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All Journal Sainteks International Journal of Artificial Intelligence Research JURNAL ILMIAH INFORMATIKA Buletin Ilmiah Sarjana Teknik Elektro Journal of Robotics and Control (JRC) JATI (Jurnal Mahasiswa Teknik Informatika) Bubungan Tinggi: Jurnal Pengabdian Masyarakat Journal of Innovation Information Technology and Application (JINITA) Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) JPM: JURNAL PENGABDIAN MASYARAKAT Buletin Sistem Informasi dan Teknologi Islam Journal of Software Engineering and Information System (SEIS) Journal of International Multidisciplinary Research IJMST Scientific Journal of Engineering Research Scientific: Journal of Computer Science and Informatics
Wijaya, Setiawan Ardi
Universitas Muhammadiyah Riau
Aerospace Engineering Humanities Astronomy Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Transportation Other

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Pemanfaatan Kahoot Sebagai Media Pembelajaran Interaktif Kepada Guru Sekolah Dasar Setiawan Ardi Wijaya; Winarso, Doni; Arribe, Edo; Hafsari, Rizka; Syahril; Aryanto; Diansyah, Risnal; Mulyana, Wide; BR Bangun, Elsi Titasari
JPM: Jurnal Pengabdian Masyarakat Vol. 5 No. 3 (2025): Januari 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jpm.v5i3.2273

Abstract

In the rapidly evolving digital era, education in Indonesia faces new challenges and opportunities to enhance the quality of learning. Therefore, it is crucial for teachers to upgrade their knowledge of digital-based learning methods. One solution offered is the use of interactive learning methods. In this community service project, the interactive learning medium to be explored is Kahoot. This activity collaborates with SDN 011 Lenggadai Hilir and is scheduled to take place on Wednesday, August 14, 2024. The workshop aims to improve the understanding and skills of the teachers at SDN 011 Lenggadai Hilir in utilizing Kahoot as an interactive learning medium. Kahoot is a quiz-based platform capable of creating a fun and engaging learning atmosphere for students. The research method employed in this activity is Participatory Action Research (PAR), chosen because it involves active collaboration between researchers and participants to address real-world problems and create relevant solutions. This method consists of several stages: preparation, pre-test, training, post-test, and evaluation. A pre-test is conducted to measure participants' initial knowledge of using Kahoot, followed by training that includes material presentations and hands-on practice with Kahoot. A post-test is then conducted to assess the improvement in knowledge after the training. The results of the workshop showed a significant improvement in participants' understanding. The average post-test scores were higher than the pre-test scores, indicating an increase in participants' skills in using Kahoot. The workshop also received positive feedback from participants, who felt that Kahoot could enhance student engagement in learning. This training successfully enhanced the teachers' ability to use Kahoot and motivated them to actively incorporate technology into their teaching activities.
DESIGN OF FINANCIAL RECORDING SYSTEM USING WATERFALL METHOD AT ARTHO FURNITURE STORE Dwi Purnomo, Raka; Ardi Wijaya, Setiawan; Mardiyanto, Silvia
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 2 (2025): JATI Vol. 9 No. 2
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i2.12817

Abstract

This research aims to develop a financial recording system for Artho Furniture using the Waterfall method based on the needs that have been identified. The results show that the system successfully automates transaction recording, reduces manual errors by 80%, and produces clear and accurate financial reports. The test results showed improved efficiency, transparency, and accountability in financial management, enabling shop owners to make better business decisions. With accurate and timely financial data, operational activities run more effectively. The system was developed using PHP and MySQL, with a user-friendly interface to facilitate users in daily operations.
RANCANG BANGUN SISTEM INVENTORY PADA CENTRAL MOTORS MENGGUNAKAN METODE WATERFALL Muzdhalifatul Ijfi, Inessthasia; Brilianti Nafilah, Rizkiya; Wahyu Ningsih, Dwi Putri; Safuan, M. Chairil; Abraar, M. Said; Sarohim, Nabil; Ardi Wijaya, Setiawan
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 3 (2025): JATI Vol. 9 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i3.13583

