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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Riau Journal of Computer Science Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) JSAI (Journal Scientific and Applied Informatics) Building of Informatics, Technology and Science Zonasi: Jurnal Sistem Informasi JISA (Jurnal Informatika dan Sains) Dinasti International Journal of Economics, Finance & Accounting (DIJEFA) JURNAL MASYARAKAT NEGERI ROKANIA Mejuajua KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Journal of Law, Poliitic and Humanities JOURNAL OF ICT APLICATIONS AND SYSTEM RJOCS (Riau Journal of Computer Science)
Budi Yanto, Budi
Program Studi Teknik Informatika Fakultas Ilmu Komputer Universitas Pasir Pangaraian Jl. Tuanku Tambusai, Kumu Kec. Rambah Hilir Kabupaten Rokan Hulu Telp, 081365929997
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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Data Visualization Using Google Data Studio: A Case Study of the 2019 Presidential Indonesia Election Results Bangkit Habiburrohman; Yanto, Budi; Muhammad Arif
Journal of ICT Applications System Vol 2 No 2 (2023): Journal of ICT Aplications and System
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56313/jictas.v2i2.396

Abstract

The 2019 Indonesian Presidential Election generated a significant amount of data requiring effective visualization for analysis and comprehension. This study demonstrates the application of Google Data Studio, a data visualization tool, for creating interactive dashboards based on election results. The dataset was sourced from the official Bureau of Statistics and processed to produce visualizations such as scorecards, bar charts, and pie charts, facilitating detailed insights into regional and candidate-specific voting patterns. The methodology includes data collection, processing, and visualization to construct a comprehensive dashboard. The findings illustrate the potential of Google Data Studio in enhancing data interpretability and decision-making through interactive visual representations. This research provides a practical guide for leveraging Google Data Studio in electoral data analysis
Strategy for the Development of International Training At the National Financial Audit Training Agency (Badan Diklat Pemeriksaan Keuangan Negara) Yanto, Budi; Lestari, Ni Putu Nina Eka
Dinasti International Journal of Economics, Finance & Accounting Vol. 6 No. 1 (2025): Dinasti International Journal of Economics, Finance & Accounting (March-April 2
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijefa.v6i1.3847

Abstract

This research aims to identifies the strategy for the development of international training at Badiklat PKN (the National Financial Audit Training Agency). This study adopts a qualitative approach to answer the research questions, utilizing two primary methods: observation and in-depth interviews. The study recommends a growth-focused strategy for Badiklat PKN’s international training programs, which includes enhancing infrastructure, increasing human resources, improving training materials. In conclusion, this research underscores the significant role of organizational environment in shaping policies for international training at Badiklat PKN, with a focus on enhancing Badan Pemeriksa Keuangan's global position through high-quality training programs
Analisis Pengaruh Gaya Hidup Mahasiswa terhadap Indeks Prestasi Kumulatif (IPK) Menggunakan Model Regresi Sastra, Amner; Sabri, Khairul; Yanto, Budi; Asmen, Faisal; Inal, Inal; Crisdianto, Ahlul
KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Vol 4, No 2 (2023)
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.kernel.2023.v4i2.7384

Abstract

Student lifestyle plays an important role in determining academic performance, including the Grade Point Average (GPA). This study aims to analyze the impact of lifestyle on students' GPA using a quantitative approach with regression analysis. Data were collected through questionnaires covering aspects such as sleep patterns, dietary habits, physical activity, and study habits. After data preprocessing, the residual normality test showed that the data met the normal distribution assumption, with a p-value of 0.1373 from the Shapiro-Wilk test. The constructed regression model was evaluated using Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and the coefficient of determination (R²). The results showed that lifestyle significantly affects GPA, particularly study habits and sleep patterns. Understanding these factors can help students optimize their lifestyles to improve academic performance. These findings can serve as a foundation for educational institutions in designing support programs for students.
INDENTIFIKASI POLA AKSARA ARAB MELAYU DENGAN JARINGAN SYARAF TIRUAN CONVOLUTIONAL NEURAL NETWORK (CNN) Yanto, Budi; -, Basorudin; -, Jufri; Hayadi, B.Herawan
JSAI (Journal Scientific and Applied Informatics) Vol 3 No 3 (2020): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v3i3.1151

