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All Journal Sistemasi: Jurnal Sistem Informasi RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) Cyber Security and Network Management
Sri Titi Handayani
Universitas Komputer Indonesia
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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PENERAPAN CONVOLUTIONAL NEURAL NETWORK UNTUK PENGENALAN BAHASA ISYARAT INDONESIA: STUDI KASUS DAN TINJAUAN FILSAFAT SAINS Hernalom Sitorus; Ucu Nugraha; Sri Titi Handayani; Agus Nursikuwagus; Usep Mohamad Ishaq; Andrias Darmayadi
Jurnal Ilmiah Teknologi Infomasi Terapan Vol. 12 No. 2 (2026)
Publisher : Universitas Widyatama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33197/jitter.vol12.iss2.2026.3448

Abstract

The low literacy of Indonesian Sign Language (BISINDO) in the general public remains a barrier to communication with the Deaf community, while research on AI-based sign language recognition generally focuses solely on technical achievements. This study aims to develop a BISINDO alphabet recognition system based on Convolutional Neural Network (CNN) and evaluate it through a philosophy of science perspective. The methods used include collecting a BISINDO alphabet hand image dataset, data augmentation, and transfer learning-based CNN training with the MobileNetV2 architecture and a stepwise training scheme, then deployed to Android using TensorFlow Lite. Test results show the system is able to achieve an accuracy of around 93% on controlled test data with stable real-time inference performance. The scientific contribution of this research is not only in the development of applied AI systems, but also in providing a reflective ontological, epistemological, and axiological framework to assess the validity and social implications of BISINDO recognition technology.
Open Government Data Analytics of Tourist Visits In West Java 2014–2024: A Data Science and Philosophy of Science Perspective Ucu Nugraha; Hernalom Sitorus; Sri Titi Handayani; Agus Nursikuwagus; Usep Mohamad Ishaq; Andrias Darmayadi
SISTEMASI Vol 15, No 4 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Universitas Islam Indragiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i4.6175

Abstract

Open Government Data (OGD) in tourism provides opportunities for data-driven analytics to support destination management policies. In policy practice, tourism OGD is often accepted at face value as a direct representation of real-world conditions, even though such data are constructed through definitions, recording procedures, and measurement choices. Therefore, a philosophy of science perspective is essential in data governance. This article analyzes an Open Data Jabar dataset on the number of tourist visits by visitor type and district/city in West Java Province for the period 2014–2024 (n = 565; 27 districts/cities; two visitor categories: domestic and international). The data science approach includes data quality auditing (completeness and consistency), time-series aggregation, spatial concentration measurement using the Gini coefficient, and a comparison of shock–recovery patterns in tourist visits before and after the pandemic. The results indicate a decline in total visits of -50.6% in 2020 compared to 2019, with international visits experiencing the sharpest drop (-82.8%). By 2024, total visits reached 64,517,298, dominated by domestic tourists (63,963,443; international share 0.9%). Spatial concentration in 2024 is reflected by a Gini coefficient of 0.429, with the top five regions accounting for 44.2% of total visits. The discussion emphasizes that visitor counts are epistemic representations shaped by definitions, reporting practices, and data cleaning processes. Therefore, policy recommendations should be accompanied by data provenance, metadata, and explicit uncertainty annotations to avoid the reification of indicators.
Systematic Literature Review (SLR) On Consensus Mechanism In Cyber-Physical System (CPS) For Smart Farm Performance Optimization) Sri Titi Handayani; Zainal Arifin Hasibuan; Sri Supadmi
Cyber Security and Network Management Vol. 1 No. 2 (2026): May: Cyber Security and Network Management
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/cybernet.v1i2.393

Abstract

This study aims to analyze the consensus mechanism on the Cyber-Physical System (CPS) to optimize smart farm performance through the Systematic Literature Review (SLR) approach. CPS integration is a fundamental component in smart farms as it allows real-time coordination of sensors, actuators, and computing devices to produce accurate and adaptive farming decisions. However, a dynamic and heterogeneous farming environment demands an efficient, stable, and energy-efficient consensus mechanism so that all nodes in the network can reach a consistent agreement on data or actions. Through SLR on 30 studies, this study found that the consensus mechanism was able to increase sensor synchronization by up to 30%, reduce latency by 27%, decrease water consumption by 19%, increase sensor response by 31%, and improve data security by up to 22%. Several consensus approaches such as average consensus, multi-sensor consensus, secure consensus, edge-based consensus, and fault-tolerant consensus have been proven to improve the accuracy of environmental monitoring, accelerate automatic irrigation response, optimize precision fertilization, and strengthen information search in unstable signal conditions. In addition, consensus in CPS shows a significant role in handling smart farm big data as well as strengthening system resilience to disruptions. However, this study also identified a research gap related to the need for a consensus model that is lighter, adaptive, and in accordance with the characteristics of tropical agriculture such as in Indonesia. These SLR findings provide a direction for the development of more efficient, secure, and sustainable consensus-based CPS for future smart farm implementation.
INDEKS RISIKO BENCANA PARIWISATA DAN KLASTER KABUPATEN KOTA JAWA BARAT BERBASIS DATA WISATA 2020–2024: TOURISM DISASTER RISK INDEX AND CLUSTERING OF WEST JAVA REGENCIES AND CITIES BASED ON TOURISM DATA (2020–2024) Ucu Nugraha; Sri Titi Handayani; Hernalom Sitorus; Bobi Kurniawan S; Adam Mukharil Bachtiar; Ednawati Rainarli; Hanhan Maulana
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7294