Abstract

Perkembangan teknologi informasi yang pesat telah membawa inovasi di berbagai sektor, termasuk industri otomotif, yang mengharuskan perusahaan untuk mengelola inventaris dengan lebih efisien. Central Motors, sebuah perusahaan otomotif, masih menggunakan sistem pencatatan manual untuk mengelola stok barang, yang menyebabkan masalah seperti ketidakakuratan data, kesulitan dalam pemantauan stok secara real-time, dan keterlambatan pengambilan keputusan. Riset ini bertujuan buat merancang serta meningkatkan sistem data inventaris berbasis website guna tingkatkan efisiensi serta akurasi dalam pengelolaan stok. Metode Waterfall digunakan dalam pengembangan sistem ini, yang meliputi 5 tahapan : analisis kebutuhan, desain sistem, implementasi, pengujian, serta pemeliharaan. Hasil penelitian menampilkan jika sistem yang dikembangkan bisa meningkatkan efisiensi manajemen inventaris dengan memberikan pencatatan stok yang lebih akurat, pemantauan real-time, serta otomatisasi proses pengelolaan barang masuk serta keluar, sehingga membantu mengurangi kesalahan pencatatan, tingkatkan efektivitas operasional, serta mempercepat pengambilan keputusan
Play Store Data Scrapping and Preprocessing done as Sentiment Analysis Material Hasanah, Rakyatul; Sulistiani, Sulistiani; Nurhikmayani, Nurhikmayani; Hasanah, Zakiyah; Wijaya, Setiawan Ardi; Abdennasser, Dahmani; Sharkawy, Abdel Nasser
Indonesian Journal of Modern Science and Technology Vol. 1 No. 1 (2025): January
Publisher : CV. Abhinaya Indo Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64021/ijmst.1.1.16-21.2025

Abstract

Sentiment analysis is a computational technique used to interpret user opinions about a product through textual reviews. This research aims to prepare useful data for further research, one of which is sentiment analysis. A total of 12000 recent reviews from July 2024 - January 2025 were collected through web scrapping. The research process includes data preprocessing steps such as case folding and data cleaning to transform the raw data into a usable format. The raw data up to the given changes have been uploaded to the mendeley data repository to be reprocessed into further research, one of which is the sentiment analysis approach.
Understanding Time Series Forecasting: A Fundamental Study Furizal, Furizal; Ma’arif, Alfian; Kariyamin, Kariyamin; Firdaus, Asno Azzawagama; Wijaya, Setiawan Ardi; Nakib, Arman Mohammad; Ningrum, Ariska Fitriyana
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 3 (2025): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i3.13318

Abstract

Time series forecasting plays a vital role in economics, finance, engineering, etc., due to its predictive power based on past data. Knowing the basic principles of time series forecasting enables wiser decisions and future optimization. Despite its importance, some researchers and professionals find it difficult to use time series forecasting techniques effectively, especially with complex data settings and selection of methods for a particular problem. This study attempts to explain the subject of time series forecasting in a comprehensive and simple manner by integrating the main stages, components, preprocessing steps, popular forecasting models, and validation methods to make it easier for beginners in the field of study to understand. It explains the important components of time series data such as trend, seasonality, cyclical components, and irregular components, as well as the importance of data preprocessing steps, proper model selection, and validation to achieve better forecasting accuracy. This study offers useful material for both new and experienced researchers by providing guidance on time series forecasting techniques and approaches that will help in enhancing the value of decision making.
A Bibliometric Analysis of Natural Language Processing and Classification: Trends, Impact, and Future Directions Setiawan Ardi Wijaya; Rahmad Gunawan; Rangga Alif Faresta; Asno Azzawagama Firdaus; Gabriel Diemesor; Furizal
Scientific Journal of Engineering Research Vol. 1 No. 1 (2025): January
Publisher : PT. Teknologi Futuristik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64539/sjer.v1i1.2025.6

Abstract

This study presents a bibliometric analysis of Natural Language Processing (NLP) and classification research, examining trends, impacts, and future directions. NLP, a key field in artificial intelligence, focuses on enabling computers to process and understand human language through tasks such as text classification, sentiment analysis, and speech recognition. Classification plays a crucial role in organizing textual data, facilitating applications like spam detection and content recommendation. The research employs bibliometric analysis to evaluate publication trends, citation networks, and emerging themes from 1992 to 2025. Using data retrieved from Scopus, descriptive statistical analysis and bibliometric mapping with VOSviewer reveal key contributors, influential publications, and subject area distributions. Findings indicate a significant rise in NLP research, with deep learning models, particularly transformers, driving advancements in the field. The study highlights dominant research areas, including computer science, engineering, and medicine, and identifies leading countries in NLP research, such as the United States, China, and India. Additionally, ethical concerns, including bias and fairness in NLP applications, are discussed as critical challenges for future research. The insights derived from this analysis provide valuable guidance for researchers and policymakers in shaping the next phase of NLP development.
Trends and Impact of the Viola-Jones Algorithm: A Bibliometric Analysis of Face Detection Research (2001-2024) Wijaya, Setiawan Ardi; Famuji, Tri Stiyo; Mu'min, Muhammad Amirul; Safitri, Yana; Tristanti, Novi; Dahmani, Abdennasser; Driss, Zied; Sharkawy, Abdel-Nasser; Al-Sabur, Raheem
Scientific Journal of Engineering Research Vol. 1 No. 1 (2025): January
Publisher : PT. Teknologi Futuristik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64539/sjer.v1i1.2025.8