Abstract

Riau province has Malay Arabic script as a traditional cultural heritage of ancient characters that should be preserved; this script is adapted from Arabic writing. This script from Malay Arabic has a unique form that is different from the original Arabic writing adaptation, which is read in a combination of letters forming latin meanings as an introduction to the everyday language of Riau Malay people in the earlier kingdom. Malay Arabic writing became an introduction to the local content of traditional languages in schools. To foster a love for preserving culture, in accordance with current technology that is able to recognize scripting patterns when written in paper, a knowledge base was created by using Matlab software by applying a convolutional Neural Network (CNN) artificial neural network algorithm capable of recognizing script patterns well. The result of image input in the form of handwriting written on paper then in the scanner in the form of JPEG image format. Testing was carried out on four Arabic Malay characters namely alif, ha, la, kho and nun. The result of training for the letter alif (a) epoch is obtained 98 out of 100 iterations with a training length of 3 seconds, furthermore, in validation performance with a result of 0.25013 on epoch 92 of 98 epoch for gradient letters with a value of 0.0071991 on the next epoch 98 in the extras produces an accuracy value of 0.6548 which states the correct result accordingness because it is close to the alif script. In the process of train input the letter kho obtained epoch 80 out of 100 iterations with a training process for 3 seconds, validation performance 0.25153 on epoch 74 out of 80 epoch for check validation with a value of 0.0011682 on the next epoch 80 in the extras obtained an extra value of 0.9326 stated the value is incorrect. Because the result of the extras results in an image that does not come close to the kho letter. Therefore, a study of how the system can recognize Malay Arabic writing patterns with the Convolutional Neural Network (CNN) method because it is very good at identifying image pattern features with an accuracy value of 4.12% of the 10 sample image patterns that have been inputted. With the introduction of imagery patterns from the extraction of features scanned Malay Arabic characters can help the findings of ancient Malay Arabic script as morphological learning of the validity of abstraction of Malay Arabic script is good
Pelatihan Pemanfaatan Website Aplikasi Destinasi Wisata untuk Meningkatkan Daya Tarik dan Kinerja Dinas Pariwisata Rokan Hulu Hidayatullah, Riski; Ezra Ariendy Widodo; Muhammad Hafis Maulana; Ismi Asmita; Fatimah; Indah Wahyuni; Meisaroh; Yanto, Budi; Khairul Sabri
JURNAL MASYARAKAT NEGERI ROKANIA Vol 6 No 1 (2025): JURNAL MASYARAKAT NEGERI ROKANIA
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Rokania

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56313/jmnr.v6i1.412

Abstract

Pelatihan penggunaan website aplikasi destinasi wisata ini diselenggarakan untuk meningkatkan kapasitas Dinas Pariwisata dan Kebudayaan Kabupaten Rokan Hulu dalam memanfaatkan teknologi digital sebagai sarana promosi dan pengelolaan destinasi wisata. Kegiatan ini meliputi pengenalan konsep destinasi wisata, pemanfaatan fitur-fitur dalam aplikasi, serta praktik langsung penggunaan sistem termasuk pembuatan akun admin dan pengelolaan konten. Sebanyak 15 peserta terdiri dari kepala dinas, staf, dan peserta magang terlibat dalam pelatihan yang berlangsung interaktif. Berdasarkan hasil evaluasi, seluruh peserta menyatakan pelatihan ini relevan, efektif, dan mudah dipahami. Sebagian besar juga merasa sangat puas terhadap materi dan metode pelatihan yang diberikan. Kegiatan ini menunjukkan bahwa integrasi website destinasi wisata dapat memperkuat daya tarik wisata lokal, meningkatkan efisiensi kerja dinas, serta mendukung pertumbuhan sektor pariwisata berbasis teknologi di Kabupaten Rokan Hulu. Hasil pelatihan juga membuka peluang bagi peningkatan promosi pariwisata secara berkelanjutan dan menyeluruh di era digital
PELATIHAN DESAIN GRAFIS DENGAN ADOBE PHOTOSHOP CS3 KEPADA REMAJA MASJID DESA NGASO (REMADENA) KECAMATAN UJUNGBATU Yanto, Budi; Sholehatun, Euis; Iskandar Zulkarnain, Wisnu; Amri, Rafelina; Afdol, Pangeran; Andriani, Andriani; Alifiansyah, Eldi; Fimawahib, Luth
Mejuajua: Jurnal Pengabdian pada Masyarakat Vol. 2 No. 2 (2022): Desember 2022
Publisher : Yayasan Penelitian dan Inovasi Sumatera (YPIS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52622/mejuajuajabdimas.v2i1.59

