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All Journal TEKNIK INFORMATIKA Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Transformasi: Jurnal Pengabdian Masyarakat Sistemasi: Jurnal Sistem Informasi JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) Jurnal Sisfokom (Sistem Informasi dan Komputer) SEIKO : Journal of Management & Business Jiko (Jurnal Informatika dan komputer) JURIKOM (Jurnal Riset Komputer) YUME : Journal of Management Journal of Humanities and Social Studies JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Media Informatika JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Management and Bussines (JOMB) Journal of Education Research Universitas Muhammadiyah Yogyakarta Undergraduate Conference Proceeding eProceedings of Engineering Jurnal Hukum Caraka Justitia Electronic Integrated Computer Algorithm Journal JER Journal of Production, Enterprise, and Industrial Applications Proceeding of Community Service and Engagement JRTI (Jurnal Riset Tindakan Indonesia)
Lukman Abdurrahman
Telkom University
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Public Health Social Sciences Other

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Peningkatan Kapabilitas UMKM Mr. Mangkok Ricebowl melalui Pelatihan dan Pedampingan Sertifikasi Halal Berbasis Dokumen SJPH Endang Chumaidiyah; Sinta Aryani; Lukman Abdurrahman; Muhammad Faza Zharfan; Muhamad Daffa Rial
The Proceeding of Community Service and Engagement (COSECANT) Seminar Vol. 5 No. 2 (2025): Prosiding COSECANT : Community Service and Engagement Seminar
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/cosecant.v5i2.10376

Abstract

Kegiatan pengabdian masyarakat ini bertujuan meningkatkan kapabilitas UMKM Mr. Mangkok Ricebowl dalam mempersiapkan sertifikasi halal melalui pelatihan dan pendampingan berbasis dokumen Sistem Jaminan Produk Halal (SJPH). Mitra merupakan usaha kuliner di Kabupaten Bandung, Jawa Barat, yang beroperasi pada dua lokasi layanan, yaitu Outlet Permata Buahbatu (PBB) dan outlet di sekitar Fakultas Industri Kreatif Telkom University. Metodologi kegiatan mencakup identifikasi kebutuhan mitra, pelatihan tatap muka di dalam ruangan kepada lima peserta, serta pendampingan penyusunan artefak kunci SJPH berupa rekapitulasi pembelian bahan tiga bulan terakhir, penataan fasilitas dan alur kerja, serta instrumen evaluasi pemahaman. Temuan utama menunjukkan tersusunnya denah fasilitas untuk kedua outlet sebagai dasar pemetaan titik kritis halal dan pemisahan area kerja, serta tersedianya pre-test dan post-test yang dapat digunakan untuk mengukur pemahaman internal secara periodik. Orisinalitas kegiatan terletak pada integrasi pendampingan dokumen SJPH dengan pemetaan fisik fasilitas dan evaluasi pembelajaran sebagai satu paket kesiapan sertifikasi yang mudah direplikasi pada UMKM pangan. Implikasi kegiatan adalah tersedianya baseline data dan perangkat pengendalian internal yang membantu mitra menutup gap dokumen dan meningkatkan kesiapan pengajuan sertifikasi halal serta keberlanjutan penerapan SJPH. Keywords: halal assurance system, halal certification, MSME, SJPH, training evaluation
Understanding Smart Environment: A Systematic Literature Review Ardhana, Sonia Frisca Putri; Prasetyo, Yuli Adam; Mukti, Iqbal Yulizar; Abdurrahman, Lukman
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 4 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i4.6539