Abstract

The Viola-Jones algorithm remains a cornerstone in computer vision, particularly for object and face detection. This bibliometric study provides a comprehensive analysis of the algorithm’s academic impact and research trends, encompassing publication patterns, citation metrics, influential authors, and co-occurrence of keywords. The findings indicate a significant rise in research outputs and citations between 2016 and 2020, reflecting the algorithm's sustained relevance and application in various domains. Network visualization maps further reveal the algorithm's integration with diverse fields, including machine learning, image processing, and neural networks, emphasizing its versatility and adaptability to emerging technological challenges. Key research contributions include advancements in hybrid approaches, combining the Viola-Jones framework with techniques such as convolutional neural networks and HOG-SVM for improved detection accuracy. However, limitations such as computational inefficiency and sensitivity to environmental factors persist, presenting opportunities for innovation. This study concludes by highlighting future research directions, such as integrating deep learning and edge computing to enhance algorithmic performance in real-time and complex scenarios. This study provides a valuable reference for researchers and practitioners aiming to extend the Viola-Jones algorithm’s capabilities and applications by consolidating existing knowledge and identifying research gaps.
Pengenalan Citra Batik Tradisional Menggunakan Deep Learning untuk Klasifikasi Motif Daerah Fanani, Galih Pramuja Inngam; Muhammad Amirul Mu'min; Yana Safitri; Setiawan Ardi Wijaya; Novi Tristanti; Tri Stiyo Famuji
Scientific: Journal of Computer Science and Informatics Vol. 2 No. 1 (2025): Januari 2025
Publisher : Universitas Muhammadiyah Bima

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34304/scientific.v2i1.336

Abstract

Batik merupakan warisan budaya Indonesia yang kaya akan nilai estetika dan keragaman motif berdasarkan asal daerahnya. Namun, upaya digitalisasi dan klasifikasi motif batik secara otomatis masih menghadapi tantangan, terutama dalam hal ketersediaan dataset representatif dan pendekatan pemodelan yang optimal. Penelitian ini bertujuan untuk mengembangkan sistem klasifikasi motif batik berdasarkan daerah asal menggunakan metode deep learning berbasis Convolutional Neural Network (CNN). Dataset citra batik yang digunakan terdiri dari 1.200 gambar, mewakili empat daerah utama yaitu Solo, Pekalongan, Cirebon, dan Madura. Model CNN dirancang dengan empat blok konvolusi dan dua fully connected layer, serta dilatih menggunakan optimizer Adam dan teknik early stopping. Hasil eksperimen menunjukkan bahwa model mencapai akurasi klasifikasi yang tinggi dan mampu membedakan motif berdasarkan karakteristik visual khas masing-masing daerah. Meskipun terdapat sedikit kesalahan klasifikasi antara motif yang memiliki kemiripan visual, secara keseluruhan model menunjukkan kinerja yang baik dan stabil. Penelitian ini menyimpulkan bahwa pendekatan deep learning efektif dalam mengenali motif batik secara otomatis dan berpotensi diimplementasikan dalam aplikasi edukasi budaya maupun promosi digital batik berbasis kecerdasan buatan.
Face Detection Analysis of Digital Photos Using Mean Filtering Method Sunardi, Sunardi; Yudhana, Anton; Wijaya, Setiawan Ardi
International Journal of Artificial Intelligence Research Vol 6, No 2 (2022): Desember 2022
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (467.748 KB) | DOI: 10.29099/ijair.v6i2.307

