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All Journal JIK Jurnal Ilmu Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Komputasi JUTEKIN (Jurnal Manajemen Informatika) Jurnal Teknologi Informasi dan Terapan (J-TIT) Journal of Applied Engineering and Technological Science (JAETS) Generation Journal JATI (Jurnal Mahasiswa Teknik Informatika) Journal of Intelligent Computing and Health Informatics (JICHI) Jurnal Teknik Informatika (JUTIF) International Journal for Applied Information Management Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) JURNAL TEKNIK INFORMATIKA DAN KOMPUTER Jurnal Sistem Informasi, Akuntansi dan Manajemen Journal of Current Research in Blockchain Smatika Jurnal : STIKI Informatika Jurnal Jurnal Komputasi
Tarigan, Masmur
Universitas Esa Unggul Jakarta Indonesia
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Medicine & Pharmacology Public Health Social Sciences

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Analysis of Gas Fee Patterns in Blockchain Transactions - A Case Study on Ethereum Smart Contracts Paramitha, Adi Suryaputra; Tarigan, Masmur
Journal of Current Research in Blockchain Vol. 2 No. 3 (2025): Regular Issue September 2025
Publisher : Bright Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jcrb.v2i3.41

Abstract

Gas fees play a crucial role in Ethereum blockchain transactions, directly affecting the cost and efficiency of decentralized applications. This study analyzes gas fee patterns across transaction types, temporal trends, and anomalous behaviors using a dataset of 1,000 Ethereum transactions. The results reveal that the average gas price was 120.5 Gwei, with a standard deviation of 45.2 Gwei, highlighting significant variability. Smart contract functions exhibited varying gas usage, with mint operations consuming the highest average gas (1,500,000 units) compared to approve (1,200,000 units) and transfer (800,000 units). A positive correlation (r = 0.65) was observed between gas price and value transferred, suggesting that higher-value transactions often incur elevated gas fees. Temporal analysis showed predictable patterns, with peak gas prices occurring between 13:00 - 17:00 UTC during high network activity and lower prices between 02:00 - 06:00 UTC. Additionally, anomaly detection identified 15 outlier transactions, including one with an unusually high gas price of 500 Gwei, reflecting network congestion or prioritization strategies. These findings provide actionable insights for optimizing transaction costs and improving smart contract efficiency. Future research could explore layer-2 scaling solutions, alternative fee mechanisms, and machine learning approaches for gas price prediction. This study contributes to a deeper understanding of Ethereum’s gas fee dynamics, offering valuable guidance for developers, users, and researchers in the blockchain ecosystem.
Fault-Tolerant Telegram Bot Architecture for Odoo 14: Validated Production Reporting in Flexible Packaging Tarigan, Masmur; Paramita, Adi Suryaputra; Dewi, Deshinta Arrova
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 6 (2025): JUTIF Volume 6, Number 6, Desember 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.6.5515

Abstract

In flexible-packaging manufacturing, manual reporting dramatically delays synchronization with the ERP — and that means operational  latency and traceability issues. The proposed work is the design, implementation, and validation of a fault-tolerant Telegram bot interconnected with Odoo 14 for six production departments. Our bot architecture that combines conversational workflows with schema-based validation and XML-RPC for slow, large payloads, enables accurate and  timely reporting. In a four-week pilot with 1,066 production entries, we achieved 98.7% field completeness and lowered reporting latency to less than 2 minutes. Manual  baselines received 75% more requests for corrections. At disconnected state, the layered middleware of the system abstracted retry logic and media ingestion. Both SDG 9 (Resilient infrastructure, including ) and SDG 12 (Continue to reduce production waste at source, including consumables) are connected to the work presented here which evidence the feasibility of automatic conversational interfaces with a computer in the manufacturing informatics domain, and provide pathways towards scalable digital transformation and sustainability in the small-to-medium industry sector.
Klasifikasi Status Gizi Anak dengan Metode Decision Tree (Studi Kasus di RS AN-NISA) Berbasis Web Michael Julius Hutabarat; Dwi Sartika Simatupang; Masmur Tarigan; Y Yulhendri
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 01 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i01.2238

