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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Robotics and Automation (IJRA) International Journal of Informatics and Communication Technology (IJ-ICT) Jurnal Reviu Akuntansi dan Keuangan Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Jurnal Ilmu Komputer Jurnal SPEKTRUM Majalah Ilmiah Teknologi Elektro Ecotrophic, Journal of Environmental Science TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics JURNAL MANAJEMEN AGRIBISNIS PROSIDING CSGTEIS 2013 Jurnal Ilmiah Mahasiswa FEB TEMA (Jurnal Tera Ilmu Akuntansi) Infestasi Jurnal Akuntansi Aktual JUTIK : Jurnal Teknologi Informasi dan Komputer SINTECH (Science and Information Technology) Journal Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Journal of Computer Science and Informatics Engineering (J-Cosine) Logic : Jurnal Rancang Bangun dan Teknologi International Journal of Engineering and Emerging Technology Jurnal Manajemen Indonesian Journal of Electrical Engineering and Computer Science Reviu Akuntansi, Keuangan, dan Sistem Informasi Majalah Ilmiah Teknologi Elektro KREATIF: Jurnal Pengabdian Masyarakat Nusantara Lontar Komputer: Jurnal Ilmiah Teknologi Informasi
Made Sudarma
Udayana University
Agriculture, Biological Sciences & Forestry Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management 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 Mechanical Engineering Social Sciences

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Text Mining pada Sosial Media untuk Mendeteksi Emosi Pengguna Menggunakan Metode Support Vector Machine dan K-Nearest Neighbour I Made Dwi Ardiada; Made Sudarma; Dwi Giriantari
Jurnal Teknologi Elektro Vol 18 No 1 (2019): (Januari - April) Majalah Ilmiah Teknologi Elektro
Publisher : Program Studi Magister Teknik Elektro Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MITE.2019.v18i01.P08

Abstract

Twitter social networking and microblog services that allow users to send and read text-based messages up to 140 characters, known as tweets. A text in a tweet does not only convey information from an information, but also contains information about human behavior including emotions. To detect the emotion of the text on Twitter social media services with unstructured data, it is necessary to do text analysis, one of them is by using Text Mining. Text mining tries to extract useful information from data sources through identification and exploration of an interesting pattern. Data sources are a collection of documents and interesting patterns that are not found in the form of record databases, but in unstructured text data. In this study proposes to do text mining research on Social Media to detect user emotions. Text-based emotional detection can be used in business, education, psychology, and any other field that is most important for understanding and interpreting emotions. From the tests carried out by the Support Vector Machine and K-Nearest Neighbor methods can produce an average value of precision of 0.45640904478933. Recall value is 0.50199332258158 and the accuracy value is 0.8140589569161 while from the K-Nearest Neighbor method the average value of precision is 0.34210487225193. Recall value is 0.45954538381009 and the accuracy value is 0.79705215419501. the results of testing with the SVM-KNN method showed that the suitability of emotional classification was better than the K-Nearest Neighbor method of the whole emotional categories.
Analisis Penerapan Psak 73 Terhadap Kinerja Keuangan Perusahaan Subsektor Maskapai Penerbangan Josep Geas Sapalatua; Made Sudarma
Reviu Akuntansi, Keuangan, dan Sistem Informasi Vol. 3 No. 2 (2024): Reviu Akuntansi, Keuangan, dan Sistem Informasi (REAKSI)
Publisher : Fakultas Ekonomi dan Bisnis Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/reaksi.2024.3.2.288

