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All Journal SMARTek MEKTEK Foristek Jurnal MEKANIKAL JURNAL SISTEM INFORMASI BISNIS Jurnal Teknologi dan Manajemen Informatika Bulletin of Electrical Engineering and Informatics Telematika : Jurnal Informatika dan Teknologi Informasi MEKTRIK CESS (Journal of Computer Engineering, System and Science) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization International Journal of Artificial Intelligence Research SemanTIK : Teknik Informasi JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Sisfokom (Sistem Informasi dan Komputer) ILKOM Jurnal Ilmiah Jurnal Informatika JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) CCIT (Creative Communication and Innovative Technology) Journal EDUMATIC: Jurnal Pendidikan Informatika ScientiCO : Computer Science and Informatics Journal Sains, Aplikasi, Komputasi dan Teknologi Informasi TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Locus Penelitian dan Pengabdian Jurnal Algoritma Indonesia Berdampak: Jurnal Pengabdian Kepada Masyarakat
Deny Wiria Nugraha
Universitas Tadulako
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KLASIFIKASI JENIS KAYU BERDASARKAN CITRA SERAT KAYU MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK Dwimanhendra, Muhammad Rifaldi; Syahrullah, Syahrullah; Joefrie, Yuri Yudhaswana; Angreni, Dwi Shinta; Azhar, Ryfial; Nugraha, Deny Wiria; rezandy Lapatta, Nouval; Najar, Abdul Mahatir
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 1 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i1.5726

Abstract

Kayu merupakan sumber daya alam yang sangat penting bagi industri mebel atau furnitur. Pemilihan jenis kayu yang tepat sangat krusial dalam industri mebel untuk menentukan kualitas hasil produksi. Pemilihan kayu secara manual memiliki risiko kesalahan yang dapat berdampak negatif pada kualitas akhir produk mebel. Oleh karena itu, diperlukan penerapan teknologi untuk meminimalkan kesalahan pemilihan jenis kayu dan meningkatkan efisiensi proses produksi. Penelitian ini bertujuan membangun model klasifikasi jenis kayu (nantu, palapi, dan uru) berbasis Convolutional Neural Network (CNN) menggunakan citra serat kayu. Dataset terdiri dari 1.584 citra yang dibagi menjadi 80% data pelatihan dan 20% data pengujian. Arsitektur model CNN terdiri dari 4 lapisan konvolusi, 4 lapisan pooling, dan 2 lapisan fully-connected. Hasil pelatihan mencapai akurasi 97,06%, sedangkan hasil pengujian dan evaluasi menggunakan matriks konfusi mencapai akurasi 95,56%. Penelitian ini membuktikan bahwa CNN dapat digunakan secara efektif untuk klasifikasi jenis kayu dengan tingkat akurasi yang tinggi, sehingga dapat membantu meningkatkan efisiensi proses produksi mebel.
Interaksi Augmented Reality Menggunakan Boxcollider Dalam Aplikasi Pembelajaran Bahasa Inggris Zulkifli, Zulkifli; Joefrie, Yuri Yudhaswana; Nugraha, Deny Wiria; Lapatta, Nouval Trezandy; Syahrullah, Syahrullah; Angreni, Dwi Shinta
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 2 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i2.6248

Abstract

Teknologi Augmented Reality (AR) telah menjadi salah satu inovasi terdepan dalam meningkatkan pengalaman belajar interaktif. Penelitian ini mengkaji penggunaan AR dalam aplikasi pengenalan bahasa Inggris dengan memanfaatkan fitur BoxCollider untuk interaksi pengguna. Ap-likasi ini dirancang untuk membantu pengguna, terutama pelajar, dalam mengenali dan memahami kosakata bahasa Inggris melalui pengalaman visual dan interaktif. BoxCollider digunakan untuk mendeteksi interaksi antara pengguna dan objek virtual yang ditampilkan di layar, memung-kinkan respons langsung terhadap tindakan pengguna seperti menyentuh atau menggerakkan objek. Hasil penelitian menunjukkan bahwa penggunaan BoxCollider dalam AR meningkatkan keterlibatan pengguna dan memudahkan proses belajar. Pengguna dapat berinteraksi dengan berbagai objek yang mewakili kata-kata bahasa Inggris, sehingga mem-berikan konteks visual yang kuat dan mendukung pemahaman kosakata secara lebih efektif. Aplikasi ini diharapkan dapat menjadi alat bantu yang efektif dalam pengajaran bahasa Inggris, menawarkan metode bela-jar yang lebih menarik dan interaktif dibandingkan dengan metode kon-vensional
SISTEM PENENTUAN RUTE PENDISTRIBUSIAN PRODUK AIR MINERAL MENGGUNAKAN ALGORITMA ANT COLONY SYSTEM Nugraha, Deny Wiria; Erwin Dodu, Albrecht Yordanus; Septiana, Stevi
ILKOM Jurnal Ilmiah Vol 11, No 2 (2019)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v11i2.418.86-94

Abstract

The problem of determining distribution routes can be categorized as Traveling Salesman Problem (TSP). TSP is a search for a sequence of locations where a salesman travels from the initial location to a list of locations which must be passed. Each location can only be visited once and ends at the initial location of departure. This study aims to resolve the problem of determining the distribution route for mineral water products at PT. Anugerah Wina Sentosa by implementing the Ant Colony System (ACS) algorithm to conduct route searches. The ACS algorithm is an algorithm adopted from the behavior of ants to determine the shortest route from the nest to the food source. Based on the research, the results of the ACS algorithm show that the greater the case to be resolved will affect the system execution time but still can produce the best distance route. The success of this algorithm is influenced by the determination of the value of the ACS parameter, namely β, qo, q, α, ?, the number of ants and the number of ant cycles determined by analyzing the TSP case to be resolved.
Descriptive¬¬–Interpretative Evaluation of SIMONEVA Palu Usability and User Experience Using Cognitive Walkthrough (CW) and User Experience Questionnaire (UEQ) Sunandar, Aisyah Syahskiah; Nugraha, Deny Wiria
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 15 No. 02 (2026): MAY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v15i02.2628

