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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Patchouli and Essential Oil Products
Haditiar, Yudi
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Economics, Econometrics & Finance Engineering Medicine & Pharmacology

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Trends in Formulation of Night Cream Containing Essential Oil Isnaini, Nadia; Faradhila, Jihan; Maysarah, Hilda; Prajaputra, Vicky; Harnelly, Essy; Zulkarnain, Zulkarnain; Maryam, Siti; Muhammad, Syaifullah; Haditiar, Yudi; Desiyana, Lydia Septa; Sari, Febia
Journal of Patchouli and Essential Oil Products JOURNAL OF PACTHOULI AND ESSENTIAL OIL PRODUCT : VOLUME 2, ISSUE 2 (DECEMBER 2023) - IN PROGRESS
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jpeop.v2i2.36090

Abstract

Night creams play a pivotal role in skincare routines by safeguarding against nocturnal moisture loss and promoting a smooth, wrinkle-free complexion. However, conventional formulations of night creams often incorporate synthetic active substances, potentially leading to adverse effects over prolonged use. Addressing this concern involves substituting these synthetic compounds with natural ingredients, particularly essential oils, renowned for their diverse skincare benefits encompassing anti-acne, anti-aging, anti-wrinkle, and moisturizing properties. A systematic review was conducted to establish a foundation for future investigations, focusing on the integration of essential oils in night cream formulations. The outcomes revealed that various night cream formulations, enriched with essential oils derived from natural ingredients such as rosemary oil, camellia oil, clove oil, geranium oil, lemongrass oil, rosehip oil, and sandalwood oil, demonstrate remarkable efficacy in preserving skin moisture. The versatility of essential oils has been showcased in the development of night creams, boasting diverse beneficial effects across skincare concerns. This systematic investigation highlights the potential of essential oil-based night creams, which have recently gained traction in the global market. The burgeoning introduction of these products signifies an escalating demand for such skincare solutions and points towards promising prospects for future advancements in essential oil-based night creams.Keywords: essential oils, formulation, natural product chemistry, night cream, patchouli oil, skincare
Implemantasi Mask R-CNN pada Perhitungan Tinggi dan Lebar Karang untuk Memantau Pertumbuhan Transplantasi Karang Alkhalis, Naufal; Husaini, Husaini; Haekal Azief Haridhi; Maretna, Cut Nadilla; Nur Fadli; Haditiar, Yudi; Nanda, Muhammad; Ulfah, Maria; Kris Handoko; Intan Malayana; Arsa Cindy Safitri
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 11 No 3: Juni 2024
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.938374

Abstract

Terumbu karang merupakan ekosistem yang berperan penting di laut serta sangat rentan terhadap kerusakan. Transplantasi karang telah menjadi salah satu pendekatan yang dilakukan untuk melestarikan terumbu karang. Pasca transplantasi, pemantauan perlu dilakukan untuk melihat pertumbuhan karang. Dalam upaya pemantauan, para penyelam harus membawa alat selam, penggaris dan buku untuk mengukur dan mencatat satu-satu karang yang telah ditransplantasi. Proses tersebut menghabiskan investasi finansial, waktu dan tenaga yang besar. Pemantauan dapat dioptimalkan dengan mengimplementasikan algoritma Mask Region Convolutional Neural Network (Mask R-CNN) melalui library Detectron2 pada citra transplantasi karang. Proses implementasi akan menghasilkan model yang dapat melakukan segmentasi pada objek karang. Segmentasi tersebut dapat dikalkulasikan untuk melihat tinggi dan lebar karang sebagai indikator pertumbuhan. Implementasi model melibatkan tujuh backbone segmentasi instance dengan jadwal laju pembelajaran sebesar tiga kali. Berdasarkan hasil penelitian, model yang dihasilkan telah berhasil diimplementasikan dalam mengukur tinggi dan lebar dari karang transplantasi. Perbandingan antara hasil pengukuran menggunakan model Mask R-CNN dan pengukuran langsung menunjukkan konsistensi yang baik. Dengan demikian para penyelam hanya perlu memaksimalkan sumberdaya yang dimiliki untuk mengambil citra karang dengan jarak yang telah ditentukan sehingga dapat meringkas waktu penyelaman.   Abstract   Coral reefs are ecosystems that play an important role in the sea and are very vulnerable to damage. Coral transplantation has become one of the approaches taken to preserve coral reefs. Post-transplant, monitoring needs to be done to see coral growth. In monitoring efforts, divers must carry diving equipment, rulers and books to measure and record the only corals that have been transplanted. The process consumes a huge investment of finance, time and effort. Monitoring can be optimized by implementing the Mask Region Convolutional Neural Network (Mask R-CNN) algorithm through the Detectron2 library on coral transplant images. The implementation process will produce a model that can segment coral objects. The segmentation can be calculated to see the height and width of corals as growth indicators. The model implementation involves seven backbone segmentation instances with a learning rate schedule of three times. Based on the results of the study, the resulting model has been successfully implemented in measuring the height and width of transplanted corals. Comparison between measurement results using the Mask R-CNN model and direct measurements showed good consistency. Thus, divers only need to maximize their resources to take images of corals with a predetermined distance so as to shorten dive time.
Co-Authors Alkhalis, Naufal Arsa Cindy Safitri Essy Harnelly Faradhila, Jihan Haekal Azief Haridhi Husaini Husaini Intan Malayana Isnaini, Nadia Kris Handoko Lydia Septa Desiyana, Lydia Septa Maretna, Cut Nadilla Maria Ulfah Maysarah, Hilda Nanda, Muhammad Nur Fadli Prajaputra, Vicky Sari, Febia SITI MARYAM Syaifullah Muhammad ZULKARNAIN ZULKARNAIN