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All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) JURNAL DESTINASI PARIWISATA JOIV : International Journal on Informatics Visualization Konvergensi : Jurnal Ilmiah Ilmu Komunikasi JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Ulul Albab ILKOM Jurnal Ilmiah JURNAL PENDIDIKAN TAMBUSAI JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Journal of Humanities and Social Studies AL-ULUM: JURNAL SAINS DAN TEKNOLOGI Jurnal Teknologi Terpadu Jurnal Review Pendidikan dan Pengajaran (JRPP) Pantun: Jurnal Ilmiah Seni Budaya Jurnal Informasi dan Teknologi Journal of Applied Engineering and Technological Science (JAETS) Journal of Governance and Local Politics (JGLP) Jurnal Sosial Humaniora Sigli Jurnal Scientia Journal of System and Computer Engineering Gunahumas Jurnal Ilmiah Wahana Pendidikan Jurnal Informatika Terpadu Indonesian Journal of Intellectual Publication (IJI Publication) Edu Cendikia: Jurnal Ilmiah Kependidikan Global Abdimas: Jurnal Pengabdian Masyarakat Sci-Tech Journal Jurnal Ilmiah Teknik Informatika dan Komunikasi Sentra Dedikasi: Jurnal Pengabdian Masyarakat Javanologi: International Journal of Javanese Studies Journal Pharmacy and Application of Computer Sciences Jurnal Informatika: Jurnal Pengembangan IT Jurnal Kajian Pendidikan dan Psikologi Jurnal Pengabdian Masyarakat dan Riset Pendidikan Toplama Jurnal Pembelajaran Bahasa dan Sastra Advances in Computer System Innovation Journal (ACSI Journal) PESHUM Indonesian Journal of Intellectual Publication (IJI Publication)
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Classification of Multiclass Ensemble SVM for Human Activities based on Sensor Accelerometer and Gyroscope Wungo, Supriyadi La; Mardewi, Mardewi; Aziz, Firman; Ishak, Pertiwi; SHILI, Hechmi
ILKOM Jurnal Ilmiah Vol 15, No 1 (2023)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v15i1.1270.107-117

Abstract

Human Activity Recognition is technology introduced to recognize human activities. Several technologies that have been applied are Accelerometer sensors, Gyroscope sensors, Cameras, and GPS. The selection of the Support Vector Machine algorithm is due to its capabilities to minimize errors in training data sets and the Curse of dimensionality which can estimate parameters as well as its ability to find the best hyperplane that separates two classes. The SVM algorithm was originally developed for the classification of two classes. Problem raised if there are more than two classes. In addition, the performance will not optimal for the large-scale data. Therefore, modification the current design is needed. An ensemble technique can be used to combine the Support Vector Machine algorithm with the bagging algorithm. This study proposes the application of an ensemble SVM algorithm to classify human activities based on accelerometers and gyroscope sensors on smartphones.  The total data is 13725 records with 4575 representatives of each class. From the results of the overall data partition carried out in the calcification process using the ensemble SVM algorithm, the best performance was generated when comparing datasets with 80% training data and 20% test data from a total of 13725 records because it succeeded in increasing accuracy, precision, and sensitivity.
Penerapan Tesseract OCR untuk Validasi Pembayaran Otomatis dalam E-Commerce Wijaya, Annisa Salsabila Apriliya; Auliyah, A Inayah; Jeffry, Jeffry; Aziz, Firman; Usman, Syahrul
Journal of System and Computer Engineering Vol 7 No 2 (2026): JSCE: April 2026
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v7i2.2625