Abstract

The Monitoring and Evaluation Information System (SIMONEVA) plays an important role in supporting regional development, but it often generates user complaints and has not been systematically evaluated. This research evaluates the usability and user experience of SIMONEVA Palu and analyzes the descriptive-interpretative relationship between the severity of usability issues and user experience scores. The usability evaluation was conducted using the Cognitive Walkthrough (CW) method, involving 10 respondents, consisting of 5 long-term users and 5 new users, while the user experience measurement used the User Experience Questionnaire (UEQ) with 41 long-term users. The results of the descriptive-interpretative relationship analysis indicate that Attractiveness and Efficiency have critical usability issues (severity level = 4) with very low UEQ scores (0.04 and 0.20), while Dependability and Perspicuity have moderate issues (severity levels = 2.22 and 2.38) with low UEQ scores (0.09 and 0.12). The pattern found indicates that the higher the severity level of usability issues, the more negative the users' perception of the system. These findings emphasize that system evaluation needs to consider both operational barriers and users' subjective perceptions. Thus, the resulting recommendations are able to highlight interface areas that require improvement more specifically. This research is expected to contribute to the literature on government information system evaluation, particularly at the regional implementation level, which is still relatively limited.
Integrasi YOLOv12 dan Konveyor Belt Untuk Mendeteksi dan Menyortir Kerusakan Kaleng Cat Secara Otomatis Usama; Deny Wiria Nugraha
Jurnal Algoritma Vol 23 No 1 (2026): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.23-1.3390

Abstract

This study aims to develop an automated system for inspecting and sorting defects in paint cans based on the integration of deep learning and a conveyor belt to improve the efficiency and consistency of quality control in the industry. The methods used include the design of a mechanical conveyor system, the integration of electronic circuits, and the development of an object detection model using YOLOv12 with a multi-camera configuration to minimize blind spots. The dataset consists of 1,209 images divided into training, validation, and test sets, with data augmentation applied to improve model robustness. Evaluation was conducted using precision, recall, F1-score, and mAP metrics, along with end-to-end system testing based on sorting accuracy, latency, and throughput under various lighting conditions and conveyor speeds. The research results show that the model achieved a precision of 0.98, a recall of 0.96, an F1-score of 0.97, and an mAP50–95 of 0.96. However, the system implementation yielded a sorting accuracy of 55.6% with optimal performance at moderate speeds, indicating a significant influence of operational factors on the system’s overall performance.
Co-Authors A.Y. Erwin Dodu A.Y. Erwin Dodu A.Y. Erwin Dodu Abdul Mahatir Najar Agustinus Kali Ahmad Ilham, Amil Amil Ahmad Ilham Aminuyati Amriana Amriana Amriana Amriana Andani Achmad Andi Hendra Andipa Batara Putra Angraeni, Dwi Shinta Ardiyansyah, Rizka Arief Pratomo Arief, Ardiaty Asminar Asminar Asri Arif Asriani Asriani, Asriani Asrul Sani Ayu Hernita Ayyub, Mohammad Azhar Baso Mukhlis Candriasih, Ni Kadek Chandra, Ferri Rama Dessy Santi Dharmakirti, Dharmakirti Djohari, Riyandi Dwitama Dodu, A. Y. Erwin Dodu, A.Y Erwin Dwi Shinta Angreni Dwi Wijaya, Kadek Agus Dwimanhendra, Muhammad Rifaldi Dwiwijaya, Kadek Agus Erwin Dodu, Albrecht Yordanus Fajriyah, Nurul Fanny Astria, Fanny Hajra Rasmita Ngemba Hamid, Odai Amer Hasanuddin Hasanuddin Ihalauw, Sahron Angelina Imat Rahmat Hidayat Isminarti, Isminarti Jeprianto Rurungan, Jeprianto K. Julianto, K. Kalatiku, Protus P Krisna Rendi Awalludin Lamasitudju, Chairunnisa Landusa, Natalia Anastasya Luh Putu Ratna Sundari Maharani, Wulan Mery Subito Mohamad Ilyas Abas Mohamad Irfan, Mohamad Muhsin, Abid Narke, I Made Reyvinno Dirga Nouval Trezandy Lapatta Novilia Chandra Paloloang, Muhammad Fairus B. Priska, Salsa Dilah Protus Pieter Kalatiku Putra, Subkhan Dinda Rahma Tanti Rahmah Laila Raivandy, I Made Randhy Rieska Setiawaty Rinianty, Rinianty Rizka Ardiansyah Rizky, Moh Taufiq Ryfial Azhar Septiana, Stevi Septiano Anggun Pratama Setiawan, Dita Widayanti Sri Khaerawati Nur Sunandar, Aisyah Syahskiah Syahrullah Syahrullah Syaiful Hendra Thia Wydia Astuti Usama Wawagalang, A. Nolly Sandra Wirdayanti Wisanti, Widya Yuli Asmi Rahman Yuri Yudhaswana Joefrie Yusuf Anshori Zulkifli Zulkifli