core Subject : Science,
Computer Science & IT
JOIN (Jurnal Online Informatika) is a scientific journal published by the Department of Informatics UIN Sunan Gunung Djati Bandung. This journal contains scientific papers from Academics, Researchers, and Practitioners about research on informatics. JOIN (Jurnal Online Informatika) is published twice a year in June and December. The paper is an original script and has a research base on Informatics.
Arjuna Subject : -
Articles 490 Documents
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YOLOv5 and U-Net-based Character Detection for Nusantara Script Agi Prasetiadi; Julian Saputra; Iqsyahiro Kresna; Imada Ramadhanti
JOIN (Jurnal Online Informatika) Vol 8 No 2 (2023)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v8i2.1180

Abstract

Indonesia boasts a diverse range of indigenous scripts, called Nusantara scripts, which encompass Bali, Batak, Bugis, Javanese, Kawi, Kerinci, Lampung, Pallava, Rejang, and Sundanese scripts. However, prevailing character detection techniques predominantly cater to Latin or Chinese scripts. In an extension of our prior work, which concentrated on the classification of script types and character recognition within Nusantara script systems, this study advances our research by integrating object detection techniques, employing the YOLOv5 model, and enhancing performance through the incorporation of the U-Net model to facilitate the pinpointing of fundamental Nusantara script's character locations within input document images. Subsequently, our investigation delves into rearranging these character positions in alignment with the distinctive styles of Nusantara scripts. Experimental results reveal YOLOv5's performance, yielding a loss rate of approximately 0.05 in character location detection. Concurrently, the U-Net model exhibits an accuracy ranging from 75% to 90% for predicting character regions. While YOLOv5 may not achieve flawless detection of all Nusantara scripts, integrating the U-Net model significantly enhances the detection rate by 1.2%.
Retweet Prediction Using Multi-Layer Perceptron Optimized by The Swarm Intelligence Algorithm Jondri Jondri; Indwiarti Indwiarti; Dyas Puspandari
JOIN (Jurnal Online Informatika) Vol 8 No 2 (2023)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v8i2.1193

Abstract

Retweets are a way to spread information on Twitter. A tweet is affected by several features which determine whether a tweet will be retweeted or not. In this research, we discuss the features that influence the spread of a tweet. These features are user-based, time-based and content-based. User-based features are related to the user who tweeted, time-based features are related to when the tweet was uploaded, while content-based features are features related to the content of the tweet. The classifier used to predict whether a tweet will be retweeted is Multi Layer Perceptron (MLP) and MLP which is optimized by the swarm intelligence algorithm. In this research, data from Indonesian Twitter users with the hashtag FIFA U-20 was used. The results of this research show that the most influential feature in determining whether a tweet will be retweeted or not is the content-based feature. Furthermore, it was found that the MLP optimized with the swarm intelligence algorithm had better performance compared to the MLP.
Optimizing YOLOv8 for Real-Time CCTV Surveillance: A Trade-off Between Speed and Accuracy Muhammad Rizqi Sholahuddin; Maisevli Harika; Iwan Awaludin; Yunita Citra Dewi; Fachri Dhia Fauzan; Bima Putra Sudimulya; Vandha Pradiyasma Widarta
JOIN (Jurnal Online Informatika) Vol 8 No 2 (2023)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v8i2.1196

Abstract

Real-time video surveillance, especially CCTV systems, requires fast and accurate face detection. Object detection models with slow inference times are ineffective in real-time. This study addresses this challenge by improving the inference speed of the YOLOv8 model, a leading object detection framework known for its accuracy and speed. We focus on pruning the model's architecture, particularly the P5 head section, which detects larger objects. According to Bochkovskiy's 2020 research, this modification enhances the model's performance specifically for medium and small objects in CCTV footage. The standard YOLOv8 model and its modified version were compared for inference time, mean Average Precision (mAP), and model weight. The pruned YOLOv8 model cuts inference time by 15.56%, from 4.5 ms to 3.8 ms, and reduces model weight. The advantages mentioned above are offset by a 1.6% decrease in mean average precision. This research advances object detection technology by demonstrating architectural modifications' efficacy. These changes make the model faster and lighter, making it suitable for real-time surveillance. The accuracy trade-off is slight. The implications of these findings are crucial for implementing efficient object detection systems in CCTV surveillance. These findings also lay the groundwork for future research to improve such systems' speed-accuracy trade-off.
Classification of Bulughul Maraam Categories: Prohibitions, Recommendations, and Information Using Extreme Learning Machine and Fasttext Rissa Handayani; Ina Najiyah; Dirga Wisnuwardana
JOIN (Jurnal Online Informatika) Vol 8 No 2 (2023)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v8i2.1205

