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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) Mejuajua KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Journal of Law, Poliitic and Humanities JOURNAL OF ICT APLICATIONS AND SYSTEM JITER-PM (Jurnal Inovasi Terapan - Pengabdian Masyarakat) 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 Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions 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.
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.
Penerapan Metode Inferensi Fuzzy Takagi Sugeno-Kang Untuk Prediksi Hasil Panen Kelapa Sawit Yanto, Budi; Rouza, erni; saputra, edi
JISA(Jurnal Informatika dan Sains) Vol 2, No 2 (2019): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v2i2.496

Abstract

Palm oil is one of the main crops and seeds in Indonesia. In oil palm plantations, oil palm crops are the most important things. Oil palm crops in the right time and quantity are what the farmers want. Therefore, harvest prediction using as reference of palm oil harvest target. Determination of harvest targets required a method that is able to predict the yield of oil palm. In this research, built a system of fuzzy inference with TSK method (Takagi Sugeno Kang), which aims to predict the yield of oil palm farmers. The fuzzy rules in the form of IF antecedent THEN are consequent, using consequent linear equations of the input variables. The coefficients of each variable of linear equation are consequently derived based on the expected yield of the harvest. The results of prediction testing of Palm Oil harvest production in 3 seasons, namely Dry Season, Rainy Season, Fertilization, input the number by values of variable with to the given range prove that the fuzzy inference of the TSK method can calculate palm il crop predictions well.
Safeguarding Bukoba Oral Tradition Through Communal Copyright and Local Regulation: A Normative-Empirical Study in Rokan Hulu Regency, Indonesia Kurniawansyah, Dani; Hendri, Hendri; Syahroni; Muhammad Arsy Ash Shiddiqy; Yanto, Budi
Journal of Law, Politic and Humanities Vol. 6 No. 3 (2026): (JLPH) Journal of Law, Politic and Humanities
Publisher : Dinasti Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/jlph.v6i3.3127

Abstract

Bukoba, an oral tradition of Rokan Hulu Regency, represents a living form of Malay cultural expression yet remains vulnerable to extinction due to the absence of legal recognition and system-atic documentation. Methods: This study applies a normative empirical legal approach by combining statutory analysis of Indonesia’s Copyright Law No. 28 of 2014 and UNESCO’s 2003 Convention with field data obtained through interviews with local cultural actors and the Rokan Hulu Tourism Office. Results: Findings indicate that Bukoba has not been included in the regional intangible cultural heritage inventory, leading to a lack of communal copyright protection and policy attention. The gap arises from limited institutional coordination, insufficient funding, and low community legal awareness. Conclusions: The research proposes an integrated safeguarding framework encompassing (i) digital documentation as legal evidence of collective ownership, (ii) community-based transmission and legal literacy programs, and (iii) enactment of local regula-tions to institutionalize protection measures. The model demonstrates that effective preservation of oral traditions requires synergy between legal instruments and local participation to ensure sustainability and prevent cultural misappropriation
Co-Authors -, Basorudin Adyanata Lubis Afdol, Pangeran agung setiawan Agus Setiadi, Irhan 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 Ashshiddiqy, Muhammad Arsy 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 Fasha, Ulya Firmansyah Firdaus Fujiawan, Vebry Hasri Ainun Pratiwi Hendri Hendri Hutagaol, Ramses Inal, Inal Intan Siregar Irawan Zai, Feri Iskandar Zulkarnain, Wisnu Jufri -, Jufri Kiki Yasdomi Kridoyono, Agung Kurniawansyah, Dani Listio, Bayu Luth Fimawahib Melani, Tasya Muhammad Arif Muhammad Vikry Sakia 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 Refni, Nurmia 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