ADHIWIBOWO, Whisnumurti and Widayat, Widayat and Syafei, Wahyul Amien (2026) PENGEMBANGAN FRAMEWORK DUAL-BLOCKCHAIN DALAM PENELUSURAN DAN KEBERLANJUTAN DAGING SEGAR HALAL DENGAN METODE CROW SEARCH ALGORITHM. Doctoral thesis, UNIVERSITAS DIPONEGORO.

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Abstract

Ketertelusuran dan jaminan kehalalan daging segar pada pasar tradisional masih menghadapi kendala pada aspek transparansi informasi, integritas data, validasi kehalalan, dan pencatatan kondisi distribusi, sehingga bukti digital yang tersedia belum sepenuhnya mampu memperkuat kepercayaan konsumen terhadap status halal produk. Penelitian ini bertujuan mengembangkan artefak framework dual-blockchain untuk penelusuran dan keberlanjutan daging segar halal yang mengintegrasikan blockchain transaksi untuk pencatatan aktivitas halal dan blockchain IoT untuk pencatatan suhu serta kelembaban selama distribusi. Pendekatan penelitian menggunakan Design Science Research (DSR) yang dipadukan dengan System Development Life Cycle (SDLC) melalui tahap perencanaan, desain, implementasi, dan evaluasi sistem. Mekanisme validasi halal diterapkan melalui Proof of Authority (PoA) yang menempatkan penyelia RPH dan JULEHA sebagai validator berotoritas, sedangkan Crow Search Algorithm (CSA) digunakan untuk mengolah data sensor dan menentukan nilai minimum-maksimum sebagai indikator kondisi ekstrem distribusi. Kontribusi teoretis penelitian ini terletak pada perumusan model halal traceability yang memadukan pemisahan rantai transaksi dan rantai sensor, validasi berbasis otoritas halal, serta pencatatan bukti kondisi fisik produk pada arsitektur sistem terdistribusi. Evaluasi artefak dilakukan melalui blackbox testing, uji kinerja integrasi blockchain-IoT, dan User Acceptance Test (UAT). Hasil penelitian menunjukkan bahwa seluruh modul sistem berjalan sesuai spesifikasi, sinkronisasi data sensor ke blockchain pada lingkungan implementasi terbatas mencapai latensi rata-rata 4 detik, dan tingkat penerimaan pengguna mencapai 80,7 persen dalam kategori sangat baik. Perbandingan empiris antara CSA dan Grey Wolf Optimization (GWO) pada data suhu dan kelembaban yang sama menunjukkan bahwa CSA menghasilkan rentang solusi yang lebih sempit dan lebih konsisten, sehingga lebih representatif untuk evaluasi mutu distribusi berbasis data lapangan. Temuan ini menunjukkan bahwa artefak yang dikembangkan layak secara fungsional, responsif secara operasional, dan relevan untuk memperkuat transparansi, auditabilitas, serta penelusuran digital daging segar halal pada konteks pasar tradisional

Traceability and halal assurance of fresh meat in traditional markets continue to face challenges in terms of information transparency, data integrity, halal validation, and the recording of distribution conditions, such that the available digital evidence has not fully strengthened consumer trust in the halal status of products. This study aims to develop a dual-blockchain framework artifact for the traceability and sustainability of halal fresh meat by integrating a transaction blockchain for recording halal-related activities and an IoT blockchain for recording temperature and humidity during distribution. The research adopts a Design Science Research (DSR) approach integrated with the System Development Life Cycle (SDLC) through the stages of planning, design, implementation, and system evaluation. Halal validation is implemented through Proof of Authority (PoA), which assigns slaughterhouse supervisors and JULEHA as authorized validators, while the Crow Search Algorithm (CSA) is employed to process sensor data and determine minimum and maximum values as indicators of extreme distribution conditions. The theoretical contribution of this study lies in formulating a halal traceability model that combines the separation of transaction and sensor chains, authority-based halal validation, and the recording of physical product condition evidence within a distributed system architecture. Artifact evaluation was conducted through black-box testing, blockchain–IoT integration performance testing, and User Acceptance Testing (UAT). The results indicate that all system modules operated according to specification, sensor-to-blockchain synchronization in a limited implementation environment achieved an average latency of 4 seconds, and user acceptance reached 80.7 percent, which falls within the very good category. An empirical comparison between CSA and Grey Wolf Optimization (GWO) using the same temperature and humidity dataset shows that CSA produces a narrower and more consistent solution range, making it more representative for evaluating distribution quality based on field data. These findings indicate that the developed artifact is functionally feasible, operationally responsive, and relevant for strengthening transparency, auditability, and digital traceability of halal fresh meat in the context of traditional markets.

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