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Hafiz Irsyad
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Algoritme Jurnal Mahasiswa Teknik Informatika
Published by Universitas Multi Data Palembang
ISSN : -     EISSN : 27758796     DOI : https://doi.org/10.35957/algoritme.v2i2
Core Subject : Science,
Computer Science & IT
Jurnal Algoritme menjadi sarana publikasi artikel hasil temuan Penelitian orisinal atau artikel analisis. Bahasa yang digunakan jurnal adalah bahasa Inggris atau bahasa Indonesia. Ruang lingkup tulisan harus relevan dengan disiplin ilmu seperti: - Machine Learning - Computer Vision, - Artificial Inteledence, - Internet Of Things, - Natural Language Processing, - Image Processing, - Cyber Security, - Data Mining, - Game Development, - Digital Forensic, - Pattern Recognization, - Virtual & AUmented Reality,. - Cloud Computing, - Game Development, - Mobile Application, dan - Topik kajian lainnya yang relevan dengan ilmu teknik informatika.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 6 Documents
 1 
Search results for , issue "Vol 3 No 2 (2023): Jurnal Algoritme" : 6 Documents clear
Identifikasi Penyakit Pada Tanaman Kopi Berdasarkan Citra Daun Menggunakan Metode Convolution Neural Network Ahmad Fatchurrachman; Daniel Udjulawa
Jurnal Algoritme Vol 3 No 2 (2023): Jurnal Algoritme
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v3i2.3384

Abstract

Coffee plants are usually made for drinks made from coffee beans that have been ground into powder. One of the causes of decreased coffee quality is caused by pests that can attack from the leaves, stems and roots. This study aims to identify coffee plant diseases based on leaves using the Convolution Neural Network (CNN) method with the ResNet-50 architecture with the Adam optimizer. The total data from the dataset is 1664 images, in the dataset there are 1264 train data images and 400 test images. The highest result in training in this study using 60 epochs and Adam's optimizer with a probability value of learning_rate of 0.0001 getting a probability value of 0.9969 and the lowest value getting a probability value of 0.4918. The results of testing the test data in this study obtained an accuracy rate of 99%.
Klasifikasi Ras Anjing Berdasarkan Citra Menggunakan Convolutional Neural Network Axel Leovincent; Yoannita Yoannita
Jurnal Algoritme Vol 3 No 2 (2023): Jurnal Algoritme
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v3i2.3389

Abstract

Dogs are mammals that are much loved and kept. Dogs have 355 breeds worldwide. Each race has its own differences, but in certain races have little or almost similar differences. This study classifies 120 dog breeds using the Convolutional Neural Network (CNN) with the ResNet-50 architectural model and the Adam optimizer. The dataset used consists of 20580 images. The dataset is divided into training data, validation data, and test data with a ratio of 60:20:20. The resolution image is 224x224 pixels in size. In this study, it yielded an accuracy of 99,35%.
Deteksi Masker Melalui Video CCTV Menggunakan You Only Look Once Dean Darmawan; Daniel Udjulawa; Novan Wijaya
Jurnal Algoritme Vol 3 No 2 (2023): Jurnal Algoritme
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v3i2.3598

Abstract

The coronavirus pandemic or known as the COVID-19 pandemic is a global pandemic of corona virus that are caused by severe acute respiratory syndrome coronavirus 2 that are started in Wuhan, China in 2019. In 30th January 2020 World Health Organization (WHO) declared an emergency situation towards COVID-19 and in 11th March 2020, WHO officially declared an ongoing global pandemic of COVID-19. COVID-19 cases in the world itself is already reaching 181 million of cases with around 3.92 million deaths. Indonesia itself is one of the country that are affected by COVID-19 spread with 2.09 million cases and 56,729 deaths. In order to decrease the amount of COVID-19 cases, WHO require each individuals to do social distancing, stay hygiene, and always wearing face mask to prevent even more spread of the virus. A method to do face mask detection is proposed using a object detection method, You Only Look Once (YOLO). The test results obtained by calculating f-measure with the highest accuracy of 0.59 and the lowest of 0.19 using CCTV video that are taken with 70 cm distance. In the second test using video that are recorded with more than 90 cm the program obtained it’s result of 0.
Prediksi Pertumbuhan Penduduk Kecamatan Cimaragas Kabupaten Ciamis Dengan Metode Artificial Neural RAFLI KURNIA ARMANDA
Jurnal Algoritme Vol 3 No 2 (2023): Jurnal Algoritme
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v3i2.3709

