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All Journal JURNAL SISTEM INFORMASI BISNIS Journal of Robotics and Control (JRC) International Journal of Aviation Science and Engineering Eduvest - Journal of Universal Studies Artinara
Kurniawan, Denni
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Health Professions Languange, Linguistic, Communication & Media Mechanical Engineering Neuroscience Social Sciences Transportation Other

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Penerapan K-Nearest Neighbour dalam Penerimaan Peserta Didik dengan Sistem Zonasi Kurniawan, Denni; Saputra, Ade
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 9, No 2 (2019): Volume 9 Nomor 2 Tahun 2019
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (54.162 KB) | DOI: 10.21456/vol9iss2pp212-219

Abstract

Admission of new students is a routine activity at the beginning of each new meeting year in all formal educational institutions. At the moment the acceptance of new students uses the zoning system and has been regulated by Permendikbud No. 20 in 2019. This zoning system will accept students where their residence enters through the user area with the school environment. With this Permendikbud the government hopes that there will be an evenness in the quality of education in all schools, so that schools will no longer get the title of superior and non-superior schools. But in a system, the zoning improves anxieties in the school environment. This research supports to help the participating school students will be accepted in accordance with the provisions of the Ministry of Education and Culture. In overcoming problems that arise in the school environment there needs to be a system that can overcome that problem. In this study using the K-Nearest Neighbor (K-NN) method. Where the K-NN method will do the classification of new learners' residence with the school. In determining the classification using the K-NN method used for zoning and non-zoning areas, it is seen based on the closest K value. In finding the optimal value in this study using the Rapidminer application. The optimal high-level test results at K 5 where the value of this K is 83.36%
Pelatihan Dan Pemanfaatan Aplikasi Canva Dalam Pembuatan Desain Grafis Untuk Pemula di Lingkungan RT. 05 RW 10 Meruya Devit Setiono; Yulianawati; Wahyuningsih, Sri; Kurniawan, Denni; Khoiriyah, Khusnul
Artinara Vol 2 No 1 (2023): Jurnal Artinara Februari 2023
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/art.v2i01.60

Abstract

Setiap anggota masyarakat memiliki peranan dalam masyarakat serta kegiatan yang dilakukan dalam kehidupan sehari-hari. Kemampuan dalam menyajikan informasi, promosi yang menarik, kreatif, unik dan informasi yang disampaikan mudah dipahami adalah suatu keterampilan yang dapat dijadikan modal untuk menyampaikan berita, informasi, media pembelajaran, serta promosi suatu produk. Tujuan dari pengabdian masyarakat ini untuk meningkatkan keterampilan design grafis dengan tools canva bagi masyarakat di lingkungan RT.05/RW.10 Meruya Utara. Kegiatan pelatihan canvaini dimulai dengan memberikan gambaran singkat, manfaat, cara menggunakan dan melakukan praktek secara langsung dengan pendampingan. Modul praktek juga diberikan kepada peserta sebagai penunjang proses pembelajaran. Dari evaluasi kegiatan pelatihan ini dapat kami simpulkan bahwa program pelatihan ketrampilan ini telah memberikan manfaat yang signifikan dan langsung dapat diaplikasikan dalam kehidupan sehari-hari dalam berbagai aktivitas. Kegiatan pelatihan ini merupakan kegiatan positif dan tepat sasaran untuk memberikan pelatihan keterampilan bagi masyarakat, sehingga dapat menambah wawasan serta pengetahuan baru di bidang design grafis dalam pembelajaran kegiatan sehari-hari seperti pembuatan materi belajar, membuat flyer product, membuat sertifikat, membuat konten, kartu ucapan dan lain sebagainya.
Bird Detection System Design at The Airport Using Artificial Intelligence Ummah, Khairul; Hidayat, Muhammad Fadly; Kurniawan, Denni; Zulhanif, Zulhanif; Sembiring, Javensius
International Journal of Aviation Science and Engineering - AVIA Vol. 4, No. 2 (December 2022)
Publisher : FTMD Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47355/avia.v4i2.72

