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All Journal International Journal of Electrical and Computer Engineering KOMPUTIKA - Jurnal Sistem Komputer Journal Social Science And Technology For Community Service International Journal of Electronics and Communications Systems Jurnal Ilmu Siber dan Teknologi Digital
Ilman, Igit Sabda
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Other

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Analisis Metode Kalman Filter, Particle Filter dan Correlation Filter Untuk Pelacakan Objek Sholehurrohman, Ridho; Habibi, Mochammad Reza; Ilman, Igit Sabda; Taufiq, Rahman; Muhaqiqin, Muhaqiqin
Komputika : Jurnal Sistem Komputer Vol. 12 No. 2 (2023): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v12i2.9567

Abstract

Object tracking is a challenging in computer vision. Object tracking is divided into two, which can be one object or several objects, depending on the object being observed. The process of tracking an object in the form of one object is to estimate the target in the next sequence based on information from the first frame given. In object tracking in the form of single object tracking, there are five steps that are often used in discriminatory methods, including motion models, feature extraction, observation models, model updates and integration methods. Although various algorithms of object tracking are proposed, there are still failures in the object tracking process caused by occlusion, non-rigid target deformation, and other factors. This study proposes the implementation of the Kalman filter, particle filter, and correlation filter methods for object tracking in video data. The results of the implementation of the three methods can track objects in traffic video data and the script circuit video. In object tracking calculations and method analysis, the kalman filter gets 96.89% where the kalman method is better in terms of accuracy compared to other methods. Meanwhile, in the average performance of computation time, the correlation method gets 26.69 FPS, where the correlation method is superior compared to other competitor methods. Keywords – Kalman Filter; Particle Filter; Correlation Filter; Object Tracking; Object Tracking in Video
A hybrid model to mitigate data gaps and fluctuations in tax revenue forecasting Taufik, Rahman; Aristoteles, Aristoteles; Ilman, Igit Sabda
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i4.pp4099-4108

Abstract

This study addresses the critical challenge of advancing tax revenue forecasting models to effectively handle distinctive data gaps and inherent fluctuations in tax revenue data. These challenges are evident in Lampung Province, Indonesia, where limited temporal granularity and non-linear variability hinder accurate fiscal planning. Despite advancements in statistical, machine learning, and hybrid approaches, existing models often fall short in simultaneously managing these challenges. A hybrid model integrating random forest regressors for data interpolation and Long Short-Term Memory for capturing complex temporal patterns was proposed. The model was evaluated, achieving an R² of 0.86, root mean squared error (RMSE) of 9.65 billion, and mean absolute percentage error (MAPE) of 3.49%. Although the model has limitations in generalizing to unseen data, the results demonstrate that it outperforms existing forecasting models regarding accuracy and reliability. Integrating random forest regressors and long short-term memory delivers a tailored solution to the complexities of tax revenue forecasting, contributing to fiscal forecasting and setting a foundation for further exploration into hybrid approaches.
Pendampingan Kelompok Sadar Wisata (Pokdarwis) Dalam Pemanfaatan Teknologi Informasi Untuk Pengembangan Ekowisata Mangrove Di Cuku Nyinyi Desa Sidodadi Yanfika, Helvi; Sholehurrohman, Ridho; Ilman, Igit Sabda
Journal of Social Sciences and Technology for Community Service (JSSTCS) Vol 6, No 1 (2025): Volume 6, Nomor 1, March 2025
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jsstcs.v6i1.4835

