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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) Jurnal Magister Manajemen Techno.Com: Jurnal Teknologi Informasi Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Bulletin of Electrical Engineering and Informatics Jurnal Teknologi Informasi dan Ilmu Komputer Kitektro Journal of Aceh Physics Society Bulletin of Electrical Engineering and Informatics Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) CIRCUIT: Jurnal Ilmiah Pendidikan Teknik Elektro Jurnal Penelitian Pendidikan IPA (JPPIPA) Syntax Literate: Jurnal Ilmiah Indonesia Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Inotera Jurnal Nasional Komputasi dan Teknologi Informasi Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Vokasi Journal of Applied Engineering and Technological Science (JAETS) JOURNAL OF INFORMATICS AND COMPUTER SCIENCE Jurnal Teknik Informatika (JUTIF) International Journal of Engineering, Science and Information Technology AJAD : Jurnal Pengabdian kepada Masyarakat J-Innovation Aceh International Journal of Science and Technology Jurnal Teknologi Informasi Jurnal Teknik Indonesia Jurnal Rekayasa elektrika Enrichment: Journal of Multidisciplinary Research and Development Proceeding of International Conference on Information Science and Technology Innovation (ICoSTEC) kawanad Jurnal Teknik Sipil PESARE: Science and Engineering Service Journal Jurnal Polimesin Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Mathematics Education Journal Jurnal Pengabdian Rekayasa dan Wirausaha Nawadeepa: Jurnal Pengabdian Masyarakat Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Jurnal Rekayasa elektrika
Yuwaldi Away
Universitas Syiah Kuala
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Neuroscience Physics Public Health Social Sciences Transportation Other

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Diseminasi Platform Online Shop berbasis Website dan Situs Belanja Online Melinda, Melinda; Away, Yuwaldi; Yunidar, Yunidar; Raihan, Siti; Nazilla, Izza; Hasan, Vania Pratama
Nawadeepa: Jurnal Pengabdian Masyarakat Volume 2, No 3 (2023): September
Publisher : Pencerah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58835/nawadeepa.v2i3.242

Abstract

This service was created with the aim of training partners who have businesses to develop their businesses by creating websites. Where the Website is one of the promotional media which is quite influential in this increasingly sophisticated technological era compared to other promotional media which still use paper such as brochures, posters and others. Websites are the cheapest, most effective and efficient promotional media if they can be managed properly. From any point of view, promotional media using websites still has more advantages, both from the point of view of distributing information, speed of information delivery, and even the price. The idea is to use pantheon.io as a hosting creation page and use several plugins to support website creation, both design and uploading product photos. The partners involved in this activity are online entrepreneurs engaged in selling fragrance products (perfume). The method we use in creating websites is the RAD (Rapid Application Development) method. As a result of this training and mentoring, partners will be able to take advantage of the use of websites and online shopping sites, so that the websites created can be useful for partners who have businesses to increase the target market for their products even wider.
Enhancing Teachers' Scientific Writing Skills Through Community Service: A Case Study at SMK Negeri 1 Darul Kamal: Penguatan Keterampilan Penulisan Ilmiah Guru Melalui Pengabdian kepada Masyarakat: Studi Kasus di SMK Negeri 1 Darul Kamal Melinda; Budi Arianto; Safrizal Razali; Yuwaldi Away; Nurmalia Zakaria
JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Vol. 8 No. 4 (2024): Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Publisher : DPD Jatim Perkumpulan Dosen Indonesia Semesta

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

Abstract

The Community Service Program at SMK Negeri 1 Darul Kamal is designed to enhance the scientific writing skills of teachers, with the aim of improving the quality of publications and teaching materials. The program includes an initial socialization of its objectives, discussions to identify writing needs, as well as careful coordination and development of training modules. Conducted through interactive workshops, the training utilizes advanced technologies such as data analysis software and scientific reference management tools. Evaluation of the program through pre-test and post-test questionnaires demonstrated significant improvements in methodology understanding, writing habits, motivation for writing, and mastery of educational technology. Notable improvements were recorded with average scores for understanding research methodologies increasing from 2.9 to 4.4, and motivation for writing rising from 2.6 to 3.6. These results validate the success of the training in improving both the quality and efficiency of scientific writing among teachers. Based on these findings, it is recommended that similar training programs be extended to more educators across Indonesia to help raise educational standards and enhance teacher professionalism nationally. This initiative not only supports profession development but also aligns with national educational goals, thereby making a significant contribution to the academic community.
Implementation of a Web-Based Asset Information System to Enhance Efficiency and Transparency in Asset Management at Gampong Tingkeum, Aceh Besar Regency: Implementasi Sistem Informasi Aset Berbasis Web untuk Peningkatan Efisiensi dan Transparansi Pengelolaan Aset di Gampong Tingkeum, Kabupaten Aceh Besar Safrizal Razali; Al Bahri; Safrizal Z.A; Maimun; Yuwaldi Away; Kahlil Muchtar
JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Vol. 8 No. 4 (2024): Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Publisher : DPD Jatim Perkumpulan Dosen Indonesia Semesta