Abstract

Hadith is the second source of Islamic law after the Quran. After the hadiths were compiled, Imam of Hadith created collections of hadiths, one of which is Imam Bukhari who compiled the book Bulughul Maraam, which is considered to have the highest level of authenticity. Digital collections of hadiths can now be found in the form of e-books and web pages, which help in the search for hadiths. The classification of hadiths is necessary to organize them by category, making it easier to search for hadiths based on their categories. Text mining is needed to classify hadiths because it can identify patterns in unstructured text. This research aims to improve the accuracy of classifying recommended, prohibited, and informational hadiths using a dataset of 7008 hadiths, which consists of primary data taken from the book Bulughul Maraam in the Indonesian language. Previously, similar research was conducted in 2017 that classified recommended, prohibited, and obligatory hadiths with an accuracy of 85%, but only for Sahih Bukhari hadiths. In this research, the same classification categories will be examined, proposing a different method, namely the Extreme Learning Machine method and Word2vec Fasttext for text representation with a larger dataset. The results of this research show a model accuracy of 86.31%, 86% precision, and 87% recall, indicating that the proposed model performs well in classifying hadiths.
Analisis Kinerja Kompresi Citra Digital dengan Komparasi DWT, DCT dan Hybrid (DWT-DCT) Faza, Aditya Mahmud; Slamet, Cepy; Nursantika, Dian
JOIN (Jurnal Online Informatika) Vol 1 No 1 (2016)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v1i1.3

Abstract

Penelitian ini merupakan penelitian tentang penerapan transformasi diskrit kosinus (DCT), transformasi wavelet diskrit (DWT), dan hybrid sebagai penggabungan dari kedua transformasi sebelumnya dalam proses kompresi data citra digital. Proses kompresi dilakukan untuk menekan konsumsi sumber daya memory, mempercepat proses transmisi citra digital. Proses kompresi yang dilakukan dapat menghasilkan nilai mean square, peak signal to noise ratio dan waktu yang dibutuhkan untuk proses kompresi dari masing-masing transformasi. Nilai tersebut sebagai parameter untuk tahap komparasi kompresi sehingga pengguna dapat menentukan kinerja kompresi dari setiap transformasi dan dapat menentukan jenis transformasi yang paling baik digunakan untuk proses citra digital.
Implementasi Algoritma Ant Colony Optimization pada Aplikasi Pencarian Lokasi Tempat Ibadah Terdekat di Kota Bandung Zarman, Andri; Irfan, Mohamad; Uriawan, Wisnu
JOIN (Jurnal Online Informatika) Vol 1 No 1 (2016)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v1i1.4

Abstract

Indonesia merupakan negara yang penduduknya memeluk berbagai agama, yaitu di antaranya agama: Islam, Kriten, Budha, Hindu. Bandung merupakan kota yang banyak wisatawannya, baik wisatawan lokal maupun mancanegara, fasilitas umum yang ada di Kota Bandung dibutuhkan, salah satunya tempat ibadah. Informasi tentang tempat ibadah cukup diperlukan oleh para wisatawan, karena cukup sulit mendapatkan informasi tempat ibadah di Kota Bandung, khususnya sulit dalam mendapatkan rute terdekat (shourtest paht) menuju tempat ibadah tersebut. Penelitian ini dibuat untuk merancang sebuah aplikasi yang memberikan informasi serta petunjuk arah tempat ibadah di Kota Bandung, dengan menerapkan Algoritma Ant Colony Optimization. Aplikasi ini digunakan pada perangkat Smatrphone/Android, oleh karena itu, aplikasi ini cukup flexibel untuk digunakan. Aplikasi ini menggunakan dukungan web service, sehingga data mudah di inputkan oleh admin.
Implementasi Algoritma Divide And Conquer Pada Aplikasi Belajar Ilmu Tajwid Dais Suryani; Mohamad Irfan; Wisnu Uriawan; Wildan Budiawan Zulfikar
JOIN (Jurnal Online Informatika) Vol 1 No 1 (2016)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v1i1.5

Abstract

Seorang muslim harus bisa membaca ayat-ayat Al-Quran dengan baik sesuai yang diajarkan oleh Rasulullah saw. Membaca Al-Quran sesuai ilmu tajwid hukumnya wajib bagi setiap orang, tidak bisa diwakili oleh orang lain. Aplikasi ilmu tajwid yang dibangun bersifat mobile, sehingga user dapat mempelajari tajwid dimana saja dan kapan saja. Selain menambah wawasan tentang tajwid, user dapat membaca Al-Quran secara fasih sesuai hukum tajwid karena aplikasi yang bersifat mobile ini mendukung pembelajaran menggunakan teks dan suara. Selain itu user dapat juga mengasah  kemampuannya tentang ilmu tajwid melalui soal-soal yang ada dalam aplikasi. Aplikasi Belajar Ilmu Tajwid menerapkan salah satu algoritma yaitu divide and conquer. Algoritma divide and conquer diimplementasikan pada pencarian jawaban pada soal yang ada pada menu latihan. Algoritma divide and conquer mempunyai cara kerja membagi masalah menjadi beberapa sub masalah sehingga dihasilkan solusi akhir dari masalah awal. Algoritma divide and conquer mempunyai kompleksitas yang cukup cepat yaitu 2,86272753, dibandingkan dengan algoritma Brute Force yang memiliki kompleksitas lebih tinggi daripada algoritma divide and conquer yaitu 6.
Sistem Klasifikasi Jenis Tanaman Hias Daun Philodendron Menggunakan Metode K-Nearest Neighboor (KNN) Berdasarkan Nilai Hue, Saturation, Value (HSV) Syahid, Dani; Jumadi, Jumadi; Nursantika, Dian
JOIN (Jurnal Online Informatika) Vol 1 No 1 (2016)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v1i1.6