Abstract

Berdasarkan hasil peninjauan pergerakan Remaja Masjid Mushola se-desa Ngaso sangat aktif dalam membangun daerah mereka terutama dalam apek Keagamaan dengan membuat berbagai acara yang dapat membangkitkan semangat pemuda-pemudi islam dan masyarakat sekitar untuk meramaikan masjid dan beribadah. selain perayaan perayaan hari-hari Basar Islam remadena juga memiliki agena-agenda yang dilaksanakan pekana, bulanan bahkan agenda tahunan serta memberikan bantuan kepada masyarakat yang tertimpa musibah dengan membuat penggalangan dana, pada saat ini masih banyak masyarakat yang tertimpa musibah yang belum terjangkau oleh bantuan pemerintah karna berbagai alasan seperti daerah yang sulit terjangkau oleh pemerintah ataupun masyarakat yang tidak diketahui oleh khalayak ramai bahwa dia terkena musibah oleh sebab itu para pemuda pemudi memerlukan skill design poster untuk membantu mereka mempromosikan acara yang mereka buat dan membuat poster untuk penggalangan dana tersebut, tentunya untuk menarik perhatian masyarakat terhadap kegiatan-kegiatan mereka. Remadena membutuhkan skill berupa desain grafis dalam bentuk poster dan lainnya. karna dizaman teknologi seperti sekarang ini. Pemuda pemudi dituntut untuk kreatif dan inovatif.
Analisis Optimasi Algoritma Backpropagation Momentum Dalam Memprediksi Jenis Tingkat Kejahatan Di Kecamatan Tambusai Utara Yanto, Budi; Hendri; almadison; Hutagaol, Ramses; Rahman, Ripatullah
Journal of ICT Applications System Vol 1 No 1 (2022): Journal of ICT Aplications and System
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (591.429 KB) | DOI: 10.56313/jictas.v1i1.165

Abstract

Crime is conduct that disobeys the law and contravenes social norms in a way that society finds objectionable. There is no system that can forecast the kind and quantity of crimes that will happen in the future as a guide in the process of preventing crime, according to the North Tambusai Police. However, the public service process in the form of complaints has been done digitally. Backpropagation is an iterative method that works well even with complex and convoluted data. Backpropagation is an artificial neural network with several levels (multi-layer). Data processing is done on the types and numbers of crimes that took place in North Tambusai District between 2015 and 2020. The first step in the data processing procedure is to normalize the data and choose the network training parameters. Crime data and levels were used in the artificial neural network research, which used a 5-5-1 design. The test results reveal that the average prediction accuracy rate is 92.66%, with the greatest prediction accuracy rate being 99.6% and the lowest forecast accuracy rate being 90.01 percent. Theft had the highest weighting (Curat) of crimes the next year with 15 cases, while fraud, crime, and extortion/threats each had the lowest weighting (1 case). The prediction findings exhibit a sufficiently high level of accuracy to serve as a basis for evaluation.
Optimized Detection of Red Devil Fish in Low-Quality Underwater Images from Lake Toba Using a Hybrid CNN and Transfer Learning Approach Enda Ribka Meganta P; Yanto, Budi
Journal of ICT Applications System Vol 4 No 1 (2025): Journal of ICT Aplications and System
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56313/jictas.v4i1.429