Abstract

West Java Province is one of Indonesia’s leading tourism destinations and, at the same time, a region with a high incidence of disasters. However, available disaster risk information such as the Indonesian Disaster Risk Index and the West Java Provincial Disaster Risk Assessment remains broad in scope and has not explicitly integrated the tourism dimension. This study aims to develop a Tourism Disaster Risk Index at the regency/municipality level in West Java Province by utilizing data on the number of disaster events, the number of disaster victims during the 2020–2024 period, and the number of tourism destination objects, while also clustering regions to construct a disaster-based typology of tourism risk. The methods include: (1) aggregating five-year disaster event and victim data by regency/municipality; (2) calculating the total number of tourism destination objects (natural, cultural, and man-made); (3) applying min–max normalization to produce partial indices for events, victims, and tourism destination objects; (4) constructing a composite Tourism Disaster Risk Index using weights of 0.4:0.4:0.2, in which hazard (events) and impact (victims) are deliberately assigned greater weights than tourism exposure as a conceptual decision aligned with disaster risk frameworks that prioritize life safety and physical damage; and (5) applying the K-Means algorithm (k = 3) to perform clustering based on the partial indices. The results show that the Tourism Disaster Risk Index (0–100 scale) ranges from 0.76 to 56.70, with a mean of 12.27 and a median of 6.90. A total of 25 regencies/municipalities fall into the low tourism risk category, while Bogor Regency and Cianjur Regency are in the moderate category. The clustering yields three clusters: cluster 1 comprises 21 regencies/municipalities with relatively low tourism risk; cluster 2 includes five regencies (Bogor, Bandung, Garut, Majalengka, and Pangandaran) characterized by moderate risk and a high concentration of destinations; and cluster 3 consists solely of Cianjur Regency as an outlier with exceptionally high disaster impacts. These findings provide a quantitative foundation as well as a prototype decision-support tool for local governments and stakeholders to prioritize resources and design interventions for disaster-resilient tourism development in West Java Province.  
SYSTEMATIC LITERATURE REVIEW BLOCKCHAIN UNTUK TATA KELOLA E-GOVERNMENT: MEKANISME TRANSPARANSI, AKUNTABILITAS, AUDITABILITY, PRIVASI, DAN ADOPSI DI SEKTOR PUBLIK Ucu Nugraha; Sri Titi Handayani; Hernalom Sitorus; Irawan Afrianto; Estiko Rijanto; Irfan Dwiguna Sumitra
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7516

Abstract

Digital transformation in government has intensified the need for public service governance that is transparent, accountable, auditable, and privacy-compliant. Blockchain and smart contracts can strengthen governance through immutability, traceability, and rule automation, yet they introduce transparency–privacy trade-offs, cross-agency interoperability constraints, and socio-technical adoption barriers. This study conducts a Systematic Literature Review (SLR) to synthesize governance mechanisms—transparency, accountability, auditability, and privacy—together with technical implementation patterns and adoption factors in e-government. We searched Scopus using a TITLE-ABS-KEY query with Open Access and English-language filters; PRISMA screening yielded 118 included studies. Results map dominant use cases (general e-government services, digital identity/credentials, e-voting, and cross-agency data sharing) and show that evidence maturity is still prototype-heavy (63/118). A critical finding is pervasive under-reporting of key technical descriptors that weakens synthesis and comparability: 72/118 studies do not specify the blockchain type and 85/118 do not report the platform; 109/118 also omit on-chain/off-chain design. The SLR contributes an evidence map and governance mechanism taxonomy, and can be operationalized as an assessment checklist for governments/consultants to question governance mechanisms, planned outcome metrics, and transparency–privacy trade-offs prior to deployment.
Design of an Artificial Intelligence-based Personalized Learning Governance Framework Ucu Nugraha; Sri Titi Handayani; Hernalom Sitorus; Agus Nursikuwagus; Yeffry Handoko Putra; Rio Yunanto
SISTEMASI Vol 15, No 7 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Universitas Islam Indragiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i7.6545

Abstract

The rapid advancement of Artificial Intelligence (AI) in education has created significant opportunities for personalized learning while simultaneously introducing governance challenges for learners with disabilities. Existing studies have examined AI, adaptive learning, accessibility, and inclusive education; however, these areas remain fragmented and lack an integrated governance-oriented framework. This study aims to develop a Personalized Learning Governance Framework (PLGF) to support inclusive digital literacy through a systematic literature review and bibliometric analysis. The research methodology consisted of Scopus database retrieval, PRISMA-based screening, Biblioshiny-assisted bibliometric analysis, literature synthesis, gap identification, and conceptual framework development. From 196 Scopus-indexed records published between 2023 and 2026, a total of 97 studies were selected for analysis. The findings reveal strong conceptual relationships among AI, personalized learning, inclusive education, accessibility, disability, and ethical technology; however, their systematic integration remains limited. The proposed Personalized Learning Governance Framework (PLGF) comprises five interconnected layers: Learner Disability Profile Input, Machine Learning Personalization Engine, Inclusive Accessibility Adaptation, Governance and Ethical Control Center, and Digital Literacy Outcome Evaluation. The framework provides a comprehensive governance model for supporting accountable, inclusive, and AI-driven personalized learning systems while promoting equitable digital literacy for learners with disabilities.
Co-Authors Adam Mukharil Bachtiar Agus Nursikuwagus Andrias Darmayadi Bobi Kurniawan S Ednawati Rainarli Estiko Rijanto Hernalom Sitorus Irawan Afrianto Irfan Dwiguna Sumitra Maulana, Hanhan Rio Yunanto Sri Supadmi Ucu Nugraha Ucu Nugraha Usep Mohamad Ishaq Yeffry Handoko Putra Zainal Arifin Hasibuan