Abstract

Penelitian ini mengembangkan model klasifikasi status gizi anak usia 0–5 tahun berbasis web menggunakan algoritma Decision Tree (C4.5) pada data antropometri RS AN-NISA Tangerang periode Januari–Desember 2024. Atribut yang digunakan meliputi umur (bulan), jenis kelamin, berat badan, dan tinggi badan, dengan label status gizi yang diklasifikasikan ke dalam kategori Gizi Kurang, Gizi Baik, dan Gizi Lebih. Data diproses melalui tahapan preprocessing yang mencakup pembersihan data kosong dan nilai ekstrem, seleksi atribut, encoding data kategorikal, normalisasi, serta pembagian data sebesar 80% data latih dan 20% data uji. Model dibangun menggunakan kriteria entropy dengan pengaturan hyperparameter untuk mengurangi risiko overfitting, kemudian dievaluasi menggunakan metrik accuracy, precision, recall, dan F1-score, serta dibandingkan dengan model baseline Logistic Regression. Hasil evaluasi menunjukkan bahwa Decision Tree mencapai nilai akurasi sebesar 96,12% dan recall macro 89,49%, yang lebih unggul dibandingkan Logistic Regression. Selanjutnya, model diserialisasi dan diintegrasikan ke dalam aplikasi berbasis Flask untuk memfasilitasi input data dan menghasilkan prediksi status gizi secara langsung. Hasil pengujian black box dan User Acceptance Test (UAT) menunjukkan tingkat kepuasan pengguna sebesar 88%, sehingga sistem dinilai layak digunakan sebagai alat bantu deteksi dini status gizi anak pada layanan kesehatan sehari-hari.
Perancangan Sistem Monitoring Detak Jantung Bagi Penderita Kardiovaskular Berbasis Internet of Things Muhamad Bahrul Ulum; Masmur Tarigan
Jurnal Komputasi Vol. 8 No. 1 (2020)
Publisher : Jurusan Ilmu Komputer Fakultas MIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v8i1.2419

Abstract

The form of an archipelago and densely populated country of Indonesia has its own constraints in efforts to deal with health, especially health for patients with cardiovascular disease. This disease is one of the highest causes of death in Indonesia. Based on data from the Ministry of Health, cardiovascular disease since 2007 is the highest cause of death in Indonesia with more than 220,000 deaths each year. While the number of cases exceeds tuberculosis, which has a death toll of 127,000. The number is increasing every year due to changes in lifestyle of Indonesian people who like to eat high-fat foods and lifestyle factors that affect the risk of cardiovascular disease, including lack of physical activity, smoking, high-fat diets, and alcohol consumption habits. This study aims to monitor the heart rate of cardiovascular sufferers with the internet of things (IoT) approach. Every patient with cardiovascular disease can be monitored using a sensor connected to a PC to record any changes that occur. The research method consists of several stages, namely: Prepare, Plan, Design, Implement, Operate and Optimize (PPDIOO). The results obtained in the form of a prototype heart rate monitoring system for patients with cardiovascular. The patient's health can be monitored at any time by the hospital doctor without the patient having to come regularly to the hospital.
Co-Authors Adhy, Dewanto Rosian Adi Suryaputra Paramita Adven Kristianata Ahmad Johadi Alexander AS Gunawan Budi Tjahjono Dewi, Deshinta Arrova Dini Handayani Dwi Sartika Simatupang Evelyn Fajrianto, Rendi Ford Lumban Gaol Futri Ramadhani, Kareena Huda, Saeful Ilham Mukti, Raulian Kristiawan, Agus Kundang Karsono Juman Michael Julius Hutabarat Mukhamad Abduh Nanda Pratama Nizirwan Anwar Nur Widiyasono, Nur Paramitha, Adi Suryaputra Rizki Ramadhan Rizki Ramadhan Rudi Hermawan Sandri Alfarisi Suryodiningrat, Satrio Pradono Susanto, Yudi Ulum, Muhamad Bahrul Widodo Budiharto Y Yulhendri Yudi Susanto Yulhendri Yulhendri