Abstract

The detection of freshwater fish in turbid underwater environments presents significant challenges due to poor image quality caused by low lighting, suspended particles, and visual noise. This study proposes an optimized detection model for Amphilophus labiatus (Red Devil fish) in the murky waters of Lake Toba, Indonesia, using a hybrid Convolutional Neural Network (CNN) integrated with transfer learning and visual enhancement techniques. The proposed architecture combines MobileNetV2 and ResNet50 backbones with CLAHE (Contrast Limited Adaptive Histogram Equalization) and median filtering to improve image clarity and feature extraction. A custom dataset comprising 3,500 annotated underwater images was used to train and evaluate the model. The hybrid model achieved a detection accuracy of 96.1%, a precision of 95.6%, a recall of 94.8%, and a mean Average Precision (mAP@0.5) of 0.941—outperforming baseline models such as YOLOv5 and Faster R-CNN. Visual diagnostics and Grad-CAM attention maps confirm the model's ability to focus on key anatomical features under varying image conditions. The architecture is optimized for real-time deployment on edge-AI devices, supporting conservation efforts and biodiversity monitoring in freshwater ecosystems
Penerapan Algoritma Deep Learning Convolutional Neural Network Dalam Menentukan Kematangan Buah Jeruk Manis Berdasarkan Citra Red Green Blue (RGB) Yanto, Budi; Rouza, Erni; Fimawahib, Luth; Hayadi, B.Herawan; Pratama, Rinanda Rizki
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 1: Februari 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2023105695

Abstract

Secara umum proses menentukan jeruk manis layak (bagus) dan tidak layak (busuk) masih banyak menggunakan cara manual. Cara manual dilakukan berdasarkan pengamatan visual secara langsung pada buah yang akan diamati. Pengamatan dengan cara ini memiliki beberapa kelemahan yaitu adanya keterbatasan visual manusia, di pengaruhi oleh kondisi psikis pengamatannya serta memakan waktu yang lama terutama bagi perkebunan besar. Untuk itu, diperlukan suatu algoritma untuk menentukan buah jeruk manis dengan sistem terkomputerisasi yang dibuat menggunakan algoritma Convolutional Neural Network (CNN) merupakan salah satu algoritma dari deep learning yang merupakan pengembangan dari Multilayer Percepton (MLP) yang mampu mengolah data dalam bentuk dua dimensi, misalnya gambar serta mampu melakukan klasifikasi pada citra dengan kelas–kelas yang lebih banyak atau besar. Sistem ini dirancang dan dibangun menggunakan bahasa pemrograman matlab versi R2018a, dengan 100 dataset gambar jeruk manis menunjukan tingkat akurasi sebesar 96% untuk training 92% untuk testing yang dinilai telah mampu melakukan klasifikasi kelayakan buah jeruk manis dengan sangat baik. Pada pengujian menggunakan data baru dari 10 citra jeruk manis dihasilkan 9 citra jeruk manis dengan nilai benar dan 1 citra jeruk manis dengan nilai salah. AbstractIn general, the process of determining appropriate (good) and unfit (rotten) sweet oranges still uses manual methods. The manual method is carried out based on direct visual observation of the fruit to be observed. Observations in this way have several weaknesses, namely the presence of human visual limitations, being influenced by the psychological condition of the observations and taking a long time, especially for large plantations. For this reason, an algorithm is needed to determine sweet oranges with a computerized system created using the Convolutional Neural Network (CNN) algorithm, which is one of the deep learning algorithms, which is the development of Multilayer Perceptron (MLP), which is able to process data in two-dimensional form, for example. Images as well as being able to classify images with more or larger classes. This system is designed and built using the Matlab programming language version R2018a, with 100 sweet orange image datasets showing an accuracy rate of 96% for training 92% for testing which is considered to have been able to classify the feasibility of sweet oranges very well. In testing using new data from 10 images of sweet oranges, 9 images of sweet oranges were generated with the correct value and 1 image of sweet oranges with a false value.
Pembuatan alat deteksi suhu tubuh untuk jamaah masjid sebagai pencegahan penyebaran COVID-19 di rumah ibadah Kridoyono, Agung; Sudaryanto, Aris; Sasongko, Dimas; Wali, Muhammad; Yanto, Budi; Ogidia Bella, Novica
Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) Vol 5 No 3 (2022)
Publisher : University of Islam Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33474/jipemas.v5i3.15031