Abstract

Tanaman hias daun biasa digunakan untuk mempercantik halaman pekarangan rumah dengan aneka warna yang indah pada tanaman hias daun ini menjadi bahan perhatian khususnya bagi pecinta tanaman. Namun dengan banyaknya jenis tanaman hias membuat kita sulit untuk mengetahui nama tumbuhan yang kita minati.Sistem pendeteksi citra tanaman hias daun bekerja dengan cara membandingkan data citra latih yang telah tersimpan pada database terhadap data citra yang akan diuji. Data citra uji akan diklasifikasikan dengan menggunakan penerapan metode K-Nearest Neighboor yaitu berfungsi untuk menghitung jarak terdekat antara data citra latih dan data citra uji pada setiap pikselnya. Setiap piksel pada citra akan dilakukan proses konversi red, Green, Blue (RGB) ke dalam ekstraksi fitur warna hue, saturation, value (HSV) terlebih dahulu. Setelah didapat nilai HSV, maka dilakukan proses klasifikasi menggunakan metode KNN. Data sampel pada penelitian ini menggunakan 5 klasifikasi citra data latih dengan 10 data citra  uji pada setiap data citra latih. Pada penelitian ini, diperoleh hasil dari akurasi sistem pendeteksi citra tanaman dengan hasil mencapai 92%.
Klasifikasi Terjemahan Ayat Al-Quran Tentang Ilmu Sains Menggunakan Algoritma Decision Tree Berbasis Mobile Devi Setiawati; Ichsan Taufik; Jumadi Jumadi; Wildan Budiawan Zulfikar
JOIN (Jurnal Online Informatika) Vol 1 No 1 (2016)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v1i1.7

Abstract

The number of verses of the Quran contained in the Qur'an, encouraging people to look for a way to get the exact clause in a short time. The science is an important knowledge, as Muslims we are obliged to study it with the Al-Quran as a guide. So that's how we get the verse about the science of the Quran with a quick, efficient and practical with a mobile application. Decision tree is a predictive model using a tree or hierarchical structure, this method can support mobile applications to be created. Because based decision very complex and global in the Quran, can be transformed into more simple and specific. C4.5 algorithm is a decision tree induction algorithm and is suitable to perform the classification process. The results of the percentage of successful applications created by using a decision tree that is 75.73%. From these results is known that the algorithm C4.5 and decision tree reasonably is well used in the classification process.
Implementasi Teknologi Augmented Reality pada Buku Panduan Wudhu Berbasis Mobile Android Setiawan, Erwin; Syaripudin, Undang; Gerhana, Yana Aditia
JOIN (Jurnal Online Informatika) Vol 1 No 1 (2016)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v1i1.8

Abstract

Augmented Reality (AR) adalah teknologi interaktif yang mampu memproyeksikan objek maya ke dalam objek nyata secara real time. Perkembangan teknologi AR dewasa ini telah memberikan banyak kontribusi ke dalam berbagai bidang. Salah satu implementasi AR di bidang edukasi adalah AR Book. Buku merupakan salah satu media pembelajaran yang banyak digunakan. Selain itu, buku juga digunakan sebagai alat berkomunikasi oleh guru maupun orang tua terhadap anak-anak, misalkan seperti jenis buku panduan mengenai tatacara wudhu. Wudhu adalah suatu bentuk peribadatan kepada Allah Ta’ala dengan mencuci anggota tubuh tertentu dengan tata cara yang khusus. Wudhu khususnya diperintahkan sebelum melaksanakan ibadah shalat dan thawaf. Umat muslim harus mengetahui tatacara berwudhu yang benar. Salah satu sistem operasi yang digunakan pada mobile phone atau smartphone yaitu Android. Android adalah sebuah sistem operasi untuk perangkat mobile yang berbasis Linux dan bersifat open source. Dengan memanfaatkan media mobile untuk membangun aplikasi menggunakan teknologi augmented reality sebagai media pembelajaran, aplikasi AR berbasis mobile mempunyai keunggulan karena sifatnya yang mudah berpindah

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