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Abstract

Asset management is a crucial aspect of governance at the village level. Gampong Tingkeum, Aceh Besar Regency, faces issues with asset recording, which is still done manually without proper codification and labeling. This study aims to design and implement a web-based asset information system to improve the efficiency, accuracy, and transparency of asset management in the village. The system was developed using the Waterfall method with a Prototype approach, utilizing the CodeIgniter framework and MySQL database. The implementation process included system installation, configuration, and training for village officials on system usage. The system was tested using Black Box Testing and User Acceptance Testing (UAT), which showed that it successfully performed asset recording, codification, labeling, and reporting functions. The implementation results demonstrated improvements in time efficiency, data accuracy, as well as increased transparency and accountability in asset management. This system is expected to serve as a model for modern and structured village asset management, aligned with the latest regulations of Permendagri No. 3 of 2024.
Improving Vocational Teachers' Data Modeling Competence through MATLAB and Python Training: : A Case Study at SMK Negeri Penerbangan Aceh Muslimsyah Muslimsyah; Yuwaldi Away; Safrizal Razali
JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Vol. 9 No. 3 (2025): Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Publisher : DPD Jatim Perkumpulan Dosen Indonesia Semesta

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Abstract

This training program aimed to enhance data modeling competencies among vocational teachers at SMK Negeri Penerbangan Aceh through intensive one-day MATLAB and Python training. Employing a pre-test/post-test design with 14 participants using 5-point Likert scale instruments, the results demonstrated significant improvements across all measured aspects. Key findings revealed the highest growth in work productivity (28.6% increase from 54.3% to 82.9%) and software mastery (25.7% increase from 42.9% to 68.6%). Cluster analysis identified three developmental patterns: (1) technical competencies (>20%), (2) tool integration (15-20%), and (3) conceptual understanding (<15%). The outcomes validate the effectiveness of hands-on, case-based training approaches while highlighting the need for advanced technical support programs. Practical implications suggest developing tiered training models for vocational teachers to address digital transformation challenges.
Comparative Analysis of Factory Parts Supplier Performance Using the Vendor Performance Rating and Analytic Hierarchy Process Methods (Case Study of PT Pupuk Iskandar Muda) Deny Novrizal; Edy Fradinata; Irwansyah Irwansyah; Yuwaldi Away; Iskandar Hasanuddin
Enrichment: Journal of Multidisciplinary Research and Development Vol. 3 No. 12 (2026): Enrichment: Journal of Multidisciplinary Research and Development
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/enrichment.v3i12.646

Abstract

The availability of spare parts is the main factor that must be considered in the maintenance process so that maintenance can be carried out as planned. The availability of spare parts really depends on the procurement process which involves many parties including suppliers who are an important part of supply chain management in a company. Supplier assessment or evaluation in several previous studies was studied using several methods, including the Vendor Performance Rating ("VPR") method which is part of the SAP application and also the Analytic Hierarchy Process ("AHP") method. The aim of this research is to determine the weight of performance priorities in determining suppliers for factory spare parts procurement using the VPR and AHP methods. The objects of this research are factory spare parts suppliers registered with PT Pupuk Iskandar Muda, namely CV A, CV B, CV C, CV D and CV E. Based on the results of the analysis using the VPR method, it is CV A got the highest average score of 89.05 (weight percentage 23%), and the lowest was CV C with an average value of 78.17 (weight percentage 16%). The results using the AHP method are the highest as well as CV A 30% with a weight value of 0.3047, and the lowest is also CV C 9% with a weight value of 0.0822. Judging from these two methods, suppliers who perform well and poorly are the same.
Application of a Levenberg–Marquardt-Based Backpropagation Neural Network for Rainfall Prediction Using a Single Weather Station Wahyu Sukmananda; Irwandi; Edwar Iswardy; Kadarsah; Yopi Ilhamsyah; Yuwaldi Away; Chakrit Chotamongsak; Dedy Ardana
Jurnal Penelitian Pendidikan IPA Vol 12 No 2 (2026)
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v12i2.13845