Abstract

This study aims to analyze the effect of PSAK 73 implementation on the financial performance of airline companies listed on the Indonesia Stock Exchange (IDX). This study employs qualitative descriptive method with a case study approach to analyze financial performance before and after the implementation of PSAK 73. Financial performance is assessed based on financial ratios consisting of debt to assets ratio (DAR), debt to equity ratio (DER), return on asset ratio (ROA), and return on equity ratio (ROE). The results of the study exhibit increased total assets and total liabilities for all of the airline companies and decreased equity of most of the airline companies after the implementation of PSAK 73. In terms of financial ratios, the implementation of PSAK 73 decreases the financial performance of airline companies, indicated by the weakening of the financial ratios: an average increase in solvency ratios consisting of DAR and DER, and an average decrease in profitability ratios consisting of ROA and ROE for all of the airline companies.   Abstrak Penelitian ini bertujuan untuk menganalisis dampak penerapan PSAK 73 terhadap kinerja keuangan perusahaan pada subsektor maskapai penerbangan yang terdaftar di Bursa Efek Indonesia (BEI). Penelitian ini menggunakan metode deskriptif kualitatif dengan pendekatan studi kasus untuk menganalisis kinerja keuangan sebelum dan setelah penerapan PSAK 73. Kinerja keuangan dinilai berdasarkan rasio keuangan yang terdiri dari rasio liabilitas pada aset (DAR), rasio liabilitas pada ekuitas (DER), rasio imbal hasil atas aset (ROA), dan rasio imbal hasil atas ekuitas (ROE). Hasil penelitian menunjukan bahwa terjadi peningkatan pada total aset dan liabilitas pada perusahaan subsektor maskapai penerbangan dan penurunan ekuitas pada sebagian besar perusahaan subsektor maskapai penerbangan setelah penerapan PSAK 73. Sementara dari sisi rasio keuangan, penerapan PSAK 73 menyebabkan penurunan pada kinerja keuangan perusahaan subsektor maskapai penerbangan, yang ditunjukkan dengan melemahnya rasio keuangan, yaitu peningkatan secara rata-rata pada rasio solvabilitas, yang terdiri dari DAR dan DER, dan penurunan secara rata-rata pada rasio profitabilitas, yang terdiri dari ROA dan ROE pada perusahaan subsektor maskapai penerbangan.
Comparative Analysis of Denoising Techniques for Optimizing EEG Signal Processing I Putu Agus Eka Darma Udayana; Made Sudarma; I Ketut Gede Darma Putra; I Made Sukarsa; Minho Jo
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol 15 No 02 (2024): Vol. 15, No. 2 August 2024
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/LKJITI.2024.v15.i02.p05

Abstract

Electroencephalogram (EEG) is a non-invasive technology that is widely used to record the electrical activity of the brain. However, often the EEG signal is contaminated by noise, including ocular artefacts and muscle activity, which can interfere with accurate analysis and interpretation. This research aims to improve the quality of EEG signals related to concentration by comparing the effectiveness of two denoising methods, namely Independent Component Analysis (ICA) and Principal Component Analysis (PCA). Using commercial EEG headsets, this study recorded Alpha, Beta, Delta, and Theta signals from 20 participants while they performed tasks that required concentration. Evaluation of the effectiveness of the denoising technique is carried out by focusing on changes in standard deviation and calculating the Percentage Residual Difference (PRD) value of the EEG signal before and after denoising. The results show that ICA provides better denoising performance than PCA, as reflected by a significant reduction in standard deviation and a lower PRD value. These results indicate that the ICA method can effectively reduce noise and preserve important information from the original signal.
Training VGG16, MobileNetV1 and Simple CNN Models from Scratch for Balinese Inscription Recognition Ida Ayu Putu Febri Imawati; Made Sudarma; I Ketut Gede Darma Putra; I Putu Agung Bayupati; Minho Jo
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol 15 No 03 (2024): Vol.15, No. 3 December 2024
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/LKJITI.2024.v15.i03.p01

Abstract

Many inscriptions in Bali are damaged. Damage to these inscriptions can be caused by natural disasters, overgrown with moss, algae and bacteria. Damage can also be caused by warfare, or deliberately erased. This inscription contains the knowledge and civilization of the ancestors so it is very important to be able to read its contents. Based on these problems, this research conducted training from scratch on 3 CNN models namely VGG16, MobileNetV1 and Simple CNN. The purpose of this research is to choose one recognition model that has the best performance and produces the highest recognition rate to proceed to the inscription restoration stage. The dataset used is Balinese inscription: Isolated Character Recognition of Balinese Script in Palm Leaf Manuscript Images in Challenge-3-ForTrain.zip. The training process of three models with five different training files resulted in the finding that VGG16 has the highest accuracy in the training, testing, and validation process with the least number of epochs. This research contributes to specific datasets, such as the Isolated Character Recognition of Balinese Script using the training process from the beginning of VGG16, involving all stages of the process. It will produce the best model performance compared to the other four training models.
MSMEs in Digital Transformation: Determinants of QRIS E-Payment Acceptance Fauziah, Farah; Made Sudarma; Erwin Saraswati
Jurnal Manajemen Vol. 29 No. 2 (2025): June 2025
Publisher : Fakultas Ekonomi dan Bisnis, Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jm.v29i2.2681

