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INDONESIA
INTECOMS: Journal of Information Technology and Computer Science
Published by Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi
ISSN : 26213249     EISSN : 26141574     DOI : -
Core Subject : Science,
Computer Science & IT
Arjuna Subject : -
Articles 4 Documents
 1 
Search results for , issue "Vol. 8 No. 3 (2025): INTECOMS: Journal of Information Technology and Computer Science" : 4 Documents clear
OPTIMIZING DATA CONSISTENCY IN MICROSERVICE ARCHITECTURE USING THE SAGA PATTERN AND EVENT-DRIVEN APPROACH Arif Nurdiansyah; Esa Fauzi
INTECOMS: Journal of Information Technology and Computer Science Vol. 8 No. 3 (2025): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/z8mxcf78

Abstract

An event-driven microservice architecture offers flexibility and scalability but introduces significant challenges in maintaining data consistency across distributed services. Traditional ACID transactions are not viable in such environments, leading to potential data integrity issues during partial failures. This research proposes and evaluates the use of the Saga orchestration pattern as a solution to this problem. A comparative study was conducted by developing two systems in Golang: a baseline system using synchronous inter-service communication and a second system implementing an event-driven Saga pattern with Redis Streams as the event bus. The systems, utilizing MySQL, MongoDB, Redis, and Elasticsearch, were subjected to various failure scenarios. The results demonstrate that the synchronous system consistently produced data inconsistencies during partial failures, while the Saga-based system successfully maintained data integrity by executing compensating transactions, thus restoring the system to a consistent state. The study concludes that the Saga pattern is an effective strategy for optimizing data consistency and reliability in complex microservice architectures.
OPTIMIZING DATA CONSISTENCY IN MICROSERVICE ARCHITECTURE USING THE SAGA PATTERN AND EVENT-DRIVEN APPROACH Arif Nurdiansyah; Esa Fauzi
INTECOMS: Journal of Information Technology and Computer Science Vol. 8 No. 3 (2025): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/z8mxcf78

Abstract

An event-driven microservice architecture offers flexibility and scalability but introduces significant challenges in maintaining data consistency across distributed services. Traditional ACID transactions are not viable in such environments, leading to potential data integrity issues during partial failures. This research proposes and evaluates the use of the Saga orchestration pattern as a solution to this problem. A comparative study was conducted by developing two systems in Golang: a baseline system using synchronous inter-service communication and a second system implementing an event-driven Saga pattern with Redis Streams as the event bus. The systems, utilizing MySQL, MongoDB, Redis, and Elasticsearch, were subjected to various failure scenarios. The results demonstrate that the synchronous system consistently produced data inconsistencies during partial failures, while the Saga-based system successfully maintained data integrity by executing compensating transactions, thus restoring the system to a consistent state. The study concludes that the Saga pattern is an effective strategy for optimizing data consistency and reliability in complex microservice architectures.
Penerapan Data Science Untuk Memprediksi Transaksi Tidak Valid Pada Sistem Voting Berbasis Blockchain Simamora, Daniel; Purba, Yusuf Deardo; Zamili, Kristianos; Notavianus, Finky; Sofhia, Maya
INTECOMS: Journal of Information Technology and Computer Science Vol. 8 No. 3 (2025): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/intecoms.v8i3.15723

Abstract

Keamanan sistem pemungutan suara elektronik (e-voting) berbasis blockchain menjadi perhatian utama di era digital. Penelitian ini bertujuan membangun model evaluasi keamanan e-voting dengan pendekatan data mining, khususnya menggunakan algoritma Support Vector Machine (SVM) dan Random Forest. Dataset yang digunakan terdiri dari lebih dari 500.000 entri transaksi blockchain. Untuk mengatasi ketidakseimbangan kelas antara transaksi sah dan mencurigakan, dilakukan teknik undersampling sehingga diperoleh 100.000 data seimbang sebagai basis pelatihan dan pengujian model. Hasil eksperimen menunjukkan bahwa model Random Forest memiliki akurasi sebesar 95%, namun performanya rendah dalam mendeteksi transaksi mencurigakan, dengan nilai recall hanya 0,00 sebelum tuning dan tetap rendah setelah optimasi. Sebaliknya, model SVM menunjukkan peningkatan signifikan setelah dilakukan hyperparameter tuning, dengan recall pada kelas minoritas meningkat menjadi 0,42 meskipun akurasi keseluruhan menurun menjadi 57%. Temuan ini menunjukkan bahwa model SVM lebih sensitif dalam mengenali pola anomali, meskipun dengan kompromi pada performa kelas mayoritas. Penelitian ini menyoroti tantangan penerapan sistem evaluasi keamanan berbasis machine learning terhadap data blockchain yang tidak seimbang. Diperlukan pengembangan lebih lanjut dengan teknik penanganan data imbalance yang lebih canggih, serta penerapan arsitektur model yang mampu menangani skala besar untuk implementasi secara real-time.
Perancangan Agen AI Lokal Mandiri Berbasis LLM Melalui Orkestrasi N8N Untuk Memori Percakapan Pada RAG Riza, Faizal; Al Din, Sayyid Jamal; Al Afghani, Dhian Yusuf; Setiabudi, Rachmat; Wibisono, Wibisono
INTECOMS: Journal of Information Technology and Computer Science Vol. 8 No. 3 (2025): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/intecoms.v8i3.15839

Abstract

Pemanfaatan model bahasa besar (Large Language Model atau LLM) melalui layanan awan kerap menimbulkan beban biaya dan risiko privasi data. Penelitian ini mengembangkan agen AI lokal berbasis LLM yang terintegrasi dengan N8N, PostgreSQL pgVector, dan Ollama untuk menjawab tantangan tersebut. Sistem yang dirancang bertujuan menciptakan agen AI mandiri yang dapat beroperasi sepenuhnya secara lokal tanpa ketergantungan pada API eksternal. Proses pengembangan melibatkan integrasi orkestrator N8N untuk alur kerja percakapan, penyimpanan memori berbasis vektor melalui pgVector, dan inferensi LLM lokal menggunakan Ollama. Pengujian menggunakan model Mistral:7B menunjukkan bahwa agen mampu menyimpan memori percakapan secara persisten dan melakukan information retrieval yang relevan dengan konteks. Konfigurasi optimal dicapai pada parameter sampling temperature 0,5, top-P 0,9, dan max token 500. Seluruh skenario black-box testing berjalan sesuai rencana. Hasil menunjukkan bahwa prototipe agen AI ini dapat dijalankan secara lokal dengan baik, menjaga privasi data dan tidak bergantung pada penyedia layanan eksternal. Rancangan ini sangat sesuai diterapkan pada organisasi dengan sumber daya terbatas, kebutuhan privasi tinggi, dan skala pengguna kecil hingga menengah.

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