Deteksi Dini Penelusuran Titik Kritis Halal Bahan Pangan Nabati

Kamilia, Meila (2022) Deteksi Dini Penelusuran Titik Kritis Halal Bahan Pangan Nabati. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Kebutuhan dalam mengonsumsi makanan halal di Indonesia sangat besar, mengingat sebagian besar penduduk Indonesia beragama Islam. Dalam membedakan makanan halal atau non-halal, LPPOM MUI mengeluarkan Sertifikat Halal untuk makanan yang terbukti halal.
Penilaian dari sertifikat halal salah satunya yaitu memastikan bahwa semua bahan yang digunakan termasuk bahan yang halal dan boleh digunakan. Pada tahap ini UMKM seringkali menemui masalah dikarenakan kurangnya pengetahuan mengenai bahan yang halal, bahan kritis, ataupun bahan yang tidak boleh digunakan.
Penelitian ini mengajukan solusi untuk mendeteksi lebih awal kehalalan suatu bahan nabati dalam membantu UMKM untuk melakukan penilaian mandiri terhadap produk yang akan disertifikasi. Prediksi dilakukan berdasarkan aktivitas penelusuran yang dilakukan UMKM.
Deteksi dilakukan menggunakan model klasifikasi dengan algoritma support vector machine (SVM) dan pemodelan proses bisnis menggunakan perangkat lunak business process management (BPM) ProcessMaker.
Hasil penelitian menunjukkan bahwa model memiliki akurasi tertinggi 95% dan model ini kemudian diujicobakan pada data penelusuran baru dari lima produk nabati yang berbeda.Hasil uji coba menunjukkan bahwa model berhasil memprediksi tiga dari lima skenario uji coba dengan tepat.
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The need to consume halal food is very large in Indonesia, considering most Indonesian people are Muslim. To differentiate between halal and non-halal food, LPPOM MUI provides Halal Certification for foods that have proven to be halal.
One of the halal certificate assessments is ensuring that all materials used are halal and may be used. At this stage, UMKM often encounter problems due to a lack of knowledge about halal ingredients, critical ingredients, or ingredients that should not be used.
This study proposes a solution to early detection of the halalness of plant-based ingredients in helping UMKM conduct a self-assessment of the product to be certified. Predictions are made based on activities tracing carried out by UMKM.
The detection process is implemented using a classification model with a support vector machine (SVM) algorithm and business process modeling using ProcessMaker business process management (BPM) software.
The results showed that the model had highest accuracy value 95% and this model was then tested on new tracking data from five different plant-based ingredients. The test results show that the model successfully predicts three of the five test scenarios correctly.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	deteksi dini, halal, nabati, processmaker, support vector machine, titik kritis, critical point, early-detection, halal, plant-based, processmaker, support vector machine,
Subjects:	Q Science > Q Science (General) > Q325.5 Machine learning. Support vector machines. T Technology > T Technology (General) > T58.6 Management information systems
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Informatics Engineering > 55201-(S1) Undergraduate Thesis
Depositing User:	Meila Kamilia
Date Deposited:	10 Feb 2022 06:00
Last Modified:	10 Feb 2022 06:00
URI:	http://repository.its.ac.id/id/eprint/93406

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