Abstract

In the rapidly evolving era of technological advancements, the concept of a Smart Environment emerges as a pivotal innovation in addressing the complex challenges of environmental sustainability. This study aims to provide a comprehensive evaluation of the Smart Environment's effectiveness in meeting urban community needs, while elucidating the synergy between business functions and the technological frameworks that drive the development of such environments. Utilizing a Systematic Literature Review (SLR) methodology, this research explores the terminologies, models, and technologies integral to the Smart Environment, focusing on their practical applications in sectors such as energy management, transportation, and natural resource conservation. The findings highlight the crucial role of the Internet of Things (IoT) in enhancing efficiency and sustainability, alongside the importance of robust data security and interoperability standards. This study not only contributes to a deeper understanding of the Smart Environment's impact on urban life but also serves as a valuable resource for future research, providing insights into the integration of societal needs with technological advancements to create sustainable, efficient, and intelligent urban environments.
The role of information systems in the digital transformation of palm oil plantations: a systematic literature review Muhammad Fitrah Sulthon; Lukman Abdurrahman
JRTI (Jurnal Riset Tindakan Indonesia) Vol. 10 No. 4 (2025): JRTI (Jurnal Riset Tindakan Indonesia)
Publisher : IICET (Indonesian Institute for Counseling, Education and Therapy)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/30036575000

Abstract

This study examined the role of information systems in supporting digital transformation in oil palm plantations using a systematic literature review (SLR). Despite the increasing adoption of digital technologies, the strategic integration of information systems in plantation management remains limited. The review was conducted by searching three major scientific databases Scopus, Web of Science, and Google Scholar for articles published between 2020 and 2025. A total of 127 articles were initially identified, of which nine studies were selected based on predefined inclusion and exclusion criteria, including relevance to oil palm plantations, focus on information systems, and methodological rigor. The quality of the selected articles was assessed using a structured evaluation framework to ensure reliability. The results showed that 89% of the reviewed studies reported significant improvements in operational efficiency and data accuracy, while 78% highlighted enhanced decision-making supported by information systems. Web-based and integrated systems were the most commonly implemented technologies, appearing in 67% of the studies, particularly for data integration, monitoring, and reporting. However, 56% of the studies identified human resource limitations and 44% reported system integration issues and organizational resistance as major barriers. The study concluded that information systems serve not only as operational tools but also as strategic enablers of sustainable digital transformation in oil palm plantations, emphasizing the need for integrated systems and strong organizational support.
Bank Mandiri Stock Performance Prediction Via SVM, LSTM, and Random Forest Rambe, Rahmat; Fakhrurroja, Hanif; Abdurrahman, Lukman
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 15 No. 02 (2026): MAY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v15i02.2589

Abstract

Reliable stock price prediction is critical for effective investment decisions; however, high volatility and nonlinear dynamics continue to challenge forecasting accuracy. Despite the extensive use of machine learning in financial research, short-term comparative studies on Indonesian banking stocks remain scarce. This study evaluates the performance of Support Vector Machine (SVM), Long Short-Term Memory (LSTM), and Random Forest models in predicting Bank Mandiri’s stock prices using daily data from Yahoo Finance covering June to December 2024. The data, including price indicators and trading volume, were normalized, transformed into time-series sequences, and divided into training and testing sets. SVM was applied for directional classification, while LSTM and Random Forest were used for regression-based price prediction. Model performance was assessed using accuracy and mean squared error (MSE). The findings show that LSTM achieves the lowest prediction error (MSE = 0.0045), indicating superior ability to model temporal and nonlinear price patterns. In contrast, Random Forest records the highest classification accuracy (0.9932), demonstrating strong performance in predicting price direction. Overall, LSTM is most effective for short-term price forecasting under volatile market conditions, whereas Random Forest remains a robust option for directional classification.
FinBERT-Based Sentiment Integration in Hybrid CNN– BiLSTM Models For Stock Price Forecasting Pawitra, Mohammad Tyas; Abdurrahman, Lukman; Fakhrurroja, Hanif
JURNAL TEKNIK INFORMATIKA Vol. 19 No. 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v19i1.49466

