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All Journal TEKNIK INFORMATIKA Reaktor Mechatronics, Electrical Power, and Vehicular Technology TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics ITEj (Information Technology Engineering Journals) Kultivasi JOIV : International Journal on Informatics Visualization Jurnal Sistem dan Manajemen Industri JRSI (Jurnal Rekayasa Sistem dan Industri) Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Mitra Manajemen Jurnal Kimia Terapan Indonesia Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JURTEKSI Jurnal Sistem Cerdas Linguistik Indonesia Teknologi Indonesia International Journal of Advances in Data and Information Systems Journal of Data Science and Its Applications Jurnal Instrumentasi INVEST : Jurnal Inovasi Bisnis dan Akuntansi Charity : Jurnal Pengabdian Masyarakat Universitas Muhammadiyah Yogyakarta Undergraduate Conference Proceeding SENTRI: Jurnal Riset Ilmiah Jurnal Ilmiah Teknik Elektro eProceedings of Engineering SEMNASTERA (Seminar Nasional Teknologi dan Riset Terapan) SmartComp Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal Polimesin AQILA : Acceleration, Quantum, Information Technology and Algorithm Journal Journal of Production, Enterprise, and Industrial Applications IJoICT (International Journal on Information and Communication Technology)
Fakhrurroja, Hanif
Telkom University
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities 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 Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences Transportation

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Ambidextrous IoT governance to support EnergyCo’s digital transformation based on COBIT 2019 traditional and DevOps Prima Audina Wibowo; Rahmat Mulyana; Hanif Fakhrurroja
Jurnal Sistem dan Manajemen Industri Vol. 9 No. 2 (2025): December
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v9i2.10803

Abstract

The accelerating digital transformation in the energy sector demands robust governance mechanisms for emerging technologies, particularly the Internet of Things (IoT). This study examines the governance challenges faced by an energy company in Indonesia as it strives to manage IoT ecosystems while meeting regulatory requirements and achieving organizational objectives. Despite IoT’s critical role in enabling digital transformation, limited Research has explored IoT governance frameworks grounded in COBIT 2019, especially within the energy domain. To bridge this gap, this study develops an ambidextrous IoT governance framework by integrating the Traditional and DevOps Focus Area mechanisms from COBIT 2019. The framework is designed to balance stability and adaptability in managing IoT-related risks. A Design Science Research methodology is employed, complemented by a case study approach involving interviews, questionnaires, and internal document analysis to ensure contextual relevance and data saturation. The study identifies and evaluates governance priorities by aligning Governance and Management Objectives (GMOs) with national regulations, design factors, and prior research findings. Based on gap analysis using seven components of the selected GMO, DSS (Managed Security Services), the study proposes targeted improvements to IoT governance. These include strengthening leadership accountability, advancing cybersecurity competencies, and enhancing system monitoring capabilities. The implementation of these improvements is projected to elevate the DSS maturity level from 3.29 to 3.86, supporting its digital transformation agenda in alignment with COBIT 2019. This Research contributes to the literature by offering a structured, context-aware IoT governance framework and providing actionable insights for practitioners seeking to govern IoT initiatives within complex, regulated environments.
Mapping IoT Applications in the Textile Industry: A Bibliometric Study using Biblioshiny and VOSviewer Kurnia, Deni; Sutanto, Agus; Fakhrurroja, Hanif; Son, Lovely
Proceedings of Universitas Muhammadiyah Yogyakarta Graduate Conference Vol. 5 No. 2 (2025): Fostering Gen Z for Sustainable Development and Renewable Energy
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/grace.v5i2.677

Abstract

The rapid advancement of technology, particularly the Internet of Things (IoT), has had a transformative impact on various industries, including the textile sector. IoT facilitates real-time data collection, monitoring, analysis, and decision-making, thereby enhancing efficiency, productivity, and resource sustainability. However, a comprehensive bibliometric study of IoT applications in the textile industry has yet to be undertaken. To address this research gap, this study employs bibliometric methods using the Biblioshiny R package and VOSviewer to examine research trends, key contributors, and emerging themes. By analyzing 177 relevant publications from 2015 to 2025, the study identifies major research directions, influential authors, leading institutions, and evolving areas of interest. The findings highlight a growing research focus on IoT-driven textile innovations, particularly the development of electronic textiles (e-textiles), which integrate electronic components into wearable devices for human use. This positioning of e-textiles at the forefront of smart wearable technology underscores their significance as a critical area of exploration within contemporary textile engineering. Furthermore, China, the United States, and India emerge as the predominant contributors to this research domain. The insights derived from this study offer valuable guidance for researchers, industry professionals, and policymakers, supporting future advancements and innovations in IoT applications within the textile industry.
A hybrid pareto–fishbone and IoT-based monitoring framework for reducing DTY yarn defects Kurnia, Deni; Fakhrurroja, Hanif; Marno, Marno; Joniko, Joniko
Jurnal Polimesin Vol 23, No 6 (2025): December
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v23i6.7678