Abstract

This study aims to develop an accurate monthly rainfall prediction model for Sabang City, Indonesia, to support agriculture, disaster mitigation, and water resource management in coastal regions with complex climatic conditions. An Artificial Neural Network (ANN) trained using the Levenberg–Marquardt (LM) algorithm was employed, combining the Gradient Descent and the Gauss–Newton methods to enhance convergence speed and training stability. Meteorological data from 2015–2024, including temperature, humidity, air pressure, sunshine duration, wind direction, wind speed, and rainfall, were obtained from the Maimun Saleh Meteorological Station. Model performance was assessed using Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and the coefficient of determination (R²). The optimal architecture consisted of a single hidden layer with 25 neurons, producing an MSE of 955.84 mm², an RMSE of 30.91 mm, an MAE of 23.06 mm, a MAPE of 34.8%, and an R² of 0.93. These results indicate that the ANN-LM model effectively captures nonlinear climatic relationships and seasonal rainfall variability. The MAPE value falls within the acceptable range reported in forecasting literature, demonstrating practical reliability. Overall, the ANN-LM approach outperformed conventional backpropagation in accuracy and training efficiency, indicating its suitability for rainfall prediction in coastal areas.
Heavy–Light Soft-Vote Fusion of EEG Heatmaps for Autism Spectrum Disorder Detection Melinda Melinda; Syahrul Gazali; Yuwaldi Away; Aufa Rafiki; W.K Wong; Muliyadi Muliyadi; Siti Rusdiana
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 8 No 1 (2026): January
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v8i1.1377

Abstract

Autism spectrum disorder is a neurodevelopmental condition that affects social communication and behaviour, and diagnosis still relies on subjective behavioural assessment. Electroencephalography provides a noninvasive view of brain activity but is noisy and often analysed with handcrafted features or evaluation schemes that risk data leakage. This study proposes a deep learning pipeline that combines wavelet denoising, EEG-to-image encoding, and heavy-light decision fusion for autism detection from EEG. Sixteen-channel EEG from children and adolescents with autism and typically developing peers in the KAU dataset is denoised using discrete wavelet transform shrinkage, segmented into fixed 4 second windows, and rendered as pseudo colour heatmaps. These images are used to fine-tune five ImageNet pretrained architectures under a unified training protocol with 5-fold cross-validation. Heavy-light fusion combines one heavyweight backbone and one lightweight backbone through weighted soft voting on class posterior probabilities. The strongest single model, ConvNeXt Tiny, attains about 97.25 percent accuracy and 97.10 percent F1 score at the window level. The best heavy light pair, ConvNeXt plus ShuffleNet, reaches about 99.56 percent accuracy and 99.53 percent F1, with sensitivity and specificity in the 99 percent range. Fusion mainly reduces missed ASD windows without increasing false alarms, indicating complementary error patterns between heavy and light models. These findings show that the proposed denoise encode classify pipeline with heavy light fusion yields more robust autism EEG classification than individual backbones and can support EEG-based decision support in autism screening.
Systematic Literature Review on AI-Enhanced Dual-Axis Solar Tracking Systems: Techniques and Performance Analysis Muhammad Basyir; Yuwaldi Away; Tarmizi Tarmizi; Ira Devi Sara
International Journal of Engineering, Science and Information Technology Vol 6, No 3 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i3.1553