Abstract

Bird strike is a process of crashing between bird and airplane which occurs in flight phase. Based on data, there are 40 times bird strike occurs every day (FAA, 2019). There are lot of research that already conducted to decrease number of birds at the airport. But it is not given significant changes. Hence, it is needed a model that can detect bird at the airport so that we can decrease the number of birds. Study already conducted by comparing motion detection with object detection and filter which can be used to improve detection quality. Model already developed using YOLOv4 object detection with 71.89% mean average precision. It is expected that object detection can be developed to become a bird repellent system in the future
Enhanced Precision Control of a 4-DOF Robotic Arm Using Numerical Code Recognition for Automated Object Handling Sukri, Hanifudin; Ibadillah, Achmad Fiqhi; Thinakaran, Rajermani; Umam, Faikul; Dafid, Ach.; Kurniawan, Adi; Morshed, Md. Monzur; Kurniawan, Denni
Journal of Robotics and Control (JRC) Vol. 6 No. 1 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research develops a 4-DOF robotic arm system that utilizes numerical codes for accurate, automated object handling, supporting advancements in sustainable industrial automation aligned with the UN Sustainable Development Goals (SDGs), particularly Industry, Innovation, and Infrastructure (SDG 9). Key contributions include the integration of EasyOCR for reliable code recognition and a control mechanism that enables precise positioning. The robotic system combines a webcam for visual sensing, servo motors for movement, and a gripper for object manipulation. EasyOCR effectively recognizes numerical codes on randomly positioned objects against a uniform background while the microcontroller calculates servo angles to guide the arm accurately to target positions. Testing results show a success rate exceeding 94% for detecting codes 1 to 4, with minor servo angle errors requiring adjustments in arm extension by 30 mm to 50 mm. Positional error analysis reveals an average error of less than 1.5 degrees. Although environmental factors like lighting can influence code visibility, this approach outperforms traditional methods in adaptability and precision. Future research will focus on enhancing code recognition under variable lighting and expanding the system's adaptability for diverse object types, broadening its applications in industries demanding high efficiency.
Comparison Of Single Moving Average And Winter Exponential Smoothing Methods In Predicting The Number Of Divorce Cases At The Religious Court Of Cibinong Widiarto, Widiarto; Kurniawan, Denni
Eduvest - Journal of Universal Studies Vol. 4 No. 4 (2024): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v4i4.1178

Abstract

Based on data from the Central Bureau of Statistics, the divorce rate in Indonesia shows a tendency to increase from year to year. Similar conditions were experienced by Cibinong district. The forecasting method that will be used in this study is the Single Moving Average and Winter's Exponential Smoothing. The results of forecasting the number of lawsuits in 2023 from July to December with movements with two obtained forecasts in July were 602, August 283, MAD value = 67.29, MSE value = 8.722, MAPE = 11.61, RMSE = 1.46, Accuracy value of 88.39%. Movements with four forecasting periods in July were 620, August 448, September 301, October 141. MAD value = 99.33, MSE value = 14,722, MAPE = 16.59, RMSE = 1.90, Accuracy value of 83.41%. Forecasting with the Winters Exponential Smoothing Method with Alpha: 0.1, Beta: 0.3 and Gamma: 0.5, the forecast results obtained in July were 504.10026, August 491.61306, September 663.18788, October 745.41004, November 732.42766 and December 732.10904. MAE value is 171.65116, MSE value is 686.63361, MAD value is 38.74, MSE value is 2.797 MAPE value is 6.0 and RMSE value is 0.83 and accuracy value is 94.00%. Based on the calculation results above, it is concluded that forecasting the number of divorce filings at  Cibinong Religious Court from January 2018 to December 2023 with the Winter Exponential Smoothing method has MAD, MSE, MAPE, RMSE values smaller than values in the Single Moving Average method. Winter Exponential Smoothing method is more appropriate with an accuracy value of 94.00%.
Appropriateness of Student Major Selection Using Naive Bayes and K-Nearest Neighbor Algorithms at SMK Plus Al Musyarrofah Mustofa, Kamaluddin; Tasa, Tyan; Kurniawan, Denni
Eduvest - Journal of Universal Studies Vol. 4 No. 6 (2024): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v4i6.1483

Abstract

The process of selecting a major is a critical stage for students because it can influence their motivation and learning outcomes while attending school, especially at Vocational High Schools (SMK). This challenge is becoming more significant with the emergence of many new schools in various cities and districts in Indonesia, especially in DKI Jakarta Province. Prospective students often choose majors not based on personal interests, which can then result in lower grades, especially in productive subjects or certain competencies. To overcome this problem, a major suitability system is needed that can provide recommendations based on student abilities through certain attributes. In this research, a department suitability classification process was carried out using the Naive Bayes and k-Nearest Neighbor methods using data from 238 tenth grade (X) students for the 2023/2024 academic year, which included 9 relevant attributes. The testing process was carried out with a composition of training data and test data in five comparisons, namely 90:10, 80:20, 70:30, 60:40, and 50:50. The research results show that the 80:20 composition provides the best results, with k-Nearest Neighbor achieving recall, accuracy and precision levels of 100%. On the other hand, the Naive Bayes Classifier produces a recall rate of 61%, with an accuracy of 73%. These results indicate that k-Nearest Neighbor is superior in predicting major suitability compared to Naive Bayes under these conditions.
Co-Authors Achmad Fiqhi Ibadillah Ade saputra Adi Kurniawan Dafid, Ach Devit Setiono Faikul Umam Hidayat, Muhammad Fadly Javensius Sembiring, Javensius Khairul Ummah Khoiriyah, Khusnul Krisna Rendi Awalludin Morshed, Md. Monzur Mustofa, Kamaluddin Sukri, Hanifudin Tasa, Tyan Thinakaran, Rajermani Widiarto Widiarto, Widiarto Yulianawati Zulhanif, Zulhanif