This paper presents the spectroscopic dataset, pre-processing, calibration, and predicted model database of Fourier transform infrared (FTIR) spectroscopy used to detect adulterated coconut milk with water. Absorbance spectral data were acquired and recorded in wavelength range from 2500 to 4000 nm for a total of 43 coconut milk samples. Coconut milk ware prepared in three forms of adulteration. Coconut milk comes from traditional markets and instant coconut milk in Indonesia. Spectra data may also be pre-processed to increase prediction accuracy, robustness performance using normalize, multiplicative scatter correction (MSC), standard normal variate (SNV), 1st derivative, 2nd derivative, and combination of 1st derivative and MSC. Calibration models and cross-validation to forecast those adulteration parameters use two regression algorithms, i.e., principal component regression (PCR) and partial least square regression (PLSR). By looking at its statistical metrics, prediction efficiency can be measured and justified (correlation coefficient (r), correlation of determination (R 2 ), and root mean square error (RMSE)). Obtained FTIR datasets and models can be used as a non-invasive method to predict and determine adulteration on coconut milk.
Jurnal Keteknikan Pertanian (JTEP) terakreditasi berdasarkan SK Dirjen Penguatan Riset dan Pengembangan Kementerian Ristek Dikti Nomor I/E/KPT/2015 tanggal 21 September 2015. Selain itu, JTEP juga telah terdaftar pada Crossref dan telah memiliki Digital Object Identifier (DOI) dan telah terindeks pada ISJD, IPI, Google Scholar dan DOAJ. JTEP terbit tiga kali setahun yaitu bulan April, Agustus dan Desember, dan mulai tahun ini berisi 15 naskah untuk setiap nomornya. Peningkatan jumlah naskah pada setiap nomornya ini dimaksudkan untuk mengurangi masa tunggu dengan tidak menurunkan kualitas naskah yang dipublikasikan. Jurnal berkala ilmiah ini berkiprah dalam pengembangan ilmu keteknikan untuk pertanian tropika dan lingkungan hayati. Jurnal ini diterbitkan dua kali setahun baik dalam edisi cetak maupun edisi online. Penulis makalah tidak dibatasi pada anggota PERTETA tetapi terbuka bagi masyarakat umum. Lingkup makalah, antara lain meliputi teknik sumberdaya lahan dan air, alat dan mesin budidaya pertanian, lingkungan dan bangunan pertanian, energi alternatif dan elektrifikasi, ergonomika dan elektronika pertanian, teknik pengolahan pangan dan hasil pertanian, manajemen dan sistem informasi pertanian. Makalah dikelompokkan dalam invited paper yang menyajikan isu aktual nasional dan internasional, review perkembangan penelitian, atau penerapan ilmu dan teknologi, technical paper hasil penelitian, penerapan, atau diseminasi, serta research methodology berkaitan pengembangan modul, metode, prosedur, program aplikasi, dan lain sebagainya. Penulisan naskah harus mengikuti panduan penulisan seperti tercantum pada website dan naskah dikirim secara elektronik (online submission) melalui
<span lang="EN-US">Since the COVID-19 pandemic, automated liquid dispensers have been increasingly developed to assist transmission prevention. However, data availability of automatic liquid dispenser mechanism's technical characteristics is not yet widely available. This causes frequent over or under design in its development. Therefore, we specifically measure push and pull forces engineering characteristics generated by the automatic liquid dispenser mechanism. A wire mechanism-based automatic liquid dispenser apparatus was used to experiment. A load-cell sensor was used to detect the force that occurs from a servo motor controlled by a microcontroller. The force data (push and pull) will be sent directly to the database server cloud with a recording </span><span lang="EN-US">frequency of every second. Three types of fluid treatment levels are used i.e. water, liquid soap, and hand sanitizer gel. Three types of fluid volume treatment levels used were 50 ml, 150 ml, and 250 ml. Each treatment level combination is carried out at the servo motors rotation steps 180</span><span lang="EN-US">°</span><span lang="EN-US">, 150</span><span lang="EN-US">°</span><span lang="EN-US">, 120</span><span lang="EN-US">°</span><span lang="EN-US">, 90</span><span lang="EN-US">°</span><span lang="EN-US">, 60</span><span lang="EN-US">°</span><span lang="EN-US">, and 30</span><span lang="EN-US">°</span><span lang="EN-US">. The results show that no significant differences were found in maximal forces required to release the water, liquid soap, and hand-sanitizer gel. It is also known that the volume of the fluid has a very significant effect on the amount of push and pull forces generated.</span>
Dataset mechanical properties of an automated liquid dispenser are essential to study for proper design. Therefore, this article includes a push and pull force dataset collected via a load cell sensor on an automatic liquid dispenser self-developed. During one test, nineteen push and pull data were acquired. Measured data is transmitted and saved using internet networks on data cloud servers. The dataset is composed of three types of fluid (i.e., water, soap, and hand sanitizer), three levels of fluid volume (i.e., 50, 150, and 250 ml), and six levels of servo motor rotation angle (i.e., 30°, 60°, 90°, 120°, 150°, 180°). The raw dataset consists of 60 treatments from the 1857 test. This data also provides push and pull force testing of an empty automatic liquid dispenser. The raw data files have been provided. For researchers involved in designing automated liquid dispensers, the dataset may be used to be more reliable in its development. It is possible to prevent over and under design in deciding the energy consumption of an automated liquid dispenser by researching this push and pull force data more deeply. The dataset will be shown as Excel files.
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