Abstract

Recent advancements in artificial intelligence have significantly improved the performance of intelligent dual-axis solar-tracking systems, enabling more efficient photovoltaic (PV) energy harvesting under variable irradiance conditions, transient cloud cover, and mechanical uncertainties. This systematic literature review synthesizes 25 peer-reviewed studies (2018–2024) identified from Scopus and Web of Science using PRISMA 2020 procedures. We examine controller families (fuzzy logic, adaptive neuro-fuzzy interface system, deep reinforcement learning, and hybrid designs), sensing and actuation stacks (ephemeris, light sensors, inertial measurement, and computer-vision-based pose), and reported outcomes for tracking accuracy and energy gain. Across comparable conditions, AI-enabled controllers consistently reduce tracking error by ~10–35% and increase annual energy capture by ~8–25% relative to fixed-tilt or conventional rule-based/PID baselines, with the largest gains observed under partial shading and rapidly varying sky conditions. Validation is dominated by simulation, while prototype and hybrid (simulation plus field) evaluations—though fewer—provide stronger evidence of real-world robustness. Persistent challenges include computational cost on embedded hardware, sample-efficient learning and safety for field deployment, inconsistent reporting of metrics, and limited long-horizon testing. To address these gaps, we recommend (i) standardized benchmarking that reports tracking error, normalized energy yield, control latency and controller power, (ii) low-cost edge-AI implementations (model compression, quantization, and microcontroller-class deployment), and (iii) multi-season field trials with reproducible protocols across climates. The findings indicate a clear shift from static, hand-tuned control toward intelligent, adaptive methods. Hybrid designs emerge as a practical choice for deployment due to their combined stability and adaptability, whereas deep reinforcement learning shows state-of-the-art performance primarily in simulation and calls for careful simulation-to-real transfer. Overall, this review clarifies the evidence base and outlines priorities for fault-tolerant, low-cost, and real-time adaptive dual-axis solar tracking.
Pembinaan Pemasangan Pembangkit Listrik Tenaga Matahari bagi Santri Dayah Mini Banda Aceh Rakhmad Syafutra Lubis; Suriadi Suriadi; Mahdi Syukri; Ramdhan Halid Siregar; Masri Masri; Yuwaldi Away
AJAD : Jurnal Pengabdian kepada Masyarakat Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Divisi Riset, Lembaga Mitra Solusi Teknologi Informasi (L-MSTI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59431/ajad.v5i3.684

Abstract

Solar energy is a renewable energy source that has become increasingly popular in recent years as an electricity source. However, the availability of trained personnel to install rooftop solar panels is limited. This community service program was conducted to provide training in residential solar system installation for students from Dayah Mini Banda Aceh. The training took place in the Power Electronics and Renewable Energy Laboratory at Universitas Syiah Kuala, where theoretical training on renewable energy was combined with demonstrations of equipment and simulated installation practice. The modules included rail mounting, panel positioning, inverter connections, charge controller setup, and wiring in series and parallel. Students were guided by lecturers and assisted by engineering students who had already undergone training in this field. They exhibited great enthusiasm and completed all the stages of installation successfully. This program not only addresses the shortage of workers with such skills in the solar installation industry but also helps students from low-income families acquire these practical competencies that can lead to jobs or entrepreneurship within the ever-growing sector of renewable energy; thus reducing unemployment among their communities while supporting Indonesia's shift towards sustainable energy.
Comparison Of Machine Learning Algorithms For Rice Production Prediction Abdul Karim; Yuwaldi Away; Syahrial; Roslidar; Jeperson Hutahaean; William Ramdhan; Yessica Siagian
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 2 (2026): April 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i2.7453