Abstract

The rapid expansion of e-commerce in Indonesia has resulted in a significant increase in digital transactions, necessitating expedited and precise payment verification. Administrators at the SweetJab hijab e-commerce platform must manually verify bank transfer receipts, a process that is time-consuming and susceptible to errors. This study utilises Optical Character Recognition (OCR) with the Tesseract engine as a supplementary approach for verifying transfer payments on the SweetJab website. The methodology encompasses image preprocessing (resizing to 200%, converting to greyscale, and enhancing contrast), employing Tesseract OCR with PSM 6 and an LSTM model for character recognition, and utilising regular expressions (regex) to extract structured transaction data. We employed Black Box Testing and Character Error Rate (CER) computations on 40 preliminary test samples and 40 post-implementation samples to assess the system. The initial test demonstrated an accuracy of 89.5%, which increased to 92.5% upon complete system integration. This study demonstrates that OCR is an effective method for extracting information from payment receipts, while maintaining security through a final manual verification by the administrator.
The Influence Of Technology Readiness, Professional Development And Teaching Autonomy On Pedagogical Innovation Of Teaching Staffs In Higher Education: Penelitian Nuraeni, Lenny; Aziz, Firman; Pramono, Susatyo Adhi; Latuconsina, Adam; Mutakim, Jaenal; Aswadi, Dana
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 4 (2026): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 4 Tahun 2026
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i4.6294

Abstract

The research investigation wants to examine the combined impact of Technology Readiness and Professional Development together with Teaching Autonomy on Pedagogical Innovation which instructors implement at universities. The researchers used a quantitative research design to conduct their study which involved surveying 170 university faculty members who had been selected through purposive sampling. The study required respondents to meet three conditions which included being an active lecturer who had worked at least two years while using learning technology and completing professional development training. The research team used multiple linear regression analysis to evaluate their data. The researchers conducted validity and reliability tests together with normality assessment and heteroscedasticity testing and multicollinearity evaluation before they initiated their data analysis procedures. The three variables of Technology Readiness and Professional Development and Teaching Autonomy together with their individual components which cover Pedagogical Innovation showed a positive relationship that reached statistical significance. The research shows that universities can achieve more pedagogical innovation by two actions which develop technological readiness through continuous professional development and provide professors with academic independence during their teaching process. The research aims to develop higher education standards which will benefit Indonesian higher education institutions.
Sentiment Analysis of Indonesian Government Policies Using the LSTM Model for Public Opinion Mapping Rijal, Muhammad; Aziz, Firman; Tenriana, Nuzul; Delilah, Eva
Jurnal Pemerintahan dan Politik Lokal Vol 8 No 1 (2026): JGLP, MAY 2026
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47650/jglp.v8i1.2336

Abstract

Social media has evolved into a primary arena for citizens to express and negotiate opinions regarding government policies, creating vast opportunities for data-driven policy evaluation. This study aims to map public sentiment toward Indonesian government policies by integrating deep learning–based sentiment classification with linguistic and governance analysis. A dataset of approximately 50,000 Indonesian-language posts was collected from Twitter (X) and Facebook between January and June 2024. The data were processed through text cleaning, tokenization, stopword removal, and word embedding using Word2Vec and FastText, and subsequently classified into positive, negative, and neutral sentiments using a Long Short-Term Memory (LSTM) model. The results indicate that public opinion is predominantly negative (45%), particularly in relation to economic and taxation policies, while positive sentiment (34%) is mainly associated with education and health sectors. The LSTM model achieved an accuracy of 86.9%, outperforming Support Vector Machine (SVM) and Naïve Bayes models. Furthermore, linguistic analysis reveals that emotive and sarcastic expressions play a significant role in shaping critical public discourse, whereas colloquial language enhances engagement, especially among younger users. This study contributes by bridging computational sentiment analysis with linguistic interpretation and public policy evaluation within a unified framework. The findings provide practical implications for evidence-based policymaking by enabling governments to monitor public sentiment in real time, improve policy communication strategies, and foster more participatory and responsive governance.
Spatio-Temporal Graph Neural Network Based on Nonlinear Time–Frequency Features for Mu-ERD Classification in Multi-Session EEG Motor Imagery Firman Aziz; Jeffry Jeffry; Syahrul Usman; Rahmat Fuadi Syam; Muhammad Nur Arafah; Nurul Fathanah Mustamin
Journal of Applied Engineering and Technological Science (JAETS) Vol. 7 No. 2 (2026): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v7i2.8679