Abstract

Pandemi mengakibatkan dampak yang luar biasa terhadap berbagai sektor kehidupan, sektor ekonomi pariwisata, perdagangan dan investasi, bahkan sektor keagamaan juga terdampak. Selama pandemi, kegiatan ibadah menjadi sangat terbatas seperti halnya kegiatan masyarakat yang lain. Hal ini menjadi kondisi yang dilematis, disatu sisi masyarakat ingin kegiatan ibadah kembali semarak, tapi disisi lain juga harus taat terhadap protokol kesehatan. Dalam rangka mengatasi permasalahan tersebut, pengabdi berinisiatif melakukan kegiatan pengabdian yang berfokus pada pembuatan alat pengukur suhu tubuh tanpa sentuh untuk jamaah masjid ini. Pendekatan yang dilakukan pada kegiatan ini adalah Participatory Action Research (PAR) dengan objek utama adalah jamaah Masjid At Thoharoh Desa Tumpang Kabupaten Malang. Diharapkan hal tersebut dapat menjadi solusi agar aktivitas ibadah tetap dijalankan serta mematuhi protokol kesehatan untuk mencegah penyebaran COVID-19. Adapun fungsional alat telah diuji dan dapat bekerja 100%, sedangkan hasil pengukuran suhu pada alat hanya selisih 0.32% dengan pengukuran suhu menggunakan thermogun. Artinya alat yang dibuat telah dapat bekerja sebagaimana mestinya dengan tingkat akurasi yang baik.
Co-Authors -, Basorudin Adyanata Lubis Afdol, Pangeran agung setiawan Aini, Yulfita Akhmad Zulkifli Ali Djamhuri Alifiansyah, Eldi Almadison Alvito Dian Deva Amri, Rafelina Andriani Andriani Anjeli, Riri Arfandi, Zirhan ARIF KURNIAWAN Arif Mukti, Muhammad Asmen, Faisal B. Herawan Hayadi Bakti, Imam Rangga Bangkit Habiburrohman Basorudin, Basorudin Crisdianto, Ahlul Cut Nayla Husin Dede Fadhillah Dian Rahayu Dimas Sasongko Edi Saputra Eka Putra, Wahyu Enda Ribka Meganta P ENDRI ENDRI Erni Rouza, Erni Erwis, Fauzi Ezra Ariendy Widodo Fasha, Ulya Fatimah Firmansyah Firdaus Hasri Ainun Pratiwi Hendri Hendri Hidayatullah, Riski Hutagaol, Ramses Inal, Inal Indah Wahyuni Irawan Zai, Feri Iskandar Zulkarnain, Wisnu Ismi Asmita Jufri -, Jufri Khairul Sabri Kiki Yasdomi Kridoyono, Agung Kurniawansyah, Dani Listio, Bayu Luth Fimawahib Meisaroh Melani, Tasya Muhammad Arif Muhammad Arsy Ash Shiddiqy Muhammad Hafis Maulana Muhammad Wali, Muhammad Nasution, Yandi Ni Putu Nina Eka Lestari Ogidia Bella, Novica Parabi, Faisal Pratama, Rinanda Rizki Putra, Wahyu Eka Rahmad Rusli, Miltri Rahmadani, Dwi Rahman, Ripatullah Ramadani, Hendrizal Riski Mai Candra Sabri, Khairul Samsul Bahri Sari, Rika Perma Sastra, Amner Satria Riki Mustafa, Satria Riki Sholehatun, Euis Silvia Wulandari, Silvia Siregar, Intan Sudaryanto, Aris Sulastri, Ika Supriyanto, Asep Syahroni Syarif Hasyim Zahara Zalzabila, Dea