Abstract

Rice production forecasting plays an important role in supporting future agricultural planning, food supply management, and food security. Accurate yield prediction allows governments and farmers to estimate production outcomes and develop appropriate strategies to maintain stable food availability.This study addresses this gap by comparing four regression-based machine learning models: Random Forest, XGBoost, Support Vector Regression (SVR), and Artificial Neural Network (ANN). All models were trained and tested using the same dataset to ensure a fair evaluation. Model performance was measured using the coefficient of determination (R²). The results show that Random Forest achieved the best performance (R² = 0.963), followed by XGBoost (R² = 0.959). In contrast, SVR (R² = -0.064) and ANN (R² = -2.417) performed poorly, indicating limited predictive capability. Overall, these findings suggest that ensemble-based methods, particularly Random Forest and XGBoost, are more reliable and effective for rice production forecasting compared to SVR and ANN.
Co-Authors - Firmansyah . Melinda . Roslidar . Zulfan Abdul Karim Abdullah Abdullah Abdullah Abdullah Abdullah Abdullah Achmad Fauzi Achmi Yuliani Adriman, Ramzi Ahmadiar, Ahmadiar Al Bahri Alfina Alfina Alfisyahrin Alfisyahrin, Alfisyahrin Andri Novandri ANISAH Arfah Salwa Ariandi, Teuku Asfianda, Muhammad Aufa Rafiki Aufa Rafiki Aulia Rahman Azizah, Nadiatul Bahri, Al Bakhtiar, Dandi Basir, Nurlida Basyir, M. Budi Arianto Chairullah, Chairullah Chakrit Chotamongsak Cholis Cholis Cut Ita Erliana Cut Mutia Dedy Ardana Deny Novrizal Devi Sara, Ira Dinda Damayanty Dirhamsyah, Dirhamsyah Dirhamsyah, Muhammad Doni Gunawan Edwar Iswardy Edy Fradinata Erdiwansyah Erdiwansyah Fachrurrazi Fachrurrazi Fachrurrazi Fachrurrazi Fardian Fardian Fathurrahman Fathurrahman Feri susilawati Firdaus Firdaus Fitri Arnia Fitri Arnia Fitriyani Fitriyani Fitriyani, Martunis Gunawan, Doni Gustin Yulian Nova Hari Anna Lastya Hasan, Hafidh Hasan, Vania Pratama Hasanuddin, Iskandar Hendra Muzawwir Hendri Farliza Herawati, Rama Heri Arya Supriyatna Husni Husni Ikram Muddin Ikramullah, Ikramullah Intan Permata Sari Irfan Mulia Irwandi Irwansyah Irwansyah Irwansyah Irwansyah Iskandar Hasanuddin Iskandar Hasanuddin Isyatur Raziah Jalil, Asri Muhammad Jamil, M. Jeperson Hutahaean Jeperson Hutahaean Kadarsah Kahlil Muchtar Kahlil, Kahlil Khadafi, M Khairul Munadi Khairul Munadi lestari, mulia Lubis, Rakhmad Syaputra Lulusi Lulusi M Ikhsan M. Dirhamsyah M. Dirhamsyah M. Dirhamsyah M. Ikhsan M. Jamil M. Khadafi Mahdi Syukri Mahmuddin Mahmuddin Mailizar Maimun Masri Ibrahim Masri Ibrahim Masri Masri Maulana, Edi Mirza Rahmat, Muhammad Mirza Tabrani Misbah Sulaiman Nura Moulina, Aisyah Rayhan Muhammad Aden Fahadi Muhammad Asfianda Muhammad Haries Muhammad Ikhsan Muhammad Ikhsan Muhammad Irhamsyah Muhammad Isya Muhammad Nur Hasan Muhammad Rizal Fachri Muhammad Thalhah Muliyadi Muliyadi Muliyadi Muliyadi Munawir Munawir Muslimsyah Muslimsyah Muslimsyah Muslimsyah Muslimsyah, Muslimsyah Nargaza, Juanda Nasaruddin Nasaruddin Nasaruddin Nasaruddin Nazilla, Izza Nikmal Maula Mirda Noprida Sari Novandri, Andri Nurhanif Nurhanif Nurmalia Zakaria Nuzula, Mukhsin Oktiana, Maulisa Oktiana, Maulisa Putra, T. Edisah Raden Mohamad Herdian Bhakti Rafiqa Shahnaz Noor Rahmah Johar Rahmat Sufri Raihan, Siti Raja Ariffin Raja Ghazilla Rakhmad Syafutra Lubis Ramdhan Halid Siregar Ramdhana, Rizka Rauzatul Jannah Raziah, Isyatur Rizal Munadi Rizal Munadi Roslidar RR. Ella Evrita Hestiandari Rudiansyah Putra Saddam Azmi Saddami, Khairun Safrizal Razali Safrizal Razali Safrizal Safrizal Safrizal Z.A Safwan Saifuddin Muhammad Jalil Saiful Husin Samsuddin Samsuddin Setiawati, Cut lilis Siti Rusdiana Sofyan, Sarwo Edhy Suhaeri Suhaeri, Suhaeri Surbakti, Muhammad Syukri Suriadi Suriadi Suriadi Suriadi Suriadi Suriadi Surya Surya Syahrial Syahrial, Syahrial Syahriza, Syahriza Syahrizal Syahrizal Syahrul Gazali Syahrul Gazali Syifaul Huzni Syukriyadin Syukriyadin T. Edisah Putra Tamlicha, Akram Tarmizi Tarmizi Tarmizi Tarmizi Taufik A. Gani Taufik A. Gani2 Taufiq A. Gani Taufiq A. Gani Taufiq A.Gani Taufiq Abdul Gani Teuku Budi Aulia Teuku Budi Aulia Teuku Yuliar Arif Teuku Yuliar Arif Udink Aulia Ulya Zikra W.K Wong W.K Wong Wahyu Sukmananda Wardana, Surya William Ramdhan Wong, W. K Yessica Siagian Yessica Siagian Yopi Ilhamsyah Yudha Nurdin Yunidar Yunidar Yunidar Yusria Darma Zakiah Zakiah Zichri, Zichri Zulfikar Zulfikar zulhelmi zulhelmi