Abstract

Mu rhythm event-related desynchronization (ERD) is a key indicator of motor imagery activity based on EEG signals. However, accurate classification of ERD remains challenging due to the nonlinear nature of EEG signals and inter-session variability. This study proposes a motor imagery classification approach using a Spatio-Temporal Graph Neural Network (ST-GNN) model that leverages nonlinear time-frequency features extracted via Variational Mode Decomposition (VMD) and Synchrosqueezing Transform (SST). The dataset was collected from a single healthy subject across five separate sessions, each consisting of two conditions: relaxation and motor imagery. After preprocessing and segmentation, features were extracted and represented as spatio-temporal graphs to be processed by the ST-GNN. The model was evaluated using metrics such as accuracy, F1-score, AUC-ROC, and the Session Stability Index (SSI). The results show that the ST-GNN achieved an accuracy of 94.2%, F1-score of 94.1%, and AUC-ROC of 96.1%, along with high prediction stability across sessions. This performance outperformed baseline models including CNN, CSP+SVM, and STFT+MLP.These findings support the hypothesis that ERD is a distributed brain network phenomenon and demonstrate that the ST-GNN approach with VMD/SST-derived features is a promising strategy for developing adaptive and accurate BCI systems.
Kajian Strukturalisme Levi-Strauss dalam Tradisi Bulusan sebagai Cerita Rakyat di Kudus, Jawa Tengah Wahyudi, Diki; Widodo, Sahid Teguh; Aziz, Firman; Y, Wilma Silvia
Javanologi: International Journal of Javanese Studies Vol 5, No 1 (2021): Javanologi Volume 5 No. 1: December
Publisher : Pusat Unggulan Ipteks Javanologi Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/javanologi.v5i1.67939