Abstract

This study is using a combination of TAM and TPB to explore the intention to use QRIS electronic payments among SMEs in Malang. The sample was collected through a survey and a representative sample of 155 SMEs was obtained. This study used SEM-PLS to analyze the construct model. The results stated that perceived usefulness, subjective norms and digital literacy significantly affect the intention to be using QRIS electronic payments. The results also show that intention to use QRIS and digital literacy significantly affect digital transformation. Interestingly, perceived convenience has the opposite effect in this study. Other factors influencing the adoption of electronic payments by SMEs and their impact on digital transformation should be explored in the future. This study should help to understand and enrich the theoretical framework so that it can be applied to increase the use of digital payments QRIS and increase digital transformation in the SME sector.
Pengabdian Kepada Masyarakat Sistem Cerdas Perlindungan Pratima Pura di Kabupaten Bangli Berbasis Deteksi Citra dan RFID Made Sudarma; Ni Wayan Sri Ariyani; I Putu Agus Eka Darma Udayana; Yogiswara Dharma Putra; I Gede Totok Suryawan
KREATIF: Jurnal Pengabdian Masyarakat Nusantara Vol. 5 No. 2 (2025): Jurnal Pengabdian Masyarakat Nusantara
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/kreatif.v5i2.6967

Abstract

Pratima is a sacred symbol in Balinese Hindu belief, holding high spiritual value and serving as a medium of worship in temples (pura). The increasing number of pratima thefts has caused not only material losses but also immaterial impacts due to the loss of their sanctity. This activity aims to develop and implement an intelligent system based on Radio Frequency Identification (RFID) and image detection technology for real-time monitoring and tracking of pratima in Desa Adat Bebalang, Bangli Regency. The system integrates long-range RFID with the Centroid Localization Algorithm and AI-based smart CCTV (VGG16), which can detect suspicious activity and automatically send notifications to the mobile application used by traditional security personnel. The program includes site mapping, equipment installation, training, trial implementation, and participatory evaluation with local communities and the Bendesa Adat. The results show that the system operates reliably, accurately, and is user-friendly. Evaluation data indicate that most respondents agreed or strongly agreed with the system’s usefulness. The system is technically effective and culturally accepted, with potential for replication in other temples across Bali. This initiative demonstrates that the integration of modern technology and local wisdom can offer sustainable solutions for the preservation and protection of cultural heritage.
Determining Tuna Grade Quality Based on Color Using Convolutional Neural Network and k-Nearest Neighbors I Gede Sujana Eka Putra; Ahmad Catur Widyatmoko; I Ketut Gede Darma Putra; Made Sudarma; A. A. K. Oka Sudana
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol. 16 No. 02 (2025): Vol.16, No. 02 August 2025
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/LKJITI.2025.v16.i02.p02

Abstract

One of the main commodities that Indonesia exports is tuna. Indonesia's inadequate handling of food safety is demonstrated by a number of instances when the United States has rejected Indonesian fishery goods and food poisoning incidences. Fish quality grade is currently determined by manual inspection which has risk human mistake. According to Robert DiGregorio, four tuna grade classifications exist: grade 1, 2+, 2, and 3. The purpose of this study is to assess the tuna meat's quality according to its color. The procedure involves pre-processing images, training datasets, and classifying them using the Convolutional Neural Network (CNN) and k-Nearest Neighbors algorithms. CNN pre-processing involves converting the image into HSV color space and training the CNN model using 240 training datasets and 74 testing datasets. CNN’s accuracy was 84% higher than k-Nearest Neighbors' which was 54%. Additionally, a comparison of the classification accuracy of CNN, VGG (Visual Geometry Group) 16, and AlexNet revealed that CNN outperformed the others with an accuracy of 84%, followed by VGG16 with 70% and AlexNet with 66%.
Deep Learning Implementation Using CNN to Classify Bali God Sculpture Pictures Ni Luh Gede Pivin Suwirmayanti; I Made Budi Sentana; I Ketut Gede Darma Putra; Made Sudarma; I Made Sukarsa; Komang Budiarta
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol. 15 No. 02 (2024): Vol. 15, No. 2 August 2024
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/LKJITI.2024.v15.i02.p02

Abstract

Efforts to preserve Balinese culture can be carried out by integrating art and technology as new steps that need to be developed. This research is motivated by the existence of various forms of God statues which have a central role in Balinese culture. The Deep Learning method is proposed because it has unique features that can be extracted automatically. The technique used in Deep Learning is Convolutional Neural Network (CNN). The training process is first performed to perform the classification process, and then the testing process is performed. We compared our CNN model with two other models, AlexNet and ResNet, based on the experimental results. Using a data split of 70%- 30%, our CNN model has the highest accuracy in managing statue image data. Specifically, our model achieves 97.14% accuracy, while Alexnet and Resnet achieve 24.44% and 33.33%, respectively. Apart from contributing to introducing the Balinese God Statue, this research can also be a basis for developing more comprehensive applications in culture and tourism.
BERT Uncased and LSTM Multiclass Classification Model for Traffic Violation Text Classification Komang Ayu Triana Indah; I Ketut Gede Darma Putra; Made Sudarma; Rukmi Sari Hartati; Minho Jo
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol. 15 No. 02 (2024): Vol. 15, No. 2 August 2024
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/LKJITI.2024.v15.i02.p04