Abstract

Quality Control (QC) challenges in the textile industry increasingly require data-driven and real-time solutions to reduce critical production defects. This research aims to develop a hybrid Pareto-Fishbone analysis integrated with an IoT-based monitoring framework to reduce the incidence of dominant defects in Draw Textured Yarn (DTY) yarns (X-stitch and Broken Filament). Defect data collected in 2024 (n=2,396) and early 2025 (n=1,177) were analyzed using Pareto charts, which identified X-stitch (40.15%) and Broken Filament (37.15%) as contributing 77.3% of total defects in 2024. Fishbone diagrams traced root causes to machine vibration and yarn tension anomalies. An IoT prototype was designed using ADXL345 vibration sensors (200 Hz sampling), tension monitoring, and MQTT communication to a Node-RED dashboard to enable real-time alerts. Preliminary testing achieved 95% MQTT transmission success and detected vibration anomalies correlating with 85% of X-stitch incidents. The proposed hybrid framework combines the diagnostic strength of Pareto–Fishbone analysis with the preventive capability of IoT monitoring, offering a scalable Industry 4.0-oriented solution for textile QC and predictive maintenance.
Analisis Keamanan Protokol Komunikasi Message Queuing Telemetry Transport (Studi Kasus Smart Greenhouse) Pakpahan, Andy Victor; Triwangsa, Mochamad Cory Sakti; Fakhrurroja, Hanif
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 12, No 4 (2023): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v12i4.4681

Abstract

Masalah keamanan pada perangkat IoT menjadi isu yang menjadi kekhawatiran pengguna. Perangkat IoT yang memiliki pemrosesan yang terbatas menjadikan perangkat ini memiliki celah keamanan. Perangkat IoT kemudian menjadi sasaran oleh penyerang untuk mengambil data-data penggunanya. Perangkat IoT yang dianalisis keamanannya adalah Smart Greenhouse. Untuk menganalisis keamanan pada Smart Greenhouse menggunakan metode penetration testing dimana terhadap tahap Reconnaissance maka perlunya penggambaran sistem yang sedang berjalan dan berdasarkan sistem yang berjalan akan dicari celah berdasarkan studi literatur yang dilakukan. lalu potensi celah dicoba diimplementasikan di Smart Greenhouse dan dibandingkan dengan protokol komunikasi MQTTS yang dianggap lebih aman Kemudian pada tahap Scanning dilakukan dengan mencari informasi seperti IP, MAC dan port pada jaringan. Tahap ketiga adalah Exploitation melakukan penetrasi menggunakan teknik sniffling, Sniffling yang digunakan adalah ARP Poisoning, pada tahap Maintaining Access dilakukan MITM Attack kemudian ditemukan celah keamanan pada bagian protokol komunikasi MQTT yang digunakan, hal yang sama dilakukan pada MQTTS sebagai pembanding. Hasil implementasi tersebut ditemukan bahwa data yang dikirim melalui protokol MQTT dapat dibaca oleh penyerang dengan melakukan ARP Poisoning dan MITM Attack dapat memodifikasi packet data sehingga packet tidak sampai ke tujuan sedangkan pada protokol MQTTS ARP Poisoning dapat dilakukan namun data terenkripsi sehingga MITM Attack tidak dapat dilakukan
Customer Engagement Transformation: A Critical Factor for Successful Digital Transformation Strategies in the Transportation Industry Ankhal, Rian Bimo; Lubis, Muharman; Fakhrurroja, Hanif
SENTRI: Jurnal Riset Ilmiah Vol. 5 No. 1 (2026): SENTRI : Jurnal Riset Ilmiah, Januari 2026
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/sentri.v5i1.5455

Abstract

Customer engagement transformation is a key aspect in developing digital transformation strategies in today's workplace. This paper aims to present an analysis of critical success factors (CSFs) that influence customer engagement transformation within the context of digital transformation strategies. The research methodology involves a combination of in-depth case studies of several organizations that have successfully implemented digital transformation strategies with a focus on employee engagement. Customer surveys, interviews with organizational leaders, and internal document analysis are the primary instruments for data collection. This paper will discuss the implications of using the latest technology, digital collaboration platforms, and supportive leadership approaches in achieving customer engagement transformation. We will also explore the impact of factors such as work-life balance, skills development, and organizational culture on the success of transformation strategies.
Association Analysis Between Public Sentiment and Grab Stock Performance Using SVM and Lambda Test Dita Pramesti; Hanif Fakhrurroja; Rahma Karina M.
IJoICT (International Journal on Information and Communication Technology) Vol. 11 No. 1 (2025): Vol. 11 No. 1 Jun 2025
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/ijoict.v11i1.9152