Abstract

This research is motivated by the existence of the annual tradition of Bulusan celebration as folklore in Kudus which is considered to have a structure. This study aims to describe the structures behind the Bulusan folklore in the Kudus community, Central Java. The formulation of the research problem is as follows: 1) Does the Bulusan folklore have a structure? 2) How is the transformation of the structure of the Bulusan folklore? This study uses a literature review method regarding various existing sources. The results of this study are as follows. 1) Bulusan story has a structure consisting of external structure, internal structure, and oppositional relations. 2) the transformation of the story is divided into six points, one of which is the Bulus transformation as a form of fertility and prosperity. Thus, this folklore about Bulus is relevant to be reviewed based on Levi Strauss structuralism analysis.
Co-Authors Abasa, Sustrin Achmad Hufad Adriana, Andi Nur Ilmi Adriana, Andi Nurilmi Afifah, Mira Aulia Ahmad Sukarna Syahrir, Ahmad Sukarna Akbar Taufik Almuhajir Haris, Almuhajir Amalyah, Aam Amelia, Kiki Resqy Ampauleng Ampauleng Andi Nurilmi Adriana Andi Taufiqurrahman Akbar Andjani, Andita Dwi Andri Kurniawan Andyka Andyka, Andyka Anirwan Anirwan Annisa Sakanti Tamir Anugriaty Indah Asmarany Aqdami, Nashrullah Tsabbit Arafah, Muhammad Nur Areta Nararya Putri Setiadi Arifin, Syaadiah Armansyah, M Rezky Armin Lawi Arni, Sitti Artikasari, Devina Arvito, Djendral Muhammad Aswadi, Dana Aulia, Khansa Auliyah, A Inayah Ayu Asrhi, Nur Ayu, Rizkia Siva Aziz, Naufal Nuurul Aziz Azizah, Regita Nur Azminuddin I. S. Azis Barokah, Nurul Nur Batau, Radus Buang, Ariyani Buang, Misbahuddin Buyung Firmansyah Cahya, Nayla Riskia Delilah, Eva Dessy Putri Wahyuningtyas Dhilan Sasmita Enal Wahyudi, Abdi Fadhila Amri, Nur Faisal Rahman Fajriana, Fajriana Fani Temarwut, Farid Fatimah Azzahra NF Fatimah Malini Lubis Ferdiana, Ryan Fiina Lanahdiyan Najah Firdaus, Siti Laya Nurbaiti Firmansyah Firmansyah Firmansyah Firmansyah, Arya Pramudya Fuadi Syam, Rahmat Fujiono, Fujiono Gunawan, Resky Nuralisa H, Rezha Ilma Hadi Prayitno Hafsah, Hafni Hamdani Nur, Nur Hanayanti, Citra Siwi Hanum Nur Alifia Hasriani Hasriani, Hasriani Hayati, Ristia Nur Hikam, Zaki Maula Hilyah, Finan Azka Nuzilla Indrayani, Lilis Intan, Dyah Noor Iriany, Rosary Irmawati Irmawati Ishak, Pertiwi Iskandar, Imran Ismail Ismail Istiqamah, Nurul Jafar Jafar Jafar Jafar Jeffry Jeffry Jeffry Kahar Gani Khairunnisa, Salwa Khurosani, Bilqhis Isywal Kurniyan Sari, Sri Kusumawardhani, Anggun L.E.P, Benny La Wungo, Supriyadi Latuconsina, Adam Lempi, Herga Andar Lenny Nuraeni, Lenny Lutfi Budi Ilmawan, Lutfi Budi M Rezky Armansyah Mahdia, Naila Maulida Manan, Linda Ifni Pratiwi Marcelina, Dona Mardewi, Mardewi Marzuki Maulani, Rista Nabilah Meiliana, Annisa Merdewiningsi, Andi Mindra, Davin Septian Misbah Abdul Aziz Muhammad Arfah Asis Muhammad Lutfi Muhammad Nur Arafah Muhammad Rijal Muhammad Rijal Mutakim, Jaenal Mutia Maulida Nasir, Norma Nasruddin Nasruddin Nur Ayu Asrhi Nur Ayu Asrhi Nur Hamadani Nur Nur Hamdani Nur Nur, Nur Hamdani Nurafni Shahnyb Nurafni Shahnyb Nurdyansa Nurul Fathanah Mustamin Nurul Fathanah Mustamin Nurul Istiqamah Osman, Isnawati Panggabean, Benny Leonard Enrico Paramitha, Aura Rahma Priambodo, Caka Gatot Putra, Sudarmadi Putranto, Samuel Aditya Eko Putri Ayu Lestari Putrinima, Ayudia Qoryn Qamal Qamal Rahma, Nabila Nailatur Rahma, Widya Rahmania Nur Saputra Rahmat Fuadi Syam Reinata, Vanya Fara Restu Arsyana Rijal, Muhammad Riyanti, Apriani Rizqya Aufa Nuraini Rofi’i, Agus Rohmah Nur Hidayah Ronald Yehezkiel Sitompul Rozak, Rama Wijaya Abdul Ryan Ferdiana Sahid Teguh Widodo Sari, Sri Kurniyan Satar Satar Sazeli, Aulya Sasikirana Sembiring, Darmawanta Shahnyb, Nurafni Shavi Khalwa Khalisha Shili, Hechmi Simarmata, Victoria Clareva Siti Saidah Soeriakartalegawa, Aldo Pranata Sofyan Sofyan Sumardi . Sumardi Sumardi Suroso Suroso Susatyo Adhi Pramono, Susatyo Adhi Syahrul Usman Syam, Rahmat Fuadi Syam, Rahmat Fuady Tanniewa, Adam M Taufik , Akbar Taufik, Akbar Tazkillah, Ghina Ajmal Tb, Mar Athul Wazithah Tenriana, Nuzul Triani, Novita Trianita, Desi Umar, Hendra Velayaty, Ali Akbar Vismania S. Damaianti, Vismania S. Wahab, Andyka Wahyudi, Andi Enal WAHYUDI, DIKI Wiftasya, Najla Wijaya, Annisa Salsabila Apriliya Wijaya, Neti Septi Wisnu, Basuki Wulandari, Ayu Ratna Wungo, Supriyadi La Y, Wilma Silvia Yahya, Kurnia Yance Manoppo Yarkuran, Nuru Zahra Hasna Nabilla Zahra, Agifa Faiza Zevi, Fidiya Iryana Zhafira Tsania Rasyiffah Zulkarnain Zulkarnain Zulkarnain Zulkarnain