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Motion capture in humanoid model with Unity engine using Kinect V2 Amir Mahmud Husein; Jimmy Ciawi
Journal of Computer Networks, Architecture and High Performance Computing Vol. 3 No. 1 (2021): Computer Networks, Architecture and High Performance Computing, January 2021
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v3i2.1067

Abstract

Animation is a technique to create illusion of motion, which is created by displaying a series of motionless pictures in sequence or using a spine/bones to create motion that looks real. All this time, the process of creating an animation still using traditional technique which requires special skills and take some time to finish a complicated animation which is used in movies or video games. Motion capture is an animation-making technique by tracking every part of body in order to find position and rotation of human’s joints which is generated by the image from the sensor. Motion capture has lots of method, such as marker base technique which use mark to track any motions. Motion capture markerless method that can capture or track motions without using any marks. Motion capture with markerless technique can be done by using RGB-Depth’s camera censor, which is by using Microsoft Kinect V2 with Kinect V2 SDK in order to make Kinect connected with computer, and using Unity Engine, a game engine that has already provided animation timeline and supports any 3D format which contains animation file that can be used in mostly other models which is using humanoid. In order to obtain motion data which will be changed into skeleton joint data, we will use connector OpenNI and 3D Collada model with (.dae) format because Collada is 3D format Open Source which is built using XML-based so that it can easily read and written back into 3D file as an output.
Pengenalan Multi Wajah Berdasarkan Klasifikasi Kohonen SOM Dioptimalkan dengan Algoritma Discriminant Analysis PCA Amir Mahmud Husein, Mawaddah Harahap
Query: Journal of Information Systems Volume: 01, Number: 02, October 2017
Publisher : Program Studi Sistem Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (334.541 KB)

Abstract

Face recognition is a process of identification with the image has variations changeable can be recognized, needs a method of optimization to minimize computational time by not affecting the classification results. This research proposes a face recognition system are directly based on Kohonen SOM classification that optimized by the method of Discriminant Analysis based Principal Component Analysis (PCA). Evaluation of PCA’s extraction performance uses two approaches, first the LDA method to optimize PCA issues of the election of irrelevant features of the dataset and the second approach is to apply a kernel function on the LDA (KDA), the results of both approaches are applied on face image classification for Kohonen directly. The testing is two phases, the first stage is testing with a single image of a face and then multi face. Based on the results of testing one face image, both of the approached feature extraction that proposed is very accurately be applied to the classification of the Kohonen SOM with the accurate value of the second approach PCA-KDA is more accurate with 94.22% and the first approach 93.91%, however on the first approach is faster than the second approach with the accurate value of time 0.4 seconds for PCA-LDA and 0.5 seconds to PCA-KDA to one image of the face, but while testing of multi face more two images the result is not significant. Keywords: Face recognition, Feature extraction, Kohonen SOM.
Predicting the Spread of the Corona Virus (COVID-19) in Indonesia: Approach Visual Data Analysis and Prophet Forecasting Amir Mahmud Husein; Jefri Poltak Hutabarat; Jeckson Edition Sitorus; Tonazisokhi Giawa; Mawaddah Harahap
International Journal of Artificial Intelligence Research Vol 4, No 2 (2020): December 2020
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (20.961 KB) | DOI: 10.29099/ijair.v5i1.192

Abstract

The development trend of the coronavirus pandemic (COVID-19) in various countries has become a global threat, including in Southeast Asia, such as Indonesia, the Philippines, Brunei, Malaysia, and Singapore. In this paper, we propose an Exploratory Data Analysis (EDA) model approach and a time series forecasting model using the Prophet method to predict the number of confirmed cases and cases of death in Indonesia in the next thirty days. We apply the EDA model to visualize and provide an understanding of this pandemic outbreak in various countries, especially in Indonesia. We present the trends in the spread of epidemics from the countries of China from which the virus originates, then mark the top ten countries and their development and also present the trends in Asian countries. We present an analytical framework comparing the predicted results with the actual data evaluated using the MAPE and MAE models, where the prophet algorithm produces good performance based on the evaluation results, the relative error rate of our estimate (MAPE) is around 6.52%, and the model average false 52.7% (MAE) for confirmed cases, while case mortality was 1.3% for the MAPE and MAE models around 236.6%. The results of the analysis can be used as a reference for the Indonesian government in making decisions to prevent its spread in order to avoid an increase in the number of deaths
Pelatihan Dan Implementasi Sistem Informasi Penetapan Angka Kredit Guru Pada Dinas Pendidikan Kabupaten Padang Lawas Utara Siti Aisyah; Amir Mahmud Husein; Mawaddah Harahap
Jurnal Mitra Prima Vol. 2 No. 1 (2020): Jurnal Mitra Prima
Publisher : Mitra prima