Abstract

Pemanfaatan teknologi informasi memiliki potensi yang luar biasa dalam pengembangan ekowisata mangrove di Cuku Nyinyi, Desa Sidodadi, Kabupaten Pesawaran. Desa Wisata Desa sidodadi desa yang terletak di wilayah provinsi lampung kecamatan teluk pandan kabupaten pesawaran, dengan luas wilayah desa sidodadi 563.25 Ha. Potensi Desa Sidodadi di sektor pariwisata memiliki tempat wisata yaitu salah satunya dengan sumber daya alam Hutan mangrove yang di kelola oleh BUMDes dan POKDARWIS dan masyrakat. Pengabdian bertujuan meningkatkan pengetahuan dan keterampilan anggota Pokdarwis di Cuku Nyinyi, Desa Sidodadi Kabupaten Pesawaran dalam pemanfaatan teknologi informasi untuk mengembangkan ekowisata mangrove. Dalam Pengabdian akan dilakukan pendampingan dalam pengembangan ekowisata mangrove menggunakan pemanfaatan teknologi informasi. Target pemberdayaan yang akan dilakukan adalah meningkatkan kapasitas SDM anggota Pokdarwis di Cuku Nyinyi, Desa Sidodadi Kabupaten Pesawaran dalam, meningkatkan pengetahuan dan keterampilan anggota Pokdarwis di Cuku Nyinyi, Desa Sidodadi Kabupaten Pesawaran dalam pemanfaatan teknologi informasi untuk mengembangkan ekowisata mangrove.Kata Kunci: ekowisata; mangrove; teknologi; informasi;
Analisis Informasi Jaringan Homogen dan Heterogen pada Liga Champions UEFA Taufik, Rahman; Muhaqiqin, Muhaqiqin; Ilman, Igit Sabda; Sholehurrohman , Ridho
Jurnal Ilmu Siber dan Teknologi Digital Vol. 1 No. 2 (2023): Mei
Publisher : Penerbit Goodwood

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/jisted.v1i2.1928

Abstract

Purpose: The interpretation of network analysis research can be challenging today. The aim of this study is to analyze the homogeneous and the heterogeneous network information that occurred in the UEFA Champions League 2017-2018. Research Methodology: To obtain an interpretation of the results of network information analysis, centrality measurements and community detection were performed, where the centrality measurements methods used are Degree centrality, Betweenness centrality, Eigencentrality, PageRank, while community detection method used is performed using the Louvain. Result: The homogenous and heterogeneous network analysis was conducted using dataset of 17980 players, 32 teams, and 128 matches in Champions League 2017-2018. In this analysis, homogenous and heterogeneous network schemes were used to represent objects and relationships between objects in the network. The analysis was based on centrality measurements to identify influential nodes and community emergence within the network. The result is an interpretation of network analysis in the form of information about the roles of players, teams, countries, locations, formations, and skills that affect the performance of UEFA Champions League. Limitation: the use of diverse data sources, the application or development of data analysis techniques, and the formation of a broader network scheme Contribution: Obtaining information related to the UEFA Champions League based on the interpretation result of the analysis of homogeneous and heterogeneous networks
YOLOv5s for Traffic Prohibition Sign Detection in Bandar Lampung: An Empirical Evaluation Under Real-World Urban Conditions Sholehurrohman, Ridho; Junaidi, Akmal; Dewi, Tasya Nursita; Andrian, Rico; Ilman, Igit Sabda; Reza Habibi, Mohammad
International Journal of Electronics and Communications Systems Vol. 6 No. 1 (2026): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v6i1.28786

Abstract

The detection of traffic prohibition signs in tropical urban environments is under-documented, as existing benchmark datasets such as GTSRB and TT100K do not represent the specific conditions of Southeast Asia. This study evaluates YOLOv5s for detecting and classifying six classes of traffic prohibition signs on four urban roads in Bandar Lampung, Indonesia, using a dataset of 9,898 labeled images extracted from real-world video recordings under various environmental conditions. YOLOv5s was directly compared with YOLOv4, YOLOv5m, and Faster R-CNN under identical evaluation conditions. YOLOv5s outperformed all comparison models with an average accuracy of 93.34% and an average F1-Score of 95.97%, with performance ranging from 88.65% in Pagar Alam to 97.28% at Unila, reflecting the documented gradation of environmental complexity. Processing speeds of 7.3–8.8 FPS place the system in the near-real-time category, making it suitable for offline traffic monitoring applications. This study provides a method for detecting prohibition signs in tropical urban environments in Indonesia and offers a practical reference point for the development of intelligent transportation systems in developing cities facing similar environmental challenges.
Co-Authors Akmal Junaidi Andrian, Rico Aristoteles, Aristoteles Dewi, Tasya Nursita Habibi, Mochammad Reza Helvi Yanfika Muhaqiqin, Muhaqiqin Parabi, M. Iqbal Putra, Chandra Prasetya Rahmawat, Amalia Nurul Reza Habibi, Mohammad Sholehurrohman , Ridho Sholehurrohman, Ridho Taufik, Rahman Taufiq, Rahman