Abstract

The increasing amount of internet content makes it difficult for users to find information using the search function. This problem is overcome by classifying news based on its context to avoid material that has many interpretations. This research combines the Uncased model BiDirectional Encoder Representations from Transformer (BERT) with other models to create a text classification model. Long Short-Term Memory (LSTM) architecture trains a model to categorize news articles about traffic violations. Data was collected through the crawling method from the online media application API through unmodified and modified datasets. The BERT Uncased-LSTM model with the best hyperparameter combination scenario of batch size 16, learning rate 2e-5, and average pooling obtained Precision, Recall, and F1 values of 97.25%, 96.90%, and 98.10%, respectively. The research results show that the test value on the unmodified dataset is higher than on the modified dataset because the selection of words that have high information value in the modified dataset makes it difficult for the model to understand the context in text classification.
Comparative Analysis of Denoising Techniques for Optimizing EEG Signal Processing I Putu Agus Eka Darma Udayana; Made Sudarma; I Ketut Gede Darma Putra; I Made Sukarsa; Minho Jo
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol. 15 No. 02 (2024): Vol. 15, No. 2 August 2024
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/LKJITI.2024.v15.i02.p05

Abstract

Electroencephalogram (EEG) is a non-invasive technology widely used to record the brain's electrical activity. However, noise often contaminates the EEG signal, including ocular artifacts and muscle activity, which can interfere with accurate analysis and interpretation. This research aims to improve the quality of EEG signals related to concentration by comparing the effectiveness of two denoising methods: Independent Component Analysis (ICA) and Principal Component Analysis (PCA). Using commercial EEG headsets, this study recorded Alpha, Beta, Delta, and Theta signals from 20 participants while they performed tasks that required concentration. The effectiveness of the denoising technique is evaluated by focusing on changes in standard deviation and calculating the Percentage Residual Difference (PRD) value of the EEG signal before and after denoising. The results show that ICA provides better denoising performance than PCA, as reflected by a significant reduction in standard deviation and a lower PRD value. These results indicate that the ICA method can effectively reduce noise and preserve important information from the original signal.
Co-Authors A. A. K. Oka Sudana A.A Ngurah Narendra A.A Raka Novi Aristi Adi Darmawan Ervanto Adinata Mas Pratama Aggry Saputra Aggry Saputra Agus Aan Jiwa Permana Agus Dharma Ahmad Catur Widyatmoko Ajeng Anandra Anak Agung Kompiang Oka Sudana Anak Agung Ngurah Prawira Yudha Andrew Sumichan Andrew Sumichan Ari Kamayanti Ariyady Kurniawan Muchsin Asri Prameshwari Casya Nova Nitali Ginting Charolina Devi Oktaviana Soleman Charolina Devi Oktaviana Soleman Dandy Pramana Hostiadi Darma Kotama, I Nyoman Darma Putra Dea Novim Kartikasari Dewa Ayu Putri Wulandari Dewa Made Wiharta Dima Nurfitri Apriani Dita Rizky Prahayuningtyas Duman Care Khrisne Erwin Saraswati Faraz Muhammad Aulia Fauziah, Farah Ferry Angga Irawan Gde Brahupadhya Subiksa Hanif Prio Ariantono Hardi yusa Hisyam Rahmawan Suharno Hisyam Rahmawan Suharno I Dewa Made Krisnayana I Dewa Nyoman Anom Manuaba I Dewa Nyoman Anom Manuaba I Gede Abi Yodita Utama I Gede Adnyana I Gede Harsemadi I Gede Herry