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Alat Pendeteksi Formalin Menggunakan Deret Sensor HCHO dan MQ-7 dengan Logika Fuzzy Cyntiya Laxmi Haura; Indri Yanti; Muh Pauzan
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 2: Mei 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i2.7097

Abstract

Formalin is a hazardous chemical substance that has a pungent odor, is colorless or clear, and is flammable. It should be used to preserve corpses, but often misused by unscrupulous traders to preserve food. Formalin has harmful effects on the human body if it is ingested. Therefore, a practical tool that can detect the presence of formaldehyde in food is needed. Making a formalin detection tool using the Mamdani fuzzy inference system is very useful for detecting formalin and the level of food safety quickly and economically. This tool used the HCHO and the MQ-7 sensors combined with an expert system, namely fuzzy logic. The HCHO detects formalin in the food, like the sense of smell; meanwhile, the MQ-7 sensor detects carbon monoxide (CO). In the testing process, a heater was utilized to vaporize the food samples. The vapor was then detected by the two gas sensors and was processed using the fuzzy logic of the Mamdani method. To see the test’s accuracy using the tool, its results were compared with those of the formalin kit and the Fuzzy Logic Toolbox in MATLAB. The results showed that the lowest level of formalin in the tofu sample, namely sample H, was 0.60 ppm; meanwhile, the highest level was in sample E, with 13.64 ppm. The lowest formalin found in salted fish, namely sample P, was 7.14 ppm, while the highest formaldehyde level was in the salted fish sample, namely sample T, with 193.81 ppm. Compared with the formalin kit results, the accuracy value obtained from the total testing of twenty samples was 95%. The output of the tool was nearly identical to that of MATLAB: 85% with a difference of 0.01 and 15% with a difference of 0.02. The average error between tool output and MATLAB was 0.77%.
Evaluasi Penerapan Belajar E-larning dalam pendalaman materi pada Universitas Wiralodra Cyntiya Laxmi Haura; Tineke Fatma Putri; Taufik Hidayat
Jurnal Pengabdian Masyarakat Sultan Indonesia Vol. 1 No. 1 (2024): Abdisultan
Publisher : Sultan Publsiher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/abdisultan.v1i1.188

Abstract

The face-to-face learning system is an effective method. However, there are several weaknesses in the face-to-face method, namely limited time for evaluation and discussion, because time is wasted during face-to-face meetings by delivering several courses. The aim of this research is to develop an E-learning prototype at Wiralodra University to complete the face-to-face learning system. Stages in building an E-Learning prototype apply the stages in the prototype model. Stages in building an E-Learning prototype apply the stages in the prototype model. This has three stages, namely receiving opinions from customers, building and improving prototypes, testing and evaluation. Apart from that, data collection techniques include observation, interviews, and building and improving prototypes.