Sistem Pakar Pengenalan Ekspresi Wajah Manusia Menggunakan Metode Kohonen Self Organizing Dan Principal Componen Analysis

Hardiansyah, Bagus; Primandari, Puteri Noraisya

doi:10.31284/j.integer.2018.v3i2.310

Cited by 4 publications

(4 citation statements)

References 1 publication

(1 reference statement)

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“…Hal ini dikarenakan MARS memanifestasikan teknologi kecerdasan buatan yakni Kohonen Self Organizing Maps. Metode ini dapat menganalisa gestur wajah dengan memetakan ruang masukan dengan jaringan syaraf (Hardiansyah dan Primandari, 2018). MARS dapat mengoptimalisasikan sesi profiling dan meminimalisasi potensi human error hasil analisis petugas terhadap calon PMI.…”

Section: Mars (Smart Profiling System)unclassified

Integrasi Smart Profiling System (Mars) Berbasis Artificial Intelligence Dengan Smart Camera Imigrasi Dalam Rangka Pencegahan Pekerja Migran Indonesia (Pmi) Nonprosedural

Hilmy,

Karunia,

Hidayat

2023

tematics

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Permasalahan Pekerja Migran Indonesia (PMI) di luar negeri masih tidak dapat diselesaikan dengan maksimal. Hal ini disebabkan masih banyak ditemukan PMI yang tidak melalui prosedur yang telah ditentukan. Permasalahan tersebut memerlukan solusi berupa inovasi untuk meningkatkan sistem pencegahan dan pengawasan PMI nonprosedural. Penelitian ini menggunakan Penelitian ini menggunakan metode kualitatif melalui studi pustaka untuk mengumpulkan data dan informasi yang relevan antara teori dan konsep, kemudian dianalisis dan dikorelasi dengan mendeskripsikan gambaran, rancangan teknologi dan mekanisme kerja Smart Profilling System (MARS).Hasil dari penelitian ini menunjukan bahwa Integrasi Smart Profiling System (Mars) berbasis Artificial Intelligence dengan Smart Camera Imigrasi dapat menjadi solusi visioner guna pencegahan PMI nonprosedural.Integrasi sistem MARS perlu mendapat dukungan dari berbagai stakeholder agar pelaksanaannya dapat berjalan maksimal

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Section: Mars (Smart Profiling System)unclassified

Integrasi Smart Profiling System (Mars) Berbasis Artificial Intelligence Dengan Smart Camera Imigrasi Dalam Rangka Pencegahan Pekerja Migran Indonesia (Pmi) Nonprosedural

Hilmy,

Karunia,

Hidayat

2023

tematics

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“…Dalam jaringan self organizing map, neuron target tidak diletakkan dalam sebuah baris seperti layaknya model JST yang lain. Neuron target diletakkan dalam dua dimensi yang bentuk/topologinya dapat diatur [12], [13]. Topologi yang berbeda akan menghasilkan neuron sekitar neuron pemenang yang berbeda sehingga bobot yang dihasilkan juga berbeda.…”

Section: Kohonen Self Oganizing Mapunclassified

Implementasi Jaringan Saraf Tiruan Pengenalan Pola Aksara Batak Simalungun Menggunakan Kohonen Self Organizing Map

Tarigan¹,

Hayadi²,

Nasyuha³

2022

JoSYC

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The Simalungun Batak script contained in the Batak Letter consists of several variants of forms depending on the language and region, in general there are five variants of the Batak Letter in Sumatra, namely Karo, Toba, Pakpak, Simalungun, Angkola Mandailing. This script is not widely known by the datu, namely people who are respected by the Batak community for mastering magic, fortune-telling, and calendaring so that errors still often occur in the introduction of this script, even though this script can be found in various libraries, namely the traditional books of the Batak community. By utilizing Artificial Neural Networks and using the Kohonen Self Organizing Map method which can be implemented in the Simalungun Batak Letter Recognition Application so that it can make it easier for the public to recognize the Simalungun Batak script. The results of the study that applied an artificial neural network with the kohonen self-organizing map algorithm made the recognition of the Simalungun Batak letter pattern easy for the public to recognize and could also preserve one of the cultures, namely the Simalungun Batak script and make it easier for users to implement it into the android-based application.

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“…The application of the Kohonen Self Organizing Map (K-SOM) network has been successfully implemented as an expert system to recognize human facial expressions. The application provides accuracy by about 80.00% obtained from testing of 30 facial expressions with 90x60 resolution [6]. In addition to using the backpropagation method and K-SOM for intelligent systems, the perceptron has also been successfully developed for the expert system for diagnosing goat diseases.…”

Section: A Literature Reviewmentioning

confidence: 99%

Expert System of Diagnosing Building Damage due to Earthquake using Backpropagation Artificial Neural Network Method

2020

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Earthquake is one of the most destructive natural disasters. After the earthquake, experts were deployed to survey the damage that occurred. One of the main objectives of the assessment task carried out by experts is to evaluate and classify buildings into several categories based on the level of damage that occurs. In this study, an expert system that could facilitate the assessment of building damage due to the earthquake was made using Backpropagation neural network method. The testing techniques used in this system are blackbox, accuracy and Mean Opinion Score (MOS) testing. MOS testing conducted by 30 respondents produced an MOS value of 4.54 from a scale of 5. While the average accuracy of the system obtained is 82.22% of the 30 case cases tested by 3 building damage experts.

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Sistem Pakar Pengenalan Ekspresi Wajah Manusia Menggunakan Metode Kohonen Self Organizing Dan Principal Componen Analysis

Cited by 4 publications

References 1 publication

Integrasi Smart Profiling System (Mars) Berbasis Artificial Intelligence Dengan Smart Camera Imigrasi Dalam Rangka Pencegahan Pekerja Migran Indonesia (Pmi) Nonprosedural

Integrasi Smart Profiling System (Mars) Berbasis Artificial Intelligence Dengan Smart Camera Imigrasi Dalam Rangka Pencegahan Pekerja Migran Indonesia (Pmi) Nonprosedural

Implementasi Jaringan Saraf Tiruan Pengenalan Pola Aksara Batak Simalungun Menggunakan Kohonen Self Organizing Map

Expert System of Diagnosing Building Damage due to Earthquake using Backpropagation Artificial Neural Network Method

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