Abstract

This study investigates sentiment-aware deep learning models for short-term stock price forecasting using NVIDIA (NVDA) as a representative high-volatility technology stock. Four architectures—CNN, LSTM, BiLSTM, and a hybrid CNN–BiLSTM—are evaluated under two configurations: without sentiment and with FinBERT-based financial news sentiment integrated as a continuous contextual feature. Historical OHLV data are combined with sentiment information to enable multimodal learning under a controlled experimental setting. The results demonstrate that recurrent architectures consistently outperform convolution-only models, highlighting the importance of temporal dependency modeling in financial time series. Among all configurations, the hybrid CNN–BiLSTM with FinBERT sentiment achieves the best overall performance, yielding the highest R², the lowest MAE and RMSE, and the smallest overfitting gap. Bootstrap-based confidence intervals indicate stable generalization, while Wilcoxon signed-rank tests confirm that the observed performance improvements are statistically significant. The study also presents a near real-time deployment framework with low inference latency, demonstrating practical applicability for decision-support systems. Overall, the findings show that effective alignment between local feature extraction, bidirectional temporal modeling, and contextual sentiment integration is critical for improving stock price.  forecasting accuracy and robustness.
Co-Authors Abdulmana, Sahidan Adinda Laras Ayu Alqahtani, Raied Ali Anindya Tyas Wulandari Ardhana, Sonia Frisca Putri Ari Fajar Santoso Ayta Boangmanalu Ayu, Adinda Laras Azzahra, Nilam Eria BASUKI RAHMAD Bremana , Rhiko Candido , Wan Liufang Bagus Deden Witarsyah Dinda Sekar Cendani Djusnimar Zultilisna Doloksaribu, Lastri M. A Endang Chumaidiyah Erlangga, Faezal Estiningtyas, Elysia Fakhrurroja , Hanif Fakhrurroja, Hanif Fasya, Muhammad Haikal Fauzi, Rokhman Firdaus, Fitri Adini Fitrah Sulthon, Muhammad Fredella, Anisah Fritasya Dwiputri Suryoputro Garcia-Constantino, Matias Ghina Khaerunnisa Ikhlas Fuad Zamzami Ikhsan , Alif Muhammad Iqbal Santosa Iqbal Santoso Karina Tarigan Kinanti Andaiary Kresnaufal Nur Fadhillah Luthfi Ramadani Matias Garcia-Constantino Moch Arif Bijaksana Muhamad Daffa Rial Muhammad Fadhly Arham Muhammad Faza Zharfan Muhammad Fitrah Sulthon Muhammad Haikal Fasya Muharman Lubis Mukti, Iqbal Yulizar Mutiara Natiqoh Purwanto Nadiya Mardiyanti Nandika, Luthfi Rahmansyah Nararya, Sabil Naufal M. Fadilah Nazmi Robbiyani Ningrum, Devi Permata Nurhakim, Maiziah Azka Nurul Afifah Pawitra, Mohammad Tyas Possumah, Mercy Kristina Pradana, Vega Putra Raden Ichsan Achmad Falach Rafian Ramadhani Rahmat Mulyana Rahmat Rambe Raied Ali Alqahtani Ramadhan, Muhammad Firly Ramadhani, Rafian Rio Savero Aranov Risky, Surya Achmad Rismadewi, Kessya Azzahra Riyadi, Muhammad Affan Rizka Putri Wahyuni Rohmat, Mila Ruri Fadhilah Ryan Adhitya Anugrah Ryan Adhitya Nugraha Safitra, Muhammad Fakhrul Sahidan Abdulmana Sandy, Muhammad Dwi Hary Sinandhi, Raihan Achmad Sinta Aryani Tampubolon, Claery Jessica Tania Nielsany Simbolon Taufik Safar Hidayat Tegar Kurnia Fajar Titisari Ramadhane Trias Zulfa Nurafifah Trigama, Ginna Vega Putra Pradana Wiwin Aminah Yudistira, Muhammad Kevin Yuli Adam Prasetyo Zamzami, Ikhlas Fuad