Abstract

During a period of strong economic performance in Indonesia—marked by a 5.4% growth in the second quarter of 2022—concerns about a potential downturn in the fourth quarter began to surface, as indicated by increased stock market volatility, including fluctuations in Grab’s share prices. This study aims to classify public sentiment toward Grab based on comments from the social media platform Twitter, and to analyze its relationship with the direction of the company’s stock price movement. Sentiment classification was conducted using the Support Vector Machine (SVM) algorithm through a series of steps including data preprocessing, TF-IDF weighting, imbalance data handling, and model performance evaluation. The dataset was split into 70% training data and 30% testing data. The SVM model achieved an accuracy of 87%, with a precision of 90%, recall of 91%, and F1-score of 91%. Public sentiment for each period was then aggregated using the Net Sentiment Score (NSS), which was subsequently categorized into positive or negative sentiment. These sentiment categories were analyzed in relation to stock price movements using the Goodman-Kruskal Lambda test. The result of ????(stock∣sentiment)=0.053 indicates that knowing public sentiment reduces prediction error by only 5.3%, while ????(sentimen|saham)=0.000 shows no predictive value in the opposite direction. This study contributes a novel approach by integrating machine learning-based sentiment classification with a categorical association test, specifically applied to a regional technology company in Southeast Asia, which remains underexplored in existing literature.
Multi-Output Classification of Cognitive Levels and Topics in Indonesian Questions using Deep Learning and Transformers Orvalamarva, Orvalamarva; Pratiwi, Oktariani Nurul; Fakhrurroja, Hanif
International Journal of Advances in Data and Information Systems Vol. 7 No. 1 (2026): April 2026 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

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

Abstract

Managing large-scale digital question banks struggles with manual metadata labeling, especially when identifying material topics and cognitive levels based on the Revised Bloom's Taxonomy. Current automated approaches usually treat these two attributes as separate tasks, which adds to the system's complexity and computational load. This study introduces a multi-output classification method using a shared encoder architecture with two task-specific heads to predict topics and cognitive levels simultaneously. We performed experiments on 685 Indonesian junior high science questions, covering 15 topic labels and four cognitive levels (C1–C4), with an imbalanced distribution in which lower cognitive levels accounted for more than 75% of the dataset. To handle this imbalance, we applied Focal Loss to taxonomy classification, and class weighting was used in the comparison model. A comparative study involved CNN, BiLSTM, DistilBERT, and IndoBERT. Our results demonstrate that IndoBERT delivered the best performance, with F1-macro scores of 0.78 for topics and 0.71 for cognitive levels and showed better performance in minority classes compared to standard cross-entropy-based models. These findings suggest that an integrated multi-output approach can boost the efficiency and accuracy of question labeling and offers potential for integration into Computer-Based Test systems and e-assessment platforms in real time.
Co-Authors Adi Sutrisno Adi Waskito Adillah, Muhammad Fauzan Nur Agus Sutanto Agustiana, Nathifa Ahmad Musnansyah Andry Alamsyah Andy Victor Pakpahan Anindya Prameswari Putri Djakaria Ankhal, Rian Bimo Anto Tri Sugiarto Arif Abdul Aziz Aris Munandar Asriana Asriana, Asriana Azwar Farrel Wirasena Betty Natalie Fitriatin Binashir Rofi’ah Carmadi Machbub Cindy Septiani Hudaya Deden Witarsyah Deni Kurnia Denis Gresan Yubelas Deris Stiawan Dermawan, M Farhan Hussaini Derry Destian Didit Adytia Dina Angela Dini Dwi Andayani Dita Pramesti Djakaria, Anindya Prameswari Putri Edy Tanu Elsa Melati Nurrachmat Emma Trinurani Sofyan Erlangga, Gilang Faishal Mufied Al Anshary Faishal Mufied Al-Anshary Firdaus, M Ridwan Fitri Widiantini Ghifari, Raden Faqih Hilmiy Hakim, Aqil Rahman Hans Melkisedek Simanjuntak Hariyadi , Joniko, Joniko Karina M., Rahma Kemahyanto Exaudi Lidanta, Fairuz Zahirah Lovely Son, Lovely Mahardiono, Novan Agung Marno Marno Mimin Muhaemin Muharman Lubis Nopendri Nopendri Novan Agung Mahardiono Novan Agung Mahardiono Novan Agung Mahardiono Nuryatno, Edi Triono Oktariani Nurul Pratiwi Orvalamarva, Orvalamarva Permatasari, Yessy Prahastiwi, Narita Ayu Prima Audina Wibowo Puspitasari, Devi Ambarwati Putra Perdana Prasetyo, Aditya Rahayu, Indah Sari Rahma Karina M. Rahman, Jodi Rizki Rahmat Budiarto Rahmat Mulyana Rais, Muhammad Haidar Ramdhani, Fiqri Rimba Pratama Putra Rukmana, Putri Utami Sadewa, Rizki Salsabila, Syifa Aria Sarmayanta Sembiring Sendhitasari, Aulia Ferina Seno Adi Putra Setyorini Setyorini Sudaryati Cahyaningsih Sugiono, - Sutoyo, Edi Tanu, Edy Tatang Mulyana Tien Fabrianti Kusumasari Triwangsa, Mochamad Cory Sakti Tualar Simarmata Utama, Muhammad Hasbi Juri V. Luvita Veithzal Rivai Zainal Veny Luvita Veny Luvita Wibowo, Jony Winaryo Wibowo, Nanang Roni Widianto Soekarnen Wijaya, I Made Darma Putra Yolanda, Mitra Marlina Zuhdi, Hafidh