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All Journal Jurnal Algoritma JOIN (Jurnal Online Informatika) JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JTT (Jurnal Teknologi Terpadu) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal) Jurnal Algoritma Jurnal Pembelajaran, Bimbingan, dan Pengelolaan Pendidikan Journal of Law, Poliitic and Humanities SENTRI: Jurnal Riset Ilmiah Coreid Journal Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal) Integrated : Journal Of Information Technology and Vocational Education
Aldy Rialdy Atmadja
UIN Sunan Gunung Djati Bandung
Aerospace Engineering Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

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Sistem Pendukung Keputusan Penentu Dosen Penguji Dan Pembimbing Tugas Akhir Menggunakan Fuzzy Multiple Attribute Decision Making dengan Simple Additive Weighting (Studi Kasus: Jurusan Teknik Informatika UIN SGD Bandung) Septiana, Ian; Irfan, Mohamad; Atmadja, Aldy Rialdy; Subaeki, Beki
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.v1i1.10

Abstract

Penentuan dosen penguji dan pembimbing skripsi adalah hal yang harus dilakukan disetiap universitas untuk membantu mahasiswa dalam menyelesaikan skripsinya. Dalam menentukan hal tersebut kadang terjadi keputusan yang kurang optimal dimana dosen yang ditunjuk kurang sesuai dengan topik skripsi mahasiswa akibatnya dapat mengurangi kualitas karya ilmiah mahasiswa. Untuk memecahkan masalah tersebut maka dibutuhkan sistem pendukung keputusan yang dapat memberikan rekomendasi dosen penguji dan pembimbing. Salah satu metode yang dapat digunakan adalah FMADM (Fuzzy Multiple Attribute Decission Making). Proses penentuan rekomendasi dosen penguji dan pembimbing dilakukan dengan mencari alternatif terbaik berdasarkan kriteria-kriteria yang telah ditentukan melalui metode SAW (Sample Additive Weighting). Adapun metode FMADM dipilih karena mampu menyeleksi alternatif terbaik dari sejumlah alternatif. Dengan mencari nilai bobot untuk setiap atribut, kemudian dilakukan proses perangkingan yang menghasilkan alternatif yang optimal, untuk menentukan dosen penguji dan pembimbing
Comparison of Template Matching Algorithm and Feature Extraction Algorithm in Sundanese Script Transliteration Application using Optical Character Recognition Gerhana, Yana Aditia; Atmadja, Aldy Rialdy; Padilah, Muhamad Farid
JOIN (Jurnal Online Informatika) Vol 5 No 1 (2020)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v5i1.580

Abstract

The phenomenon that occurs in the area of West Java Province is that the people do not preserve their culture, especially regional literature, namely Sundanese script, in this digital era there is research on Sundanese script combined with applications using Feature Extraction algorithm, but there is no comparison with other algorithms and cannot recognize Sundanese numbers. Therefore, to develop the research a Sundanese script application was made with the implementation of OCR (Optical Character Recognition) using the Template Matching algorithm and the Feature Extraction algorithm that was modified with the pre-processing stages including using luminosity and thresholding algorithms, from the two algorithms compared to the accuracy and time values the process of recognizing digital writing and handwriting, the results of testing digital writing algorithm Matching algorithm has a value of 87% word recognition accuracy with 236 ms processing time and 97.6% character recognition accuracy with 227 ms processing time, Feature Extraction has 98% word recognition accuracy with 73.6 ms processing time and 100% character recognition accuracy with 66 ms processing time, for handwriting recognition in feature extraction character recognition has 83% accuracy and 75% word recognition , while template matching in character recognition has an accuracy of 70% and word recognition has an accuracy of 66%.
Automatic Detection of Hijaiyah Letters Pronunciation using Convolutional Neural Network Algorithm Gerhana, Yana Aditia; Azis, Aaz Muhammad Hafidz; Ramdania, Diena Rauda; Dzulfikar, Wildan Budiawan; Atmadja, Aldy Rialdy; Suparman, Deden; Rahayu, Ayu Puji
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.882