Juniartha I Gede Sujana Eka Putra I Gede Totok Suryawan I Gede Wira Darma I Gst Agung Alit Wismaya I Gusti Agung Gede Mega Perbawa I Gusti Agung Indrawan I Gusti Agung Komang Diafari Djuni Hartawan I Gusti Kade Harta Kesuma Wijaya I Gusti Made Panji Indrawinatha I Gusti Ngurah Adhy Pradhana I Gusti Ngurah Agung Jaya Sasmita I Gusti Ngurah Agung Surya Mahendra I Gusti Ngurah Agung Surya Mahendra I Gusti Ngurah Gede Agung Suniantara I Gusti Ngurah Rai Dharma Widhura I Gusti Rai Agung Sugiartha I Kadek Arya Wiratama I Kadek Dwi Gandika Supartha I Kadek Sastrawan I Kadek Yuda Setiadi I ketut Gede Darma Putra I Komang Yogi Sutrisna I Made Adi Bhaskara I Made Arsa Suyadnya I Made Artawan I Made Budi Sentana I Made Dwi Ardiada I Made Dwi Jendra Sulastra I Made Gede Yudiana I Made Gede Yudiyana I Made Oka Widyantara I Made Sukarsa I Made Sukarsa I N Satya Kumara I Nyoman Adi Putra I Nyoman Gunantara I Nyoman Putu Suwindra I Putu Adi Pradnyana Wibawa I Putu Agung Bayupati I Putu Agus Eka Darma Udayana I Putu Agus Eka Darma Udayana, I Putu Agus Eka I Putu Agus Priska Suryana I Putu Alit Putra Yudha I Putu Arya Putrawan I Putu Astya Prayudha I Putu Gd Sukenada Andisana I Putu Oka Wisnawa I Putu Putra Diyastama I Putu Putrayana Wardana I Putu Sugi Almantara I Putu Warma Putra I Wayan Agus Surya Darma I Wayan Eka Krisna Putra I Wayan Suarna Ida Ayu Dwi Giriantari Ida Ayu Listia Dewi Ida Ayu Putu Febri Imawati Ida Bagus A. Swamardika Ida Bagus Agung Eka Mandala Putra Ida Bagus Dwijaya Kesuma Ida Bagus Gede Manuaba Ida Bagus Gede Widnyana Putra Ida Bagus Leo Mahadya Suta Ida Bagus Leo Mahadya Suta Ida Bagus Leo Mahadya Suta Ida Bagus Surya Paramarta IGAM Yoga Mahaputra Irvan Dinda Prakoso Irwansyah Cahya Irwansyah Cahya Adha L Iskandar, Adi Panca Saputra Isnan Murdiansyah IW Dani Pranata Jauzaa Maylia Suhendro Josep Geas Sapalatua Kadek Ary Budi Permana Kadek Ary Budi Permana Kadek Ary Budi Permana Kadek Ary Budi Permana Kheri Arionadi Shobirin Komang Agus Putra Kardiyasa Komang Ayu Triana Indah Komang Budiarta Komang Budiarta Komang Budiarta Komang Isabella Anasthasia Komang Nova Artawan Komang Oka Saputra Komang Sri Utami Lanang Bagus Amertha Lanang Bagus Amertha Lie Jasa Linawati Linawati Luh Gede Putri Suardani Luh Ria Atmarani M. Azman Maricar Made Dinda Pradnya Pramita Made Dinda Pradnya Pramita Made Pasek Agus Ariawan Made Pradnyana Ambara, Made Pradnyana Made Sri Indradewi Adnyana Manuh Artana Michael Tanduk Langi Londong Allo Minho Jo Minho Jo Minho Jo Muhammad Ridwan Satrio Murpratiwi, Santi Ika Naser Jawas Nengah Widiangga Gautama Ni Ketut Novia Nilasari Ni Komang Sri Julyantari Ni Komang Sukri Antariani Ni Luh Gede Pivin Suwirmayanti, S.Kom, MT, Ni Luh Gede Pivin Ni Luh Ratniasih, Ni Luh Ni Made Ananda Putri Pratiwi Ni Made Ari Lestari Ni Made Dwi Antari Ni Putu Sutramiani Ni Wayan Lusiani Ni Wayan Sri Ariyani Nurkholis - Nyoman Gede Yudiarta Nyoman Paramaita Nyoman Pramaita Nyoman Putra Sastra Nyoman Swastika Dharma Pande Made Sutawan Philipus Novenando Mamang Weking Purwania Ida Bagus Gede Putri Sintya Dewi Putri Suardani Putu Agung Ananta Wijaya Putu Angelina Widya Putu Arya Mertasana Putu Bagus Satria Paramartha Putu Risanti Iswardani Putu Wirya Kastawan R. Sapto Hendri Boedi Soesatyo Reni Surmayanti Ricky Aurelius Nutanto Diaz, Ricky Aurelius Rifky Lana Rahardian Risky Aswi R, Risky Rizky Muharram Julyanto Roekhudin, Roekhudin Rukmi Sari Hartati Rukmi Sari Hartati Tria Hikmah Fratiwi Vony Wahyunurani Wahyudin Wahyudin Wayan Gede Ariastina Wikan Pradnya Dana, Gde Y. Yuliati Yogiswara Dharma Putra Yogiswara Dharma Putra Yoni Yogiswara Yudhistira Bayu Perkasa Zulfachmi, Zulfachmi