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All Journal Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika
Ratih Titi Komala Sari, Ratih Titi Komala
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Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Rancang Bangun Game Birokrasi Penyelenggaraan Kegiatan Kemahasiswaan Menggunakan Metode Finite State Machine Puspita, Anna Thasyia; Andryana, Septi; Sari, Ratih Titi Komala
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol 4 No 1 (2020)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (826.886 KB) | DOI: 10.31961/eltikom.v4i1.141

Abstract

Organisasi dan kegiatan kemahasiswaan adalah hal yang tidak dapat dipisahkan. Kurangnya pengetahuan anggota organisasi tentang birokrasi penyelenggaraan kemahasiswaan disebabkan oleh kurangnya edukasi sebelum pendaftaran organisasi. Berdasarkan permasalahan yang telah diuraikan, maka dibuat game tentang birokrasi penyelenggaraan kegiatan kemahasiswaan dengan tujuan menjadi media pembelajaran kepada calon anggota organisasi tentang prosedur penyelenggaraan kegiatan kemahasiswaan. Game ini dirancang menggunakan metode Finite State Machine dengan tujuan memberikan edukasi terhadap pengguna tentang proses penyelenggaraan kegiatan kemahasiwaan. Dari hasil pengujian game menggunakan skala likert didapat persentase rata – rata 96,76% pengguna menyatakan bahwa game telah sesuai dengan fungsinya, maka dapat dikatakan game ini memenuhi tujuan awal pembuatannya yaitu menjadi media pembelajaran kepada calon anggota organisasi tentang prosedur penyelenggaraan kegiatan kemahasiswaan.
MCDM-Based Blockchain and Artificial Intelligence Integration for Earthquake Risk Recommendation System Widianto, Aditya; Sari, Ratih Titi Komala; Hindarto , Djarot; Sani, Asrul
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 4 (2025): Articles Research October 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i4.15437

Abstract

Indonesia is one of the countries with the highest earthquake vulnerability in the world because it is located at the meeting point of three major tectonic plates, namely Eurasia, Indo-Australia, and Pacific. The high risk of disaster requires a system that is capable of analyzing, predicting, and recommending earthquake-prone areas accurately, efficiently, and safely. This study aims to develop an earthquake risk recommendation system based on the integration of Artificial Intelligence (AI), Multi-Criteria Decision Making (MCDM), and Ethereum Blockchain. Earthquake data was obtained from Google Earth Engine (GEE) and geospatial data from the Geospatial Information Agency (BIG) and BMKG. The data is processed using AI algorithms for predictive analysis, then the MCDM methods of TOPSIS, and ELECTRE are applied to determine the priority of earthquake-prone areas based on a combination of seismic parameters, population density, infrastructure vulnerability, and distance to active faults. The analysis results are stored in a decentralized manner using the Ethereum Blockchain through smart contracts to ensure data integrity, security, and transparency. The research results show that the integration of AI–MCDM is capable of providing earthquake risk recommendations with high accuracy, while the application of blockchain ensures that the results cannot be manipulated. This system is expected to become a decision-making tool for disaster management agencies such as BMKG and BNPB in data-based earthquake risk mitigation.
Blockchain Disaster-Relief DApps with SVM and Data Anchors for Fraud-Prevention Ardhi, Agil Zaky; Sari, Ratih Titi Komala; Nathasia, Novi Dian; Ningsih, Sari
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 1 (2026): Article Research January 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i1.15522

Abstract

VoucherAid and DataAnchor are prototype DApps for disaster-relief voucher processing that integrate on-chain rule enforcement, cryptographic data anchoring through fixed-size hash commitments, and an off-chain SVM-based analytics gateway. VoucherAid issues non-transferable vouchers, restricts redemption to certified merchants, and emits auditable events, while DataAnchor records time-stamped digests to support provenance verification without exposing sensitive content. A 200-record dataset was generated from on-chain logs and enriched with behavioral–temporal features derived from redemption activity. Experiments conducted in a single-node Ganache environment using a 70:30 split show that the SVM achieves 0.75 accuracy with perfect precision but limited recall for fraud (1.00 precision, 0.32 recall, 0.48 F1), indicating that the model cannot serve as a reliable stand-alone detector and is more appropriate as a conservative decision-support tool under human oversight. The prototype demonstrates that separating on-chain enforcement from off-chain analytics can enhance auditability and support model evolution without contract redeployment. However, the findings remain constrained by the small, partially synthetic dataset, the single-node evaluation environment, and programmatic labeling. Future work will expand datasets, incorporate richer temporal and graph-based features, adjust thresholds and class weights, and evaluate the system on multi-node networks to improve fraud recall while maintaining usability and inclusion.
Co-Authors Ardhi, Agil Zaky Asrul Sani Hindarto , Djarot Novi Dian Nathasia Puspita, Anna Thasyia Sari Ningsih Septi Andryana Vebiant, Kiki Wahyuddin, Mohammad Iwan Widianto, Aditya