Abstract

Face detection in digital photos aims to get the face area in the digital photo. Usually, a lot of noise occurred when detecting faces in digital photos. This study applies the mean filtering method to improve digital photos by reducing noise. The accuracy of the mean filtering method is calculated using a confusion matrix, while the ability of this method is measured using the parameters of Mean Square Error (MSE) and Peak Noise to Signal Ratio (PNSR). Viola-Jones method was used to detect faces in this research. This method was chosen because it is one of the face detection procedures with high accuracy and good computational ability. Testing the mean filtering method obtained the lowest MSE of 9.33, while the highest PNSR of 14.37. The accuracy obtained by the mean filtering method using confusion is 90%. Based on these results, it can be concluded that the mean filtering method is feasible to be used in the case of face detection in digital photos.
Penerapan Model Prototype Rancang Bangun Sistem Bimbingan Konseling Berbasis Web pada SMK Muhammadiyah 3 Pekanbaru Marisa, Vania; Ardi Wijaya, Setiawan; Tsabitah, Nayla
Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Vol. 7 No. 1 (2024): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Utility Project Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jikomsi.v7i1.2925

Abstract

Unit Bimbingan Konseling adalah salah satu elemen penting pada praktik lembaga pendidikan untuk dapat melakukan pemantauan dan evaluasi terhadap akademik dan perilaku sosial siswa di SMK Muhammadiyah 3 Pekanbaru. Sebelumnya SMK Muhammadiyah 3 Pekanbaru melakukan kegiatan administrasi dan pengarsipan data yang bersifat konvensional. Permasalahan yang diperoleh berdasarkan observasi diantaranya pengolahan data konseling siswa yang dilakukan secara sederhana dengan pencatatan dan pengarsipan berkas siswa yang bersifat fisik serta waktu konseling yang tidak terjadwal yang dapat mengganggu kegiatan belajar siswa di kelas. Maka dari itu, dilakukan suatu Rancang Bangun Sistem Informasi untuk memfasilitasi layanan bimbingan konseling berbasis website yang terdigitalisasi agar tidak terjadinya pemborosan serta bertujuan untuk menanggulangi kekurangan yang ada dengan menggunakan bahasa pemrograman PHP, framework Laravel, dan menggunakan metode pengembangan sistem yaitu model prototype dan Unified Modeling Languange (UML) sebagai tools perancangan sistem serta menggunakan penyimpanan database terstruktur yaitu MySQL. Sistem telah melalui uji fungsional dengan metode pengujian black box. Hasil penelitian ini adalah Sistem Informasi yang dibangun dapat menjadi fasilitas bagi Unit BK di SMK Muhammadiyah 3 Riau dalam memberikan pelayanan konseling meliputi proses konseling, pemantauan rekam jejak siswa hingga penjadwalan konseling yang terdigitalisasi guna mencapai perkembangan yang sesuai dengan potensi siswa melalui aplikasi berbasis website yaitu SIMBEKA.
Co-Authors Abdennasser, Dahmani Abdul Fadlil Abid Yanuar Badharudin Abraar, M. Said Agus Prasetyo Marsaid Ahmad Bukhari, Ahmad Al-Sabur, Raheem Alfian Ma’arif Anton Yudhana Anton Yudhana Ariska Fitriyana Ningrum Aryanto Asno Azzawagama Firdaus Br Bangun, Elsi Titasari Brilianti Nafilah, Rizkiya Dahmani, Abdennasser Doni Winarso, Doni Driss, Zied Dwi Purnomo, Raka Edo Arribe, Edo Fanani, Galih Pramuja Inngam Fauzan, Al fana Fauzan, Wahyu Fazilla, Rahma Muti Firmansyah Fitri Anggraini Furizal Furizal, Furizal Gabriel Diemesor Gerry Julian Gunawan, Rahmad Hafsari, Rizka Hasanah, Rakyatul Hasanah, Zakiyah Kariyamin, Kariyamin Laia, Ertin Mardiyanto, Silvia Marisa, Vania Mihardi, Hansen Muhammad Amirul Mu'min Murni Murni Muzdhalifatul Ijfi, Inessthasia Nakib, Arman Mohammad Novi Tristanti Nurhikmayani, Nurhikmayani Pratama, Dzaky Medlin Putera, Ardi Maulia Putri, Jossie Mutiarani Rangga Alif Faresta Risnal Diansyah, Risnal Safuan, M. Chairil Sarohim, Nabil saskia, ananda Sharkawy, Abdel Nasser Sharkawy, Abdel-Nasser Silpandi, Dimas Sulistiani Sulistiani, Sulistiani Sunardi Sunardi sunardi sunardi Sunardi, Sunardi Suwarno, Iswanto Syahril Syaputri, Qori Monica Tri Stiyo Famuji Tristanti, Novi TSABITAH, NAYLA Wahyu Ningsih, Dwi Putri Wide Mulyana Wiyrabawa Kainna Putra Rachman Yana Safitri Yana Safitri, Yana Yusuf Hendra Pratama Zahran Ramdani, Ibnu Ziad Iqbal, Muhammad