Abstract

Abstract— Speech recognition technology is used in learning to read letters in the Qur'an. This study aims to implement the CNN algorithm in recognizing the results of introducing the pronunciation of the hijaiyah letters. The pronunciation sound is extracted using the Mel-frequency cepstral coefficients (MFCC) model and then classified using a deep learning model with the CNN algorithm. This system was developed using the CRISP-DM model. Based on the results of testing 616 voice data of 28 hijaiyah letters, the best value was obtained for accuracy of 62.45%, precision of 75%, recall of 50% and f1-score of 58%.
Analysis of Living Organism in Arabic Vocabulary Meaning Perspective Biology and Lexical Meaning Akmaliyah, Akmaliyah; Teti Ratnasih; Ayuni Adawiyah; Aldy Rialdy Atmadja; Amiq; Hendar Riyadi
Journal of Law, Politic and Humanities Vol. 3 No. 2 (2023): (JLPH) Journal of Law, Politic and Humanities (February 2023)
Publisher : Dinasti Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/jlph.v3i2.177

Abstract

Most of Arabs people has spoken Arabic for communication. The Arabic word has a meaning to express feelings and interact socially. Lexical meaning in Arabic word has related to a specific of gender and a characteristic of living organism. The purpose of this study was to observed several meanings from the Arabic words and their relationship. In this study, semantic approach are used to analyze words lexically to find the meanings that indicate the characteristics and gender of living organism. The study found that the Arabic word has a real and a derivative meaning. As in the word father which in Arabic means Al-Abu, but it has a derivative meaning rooster. A rooster have similar character and behavior as a father in the role of the group and family member. Derivative meaning and reak meaning show that have a close relationship observed from characteristic and behavior of a living organism.
The Scopus Radar Readiness Model for Mitigating Algorithmic Discontinuation Risks Eko Pramudya Laksana; Ikhwan Arief; Mochammad Tanzil Multazam; Busro Busro; Arif Zainudin; Akhmad Anwar Dani; Andista Candra Yusro; Dedi Rahman Nur; Utama Alan Deta; Much Fuad Saifuddin; Mohammad Fauziddin; Muhamad Ratodi; Asep Erlan Maulana; Muh. Firyal Akbar; Lucky Zamzami; Aldy Rialdy Atmadja; Eko Pramudya Laksana; Ikhwan Arief; Mochammad Tanzil Multazam; Busro Busro; Arif Zainudin; Akhmad Anwar Dani; Andista Candra Yusro; Dedi Rahman Nur; Utama Alan Deta; Much Fuad Saifuddin; Mohammad Fauziddin; Muhamad Ratodi; Asep Erlan Maulana; Muh. Firyal Akbar; Lucky Zamzami; Aldy Rialdy Atmadja
Jurnal Pembelajaran, Bimbingan, dan Pengelolaan Pendidikan Vol. 6 No. 3 (2026)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um065.v6.i3.2026.3

Abstract

The integrity of the global academic record is under unprecedented threat due to the industrialization of scientific misconduct, driven by paper mills, citation cartels, and identity theft, prompting major bibliographic databases to replace manual curation with algorithmic systems. This study examines the operational mechanics of the Scopus Radar tool, an unsupervised anomaly detection system designed to identify and eliminate articles exhibiting anomalous behavior. We reconstruct the bibliometric indicators that lead to discontinuation by triangulating data from the November 2025 Scopus Discontinued Titles list, public Elsevier policy papers, and independent bibliometric research. Our study of 62 cancelled journals shows that Publication Concerns (59.7%) and Outlier conduct (14.5%) are the top grounds for removal. There are definite tendencies when it comes to hyper-concentrated authorship, quick volume velocity spikes, and citation stacking that does not make sense. We also see a "contagion effect," where certain publications have far greater rates of quitting than others. Based on these findings, we propose the Scopus Radar Readiness Model (SRRM). The model is based on the Core Practices of the Committee on Publication Ethics (COPE) and has four stages of growth. This roadmap gives editorial boards the tools they need to go from reactive compliance to proactive integrity assurance. They can do this by using internal bibliometric audits to find and fix problems before they lead to external algorithmic enforcement. The results show that journals need to use Level 4 Optimized integrity practices to stay alive in a time when automated gatekeeping is common.
Klasifikasi Tulisan Tangan Huruf Hijaiyah Anak Usia 6-8 Tahun Menggunakan Metode Support Vector Machine Ahmad Maulidi Roofiad; Cecep Nurul Alam; Aldy Rialdy Atmadja
SENTRI: Jurnal Riset Ilmiah Vol. 4 No. 12 (2025): SENTRI : Jurnal Riset Ilmiah, Desember 2025
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/sentri.v4i12.5077

