PERANCANGAN SISTEM UJI SENSORIS MAKANAN DENGAN PENGUJIAN PEFERENCE TEST (HEDONIK DAN MUTU HEDONIK), STUDI KASUS ROTI TAWAR, MENGGUNAKAN ALGORITMA RADIAL BASIS FUNCTION NETWORK

Produsen roti tawar dituntut untuk menghasilkan prouk yang berkualitas dan di sukai oleh konsumen. Peningkatan kualitas roti tawar tentunya akan berdampak pada penjualan yang akan dihasilkan. Salah satu upaya dalam peningkatan mut uroti tawar yaitu dengan cara melakukan uji Hedonik dan uji Mutu Hedonik. Penelitian ini bertujuan untuk mengembangkan sistem yang mampu memberikan penilaian terhadap produk baru yang akan dilepas di pasaran. Mutu hedonik digunakan sebagai variabel untuk menilai produk roti dengan 4 buah varibel, yang meliputi aroma, rasa, penampakan, dan teksture. Sedangkan uji hedonik menggunakan enam buah class yaitu amat sangat suka, sangat suka, suka, agak  suka, dan tidak suka, selanjutnya hasil ini akan digunakan sebagai kelas dari Knowledge Based (KB). Penelitian ini menggunakan algoritma Radial Basis Function Network (RBFN), menghasilkan tingkat akurasi 98,8% dengan teknik pengujian 10 fold. Tujuan akhir dari pengembangan sistem ini akan tercipta suatu sistem yang mampu memberikan penilaian terhadap suatu produk roti apakah akan di terima oleh pasar atau tidak, sehingga akan bermanfaat bagi industri roti untuk melakukan pengujian produk terhadap selera pasar

Studi Komparasi Data Uji Sensoris Makanan dengan Preference Test (Hedonik dan Mutu Hedonik), antara Algoritma Naïve Bayes Classifier dan Radial Basis Function Network

Bread is a food source of carbohydrates that is often consumed by the community. Various types of bread was to meet the consumer's curiosity, one of which is fresh bread. Manufacturers must be able to produce quality fresh bread and liked by consumers. Increasing the quality of bread will certainly have an impact on sales to be generated. One of the efforts in improving the quality of fresh uroti is by doing Hedonic test and Hedonic Quality test. This study aims to test the level of accuracy of candidate algorithms. The results of the research test shown that Naïve Bayes Classifier proved to be able to provide a high value of 95.6% but with a short time of execution, in testing to complete the 250 data it takes only 0.00 seconds, the time required under that number. By using the Naïve Bayes Calssifier algorithm the system is expected to provide an assessment of a bread product not to be accepted by the market or not, so it will be beneficial for the bakery industry to conduct product testing of the market tastes. Keywords— Preference Test, Hedonic, Naïve Bayes Classifier, Radial Basisi Function NetworkÂ

Emergent quality issues in the supply of Chinese medicinal plants: A mixed methods investigation of their contemporary occurrence and historical persistence

Quality issues that emerged centuries ago in Chinese medicinal plants (CMP) were investigated to explore why they still persist in an era of advanced analytical testing and extensive legislation so that a solution to improve CMP quality could be proposed. This is important for 85% of the world’s population who rely on medicinal plants (MP) for primary healthcare considering the adverse events, including fatalities that arise from such quality issues. CMP are the most prevalent medicinal plants globally. This investigation used mixed-methods, including 15 interviews with CMP expert key informants (KI), together with thematic analysis that identified the main CMP quality issues, why they persisted, and informed solutions. An unexplained case example, Eleutherococcus nodiflorus (EN), was analysed by collection of 106 samples of EN, its known toxic adulterant Periploca sepium (PS), and a related substitute, Eleutherococcus senticosus (ES), across mainland China, Taiwan and the UK. Authenticity of the samples was determined using High-performance thinlayer chromatography. Misidentification, adulteration, substitution and toxicity were the main CMP quality issues identified. Adulteration was found widespread globally with 57.4% EN found authentic, and 24.6% adulterated with cardiotoxic PS, mostly at markets and traditional pharmacies. The EN study further highlighted that the reason CMP quality issues persisted was due to the laboratory-bound nature of analytical methods and testing currently used that leave gaps in detection throughout much of the supply chain. CMP quality could be more effectively tested with patented analytical technology (PAT) and simpler field-based testing including indicator strip tests. Education highlighting the long-term economic value and communal benefit of delivering better quality CMP to consumers was recommended in favour of the financial motivation for actions that lead to the persistence of well-known and recurrent CMP quality issues