Abstract

This research was conducted to study an Artificial Neural Network, which is one of the command languages used in the Matlab program which is used to predict input data and can be used to predict population growth. Artificial Neural Network is a powerful data model that is able to capture and represent complex Input-Output relationships, because of its ability to solve some problems relatively easy to use, resilience to input speed data for execution, and initialize complex systems. By using Artificial Neural Networks (Artificial Neural Network) is expected to provide another alternative in estimating and predicting population growth rates in Cimaragas District, Ciamis Regency.
Penentuan Tingkat Kerontokan Rambut Kepala Pria dengan Metode Fuzzy Inference System Sugeno Eric Karuna; Johannes Petrus
Jurnal Algoritme Vol 3 No 2 (2023): Jurnal Algoritme
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v3i2.4204

Abstract

Abstrak Rambut kepala merupakan organ tubuh dari manusia yang memiliki bentuk seperti helaian benang yang tumbuh di kulit dengan mengandung banyak keratin serta dapat muncul dari lapisan epidermis. Terdapat berbagai faktor yang dapat mengakibatkan perubahan kondisi kulit kepala dan rambut seperti faktor usia lanjut, depresi, berkurangnya aktifitas kelenjar minyak dikulit kepala, gangguan pembuluh darah, gangguan hormon, pengaruh kosmetika, paparan sinar matahari secara terus menerus dan kurangnya makanan yang bergizi untuk kepentingan pertumbuhan rambut. Penelitian ini melakukan perancangan model Fuzzy Sugeno untuk menentukan tingkat kerontokan rambut kepala pada pria berdasarkan faktor-faktor penyebabnya. Salah satu tujuan dalam penelitian ini adalah untuk mengetahui tingkat kerontokan rambut kepala pada pria menggunakan metode Sugeno. Pada model Fuzzy Sugeno mendapatkan hasil yang rendah dalam menentukan tingkat kerontokan rambut kepala pada pria, yaitu memperoleh nilai error sebesar 114,870 untuk nilai MSE dan 5,73% untuk nilai MAPE.
Identifikasi Kadar Ikan Pada Pempek Menggunakan Fitur GLCM dan SVM Muhammad Afif Naufal; Gasim Gasim
Jurnal Algoritme Vol 3 No 2 (2023): Jurnal Algoritme
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v3i2.4791

Abstract

Pempek merupakan makanan khas kota Palembang, Sumatera Selatan. Pempek dibuat dari olahan daging ikan giling yang sebelumnya telah dikuliti dan dipisahkan dari duri halus. Perbandingan pada pempek tersebut selain dapat diketahui oleh orang awam melalui rasa dapat juga diketahui melalui media elektronik yakni melalui kecerdasan buatan. Penelitian ini dilakukan untuk mengetahui perbandingan kadar ikan pada pempek dengan empat jenis kadar perbandingan yakni kadar 1 terdiri dari 1 ikan gabus 1 tepung (1:1), kadar 2 terdiri dari 1.5 ikan gabus 1 tepung (1.5:1), kadar 3 terdiri dari 2 ikan gabus 1 tepung (2:1), dan kadar 4 terdiri dari 1 ikan gabus 2 tepung (1:2). Metode pengenalan yang digunakan Support Vector Machine dengan ekstraksi fitur GLCM dengan dua jenis parameter yang berbeda yakni menggunakan GLCM dengan 4 parameter yang terdiri dari nilai Contras, Homogeneity, Correlation, dan Energy. Dan GLCM dengan 2 parameter yang terdiri dari nilai Homogeneity dan Correlation. Klasifikasi menggunakan metode SVM dengan ekstraksi GLCM dua parameter berbeda pada penelitian ini mendapatkan nilai akurasi sebesar 25.83% pada ekstraksi GLCM empat parameter, sedangkan hasil dari SVM dengan ekstraksi GLCM dua parameter hanya 25%.

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