Abstract

This study aims to develop a handwritten Hijaiyah letter classification system for children aged 6–8 years using the Support Vector Machine (SVM) algorithm. The main problem in elementary education is the difficulty children face in recognizing and writing Hijaiyah letters due to the similarity of their shapes and variations in handwriting. The research process uses the CRISP-DM stages, consisting of problem understanding, data collection and preparation, modeling with SVM (GridSearch for hyperparameter tuning), and evaluation using a confusion matrix and f1-score. The dataset used consists of 2,100 images of handwritten letters from elementary school students. The results show that the SVM model with RBF kernel, C=10, and gamma="scale" achieved the highest accuracy of 83.57%. This study demonstrates that an SVM-based machine learning approach can assist in recognizing Hijaiyah letters, making it a practical solution for teachers in teaching Hijaiyah writing.
Co-Authors Aaz Muhammad Hafidz Azis Adawiyah, Ayuni Adilla Febrina Ahmad Maulidi Roofiad Akhmad Anwar Dani Akhmad Anwar Dani Akmaliyah Akmaliyah Aldy Rialdy Atmadja Alfi Dawa Mumtaazy Amiq Angelyna, Angelyna Arif Zainudin Arkaan, Shabiq Ghazi Asep Erlan Maulana Asep Erlan Maulana Asep Rohimat Azis, Aaz Muhammad Hafidz Beki Subaeki, Fatkhan Gunawan, Aldy Rialdy Atmadja, Beki Busro, B. Cecep Nurul Alam Cecep Nurul Alam, Cecep Nurul Dede Kurniadi Deden Suparman, Deden Dedi Rahman Nur Diena Rauda Ramdania Dini Destiani Siti Fatimah Dyka Afan Afthori Dzulfikar, Wildan Budiawan Eko Pramudya Laksana Eko Pramudya Laksana Fadlilah, Muhammad Furqon Firdaus, Muhammad Deden Fridayanti Fridayanti Hani Hamidah Hendar Riyadi Ian Septiana, Ian Ichsan Budiman Ichsan Taufik, Ichsan Ikhwan Arief Iqbal, Arif Muhamad Irhamnillah, Sami Juliansyah, Roby Jumadi Jumadi Kartamanah, Fatih Fauzan Leni Fitriani Lucky Zamzami Lupi Krisrupianti Mochammad Tanzil Multazam Mohamad Irfan Mohamad Irfan, Mohamad Mohammad Fauziddin Much. Fuad Saifuddin Muh. Firyal Akbar Muh. Firyal Akbar Muhamad Farid Padilah Muhamad Fawaz Nurfauzan Muhamad Ratodi Muhamad Ratodi Muhammad Adam Dzulqarnain Muhammad Adi Nugraha Muhammad Dzulfi Muwaffaq Muhammad Fauzi Rachman Muhammad Luthfi Nadia Rohimah Nurfikri Habibulloh Padilah, Muhamad Farid Pamungkas, Arba Adhy Pancadrya Yashoda Pasha Pasha, Muhammad Kemal Pebri Alkautsar Rahayu, Ayu Puji Ratnasih, Teti Rifan Alamsyah Rifqi Syamsul Fuadi Sipa Almasik Sri Rahayu Sri Sulastri Taufik, Ichsan Utama Alan Deta Wildan Budiawan Zulfikar Wisnu Uriawan Wisnu Uriawan, Wisnu Yana Aditia Gerhana Yana Aditia Gerhana Yana Aditia Gerhana, Yana Aditia Yeni Pariyatin Yeni Pariyatin Yusro, Andista Candra Zanuar Ekaputra Rus’an