Skinophile: The Art Of Skincare Selection With Haar Wavelet
Abstract
In this study, a mobile application has been developed with the primary objective of classifying facial skin types to
facilitate the selection of appropriate skincare products tailored to individual skin needs. The motivation behind this
research stems from the widespread issue of individuals being unaware of their specific skin types, which often leads
to suboptimal skincare routines and, in some cases, adverse effects such as skin dullness and damage. To address
this challenge, a comprehensive problem-solving approach has been adopted. The methodology encompasses the
utilization of the Haar Wavelets method for facial image feature extraction, complemented by the application of the
Support Vector Machine (SVM) algorithm for precise skin type classification. Face Recognition technology has also
been integrated to enhance the accuracy and reliability of the classification process.In terms of system development,
an Agile methodology has been employed, facilitating swift and cost-effective project completion. This agile
approach ensures the development process is efficient, reducing both time and financial resources.The mobile
application developed for this purpose utilizes the Python programming language, specifically incorporating the
PyWavelets library. The culmination of this research effort is a user-friendly mobile application that enables users to
capture their facial images. Subsequently, the application employs advanced algorithms to identify their specific skin
type, providing personalized recommendations for suitable skincare products and routines. This innovative solution
aims to empower individuals with the knowledge and tools necessary to enhance the effectiveness of their skincare
regimen, ultimately promoting healthier and more radiant skin.
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References
N. U. Ramadhani, B. M. Wibawa, and J. Gunawan, “Analisis Sikap Konsumen Perempuan terhadap Produk
Green Skincare: Pendekatan Multiatribut Fishbein,” J. Sains dan Seni ITS, vol. 8, no. 1, 2019. d
D.Sukristiani,“Pengetahuan Tentang Kosmetika Perawatan Kulit,”E-Journal Home Econ.Tour,vol.7,no.3,
K. G. Gaghana and R. Sutomo, “Prototype Development of Mobile-Based Commodity Exchange Information
Application for Indonesian Companies,” G-Tech J. Teknol. Terap., vol. 7, no. 3, pp. 1037–1050, Jul. 2023.
Indriyani and I. Made Sudarma, “Classification of facial skin type using discrete wavelet transform, contrast,
local binary pattern and support vector machine,”J.Theor. Appl. Inf. Technol., vol. 98, no.5, pp. 768–779, 2020.
W. Van Casteren, “The Waterfall Model And The Agile Methodologies : A Comparison By Project
Characteristics-Short The Waterfall Model and Agile Methodologies,” Acad. Competences Bachelor, no.
February, pp. 10–13, 2017. Harahap, Arman ,2018, Macrozoobenthos diversity as bioindicator of water quality
in the Bilah river, Rantauprapat, Medan. J. Phys.: Conf. Ser. 1116 052026.
A.Harahap,P.Hrp,N.K.A.R.Dewi,Macrozoobenthos diversity as anbioindicator of the water quality in the River
Kualuh Labuhanbatu Utara, International Journal of Scientific & Technology Research, 9(4),2020,pp.179-183.
Harahap,et,all,Macrozoobenthos diversity as anbioindicator of the water quality in the Sungai Kualuh
Labuhanbatu Utara, AACL Bioflux, 2022, Vol 15, Issue 6.
Harahap, Arman. 2020. Species Composition & Ecology Index Of The Family Gobiidae At The Mangrove
Belawan Of Sicanang Island International Journal of Scientific & Technology Research Volume 9, Issue 04,
April 2020.
Harahap, A., et all ( 2021), Monitoring Of Macroinvertebrates Along Streams Of Bilah River International
Journal of Conservation Sciencethis link is disabled, 12(1), pp. 247–258.
Mamangkey, J., Suryanto, D., et all (2021). Isolation and enzyme bioprospection of bacteria associated to
Bruguiera cylindrica, a mangrove plant of North Sumatra, Indonesia, Biotechnology Reports, 2021, 30, e00617.
L. A. Sunjoyo, R. G. Santosa, and K. A. Nugraha, “Implementasi Transformasi Haar Wavelet untuk Deteksi
Citra Jeruk Nipis yang Busuk,” J. Inform., vol. 12, no. 2, 2016, doi: 10.21460/inf.2016.122.498.
J. Alcaraz, M. Labbé, and M. Landete, “Support Vector Machine with feature selection: A multiobjective
approach,” Expert Syst. Appl., vol. 204, 2022, doi: 10.1016/j.eswa.2022.117485.
M. R. Farhan, A. W. Widodo, and M. A. Rahman, “Ekstraksi Ciri Pada Klasifikasi Tipe Kulit Wajah
Menggunakan Metode Haar Wavelet,” J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 3, no. 3, 2019.
C. Destitus, W. Wella, and S. Suryasari, “Support Vector Machine VS Information Gain: Analisis Sentimen
Cyberbullying di Twitter Indonesia,” Ultim. InfoSys J. Ilmu Sist. Inf., vol. 11, no. 2, pp. 107–111, 2020.
V. H. P. Noya, F. Y. Rumlawang, and Y. A. Lesnussa, “Aplikasi Transformasi Fourier untuk Menentukan
Periode Curah Hujan (Studi Kasus: Periode Curah Hujan di Kabupaten Seram Bagian Barat, Provinsi Maluku),”
J. Mat. Integr., vol. 10, no. 2, p. 85, 2014, doi: 10.24198/jmi.v10i2.10251
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