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All Journal SMATIKA INTEGER: Journal of Information Technology Network Engineering Research Operation [NERO] JPP IPTEK (Jurnal Pengabdian dan Penerapan IPTEK) Prosiding Seminar Nasional Sains dan Teknologi Terapan Jurnal Tekinkom (Teknik Informasi dan Komputer) Jurnal Nasional Teknologi Terapan Journal of Informatics, Information System, Software Engineering and Applications (INISTA) Djtechno: Jurnal Teknologi Informasi Indonesian Journal of Islamic Studies SAGA: Journal of Technology and Information Systems Indonesian Journal of Applied Technology Journal of Blockchain, Nfts and Metaverse Technology Smatika Jurnal : STIKI Informatika Jurnal
Azmuri Wahyu Azinar
Universitas Muhammadiyah Sidoarjo
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering Other

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Classification of Ceramic Roof Tiles Using the CNN Method Zakaria, Achmad Danu; Eviyanti, Ade; Mauliana, Metatia Intan; Azinar, Azmuri Wahyu
SAGA: Journal of Technology and Information System Vol. 3 No. 2 (2025): May 2025
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v3i2.511

Abstract

The research on tile classification using Convolutional Neural Network (CNN) aims to improve and address issues in the sorting process within the tile manufacturing industry. The accuracy level in manual sorting processes is very low due to errors caused by visual limitations and physical fatigue. By leveraging the capabilities of Convolutional Neural Network (CNN), a model was developed to classify tiles. This research involved several processes, including literature review, dataset collection, dataset splitting, preprocessing, Convolutional Neural Network (CNN) design, training, testing, and result evaluation. The study used 69 tile images divided into three classes: KW 1, KW 2, and KW 3. The results of testing the Convolutional Neural Network (CNN) on tile classification using 100 epochs with a data split of 90% training and 10% validation yielded an accuracy rate of 100%.
Model Analysis of the 2019 Election Participation Level Against Demographics in Pamekasan Regency Using the Naive Bayes Method Firmansyah, Maulana Habib; Fitrani, Arif Senja; Azinar, Azmuri Wahyu; Busono, Suhendro
SaNa: Journal of Blockchain, NFTs and Metaverse Technology Vol. 3 No. 1 (2025): February 2025
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/sana.v3i1.609

Abstract

This study aims to analyze the level of participation in the 2019 elections in Pamekasan Regency based on demographic data using the Naive Bayes classification method. The data used consisted of 189 instances and 208 predictor attributes obtained from the Central Statistics Agency (BPS) publication. The analysis process involved preprocessing, feature selection, and model evaluation stages. The test results showed a model accuracy of 66%, with the highest f1-score value in the high participation class. Further analysis also shows that most subdistricts and villages in Pamekasan have high participation rates. In addition, a very strong correlation was found between demographic attributes that have the potential to be important predictors of voter engagement. These findings provide an initial overview to understand the factors that influence community participation in elections.
Audit System Information at The Language Muhammadiyah University of Sidoarjo Syauqil, Muhammad; Eviyanti, Ade; Rosid, Mochamad Alfan; Azinar, Azmuri Wahyu
SaNa: Journal of Blockchain, NFTs and Metaverse Technology Vol. 3 No. 1 (2025): February 2025
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/sana.v3i1.612

Abstract

This test was conducted to assess the performance of the information system of the Language Center at Muhammadiyah University Sidoarjo using the COBIT 5 DSS domain framework. The audit aimed to evaluate the reliability and efficiency of the system in addressing operational issues such as limited website access and failure to print TOEFL certificates. Data collection involved interviews with unit leaders and technical observations. The results showed varying maturity levels from 2.1 (DSS03) to 4 (DSS06). Critical findings included the absence of a ticketing system and backup automation. Recommendations focused on implementing centralized incident management and cybersecurity training. This study provides a governance model for optimizing language service systems in higher education institutions.
Co-Authors Ade Eviyanti Adi, Ragil Sapta Afidah, Dewi Nur Anjar Firmansya annisaa sri indrawanti annisaa sri indrawanti Arif Senja Fitrani Astutik, Ika Ratna Indra Bachtiar, Ilham Wisnu Busono, Suhendro Dian Khoirul Hudalloh Dian Khoirul Hudalloh, Dian Khoirul Eriec Priyono Firdiansyah, M. Anang Firmansya, Anjar Firmansyah, Maulana Habib Hendro Nugroho Hendro Nugroho, Hendro Hermawan, Rafel Ardinata Hindarto Indrawanti, Annisaa Sri Irwan Alnarus Kautsar Kautsar, Irwan A. M. Anang Firdiansyah Maftahatul Hakimah Maftahatul Hakimah, Maftahatul Maretha Ruswiansari Maretha Ruswiansari, Maretha Mauliana, Metatia Intan Mochamad Alfan Rosid Mufti, Adam Laxmana Muhammad Ilham Ikhwandi Muhammad Qosdy Jauharul Arzaq Ragil Sapta Adi Rinci Kembang Hapsari Rohman Dijaya Saputra, Cahnur Sugiyanto, Sugiyanto Sumarno Sumarno Syauqil, Muhammad Taurusta, Cindy Uce Indahyanti Utami, Gati Sri Yunianita Rahmawati, Yunianita Zakaria, Achmad Danu