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/mitra_prima.v1i1.826

Abstract

Jumlah guru PNS tingkat SD dan SMP pada Dinas Pendidikan Kabupaten Padang Lawas Utara pada tahun 2018 sebanyak 1.657. Sudah seharusnya memberikan pelayanan yang mudah dan transparan dengan memanfaatkan teknologi informasi, dalam bentuk Sistem Informasi yang terintegrasi dengan database manajemen kepegawaian BKD Kabupaten Padang Lawas Utara secara penuh. Sistem Informasi digunakan sebagai media yang dapat mempermudah pelayanan pengurusan Daftar Usul Penetapan Angka Kredit (DUPAK) bagi guru secara online kepada Tim Operator dan Tim Penilai. Adapun tahapan yang dilakukan adalah : persiapan dengan tim, pembuatan aplikasi, Observasi dan evaluasi, dan refleksi. Aplikasi memudahkan pihak guru untuk mengusulkan PAK dan DUPAK tanpa harus datang langsung ke lokasi Mitra, sehingga memberikan efesiensi waktu dan biaya. Dapat mempermudah Tim Penilai untuk melakukan tugasnya tanpa terbatas tempat dan waktu.
Peningkatan Pelayanan Disiplin Aparatur Negara di Lingkungan Badan Kepegawaian Daerah Kabupaten Padang Lawas Utara dengan Teknologi Informasi Amir Mahmud Husein; Yennimar; Delima sitanggang; yonata laia
Jurnal Mitra Prima Vol. 1 No. 2 (2019): Jurnal Mitra Prima
Publisher : Mitra prima

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Masalah kedisiplinan pegawai menjadi faktor penting yang sangat mempengaruhi terhadap keberhasilan organisasi pemerintah. Seorang PNS (pegawai negri sipil) tidak akan bisa bertanggung jawab atas pekerjaannya apabila kurang disiplin terhadap aturan– aturan yang berlaku. Untuk membantu pemerintah khususnya di lingkungan pemerintah Kabupaten Padang Lawas Utara menjalankan regulasi Peraturan Pemerintah Nomor 53 Tahun 2010 Tentang Peraturan Disiplin Pegawai Negeri Sipil, Fakultas Teknologi dan Ilmu Komputer (FTIK) UNPRI terpanggil untuk turut menanggulangi masalah disiplin PNS tersebut yang terfokus pada penerapan teknologi informasi dengan membangun sistem informasi absensi digital (SIABDI) melalui pengabdian kepada masyarakat. Kegiatan ini melibatkan PNS perwakilan dari tiap-tiap Satuan Kinerja Perangkat Daerah (SKPD) Pemerintah Kabupaten Padang Lawas Utara untuk diberikan sosialisasi dan pelatihan penggunaan sistem, selain itu Tim PKM juga membantu membangun jaringan LAN di setiap SKPD. Kegiatan ini dilaksanakan di BKD Kabupaten Padang Lawas Utara selama 8 bulan kemudian dilakukan evaluasi terhadap penerapan sistem sesuai kebijakan yang berlaku. Dari hasil evaluasi setelah pelaksanaan kegiatan, target akhir kegiatan ini telah memberikan kemudahakn bagi BKD melakukan pengawasan dan penerapan hukuman disiplin, selain itu pimpinan daerah dapat menggunakan sistem ini untuk memonitoring kedisiplinan PNS melalui device mobile. Dalam kegiatan pelaksanaan pengabdian masyarakat ini, mengikuti aktivitas pelaksanaan penelitian tindakan yang terdiri dari persiapan, pelaksanaan, observasi, evaluasi dan refleksi.
Analisis Performa Rasio Kompresi Pada Metode Differensiasi ASCII Dan Lempel Ziv Welch (LZW) Tommy Tommy; Rosyidah Siregar; Amir Mahmud Husein; Mawaddah Harahap; Ferdy Riza
JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Vol. 1 No. 2 (2018): Jutikomp Volume 1 Nomor 2 Oktober 2018
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jutikomp.v1i2.225

Abstract

ASCII differentiation is a compression method that utilizes the difference value or the difference between the bytes contained in the input character. Technically, the ASCII differentiation method can be done using a coding dictionary or using windowing block instead of the coding dictionary. Previous research that has been carried out shows that the ASCII differentiation compression ratio is good enough but still needs to be analyzed on performance from the perspective of the compression ratio of the method compared to other methods that have been widely used today. In this study an analysis of the comparison of the ASCII Difference method with other compression methods such as LZW will be carried out. The selection of LZW itself is done by reason of the number of data compression applications that use the method so that it can be the right benchmark. Comparison of the compression ratio performed shows the results of ASCII differentiation have advantages compared to LZW, especially in small input characters. Whereas in large input characters, LZW can optimize the probability of pairs of characters that appear compared to ASCII differentiation which is glued to the difference values ​​in each block of input characters so that in large size characters LZW has a greater compression ratio compared to ASCII differentiation.
Analisa Frekuensi Hasil Enkripsi Pada Algoritma Kriptografi Blowfish Terhadap Keamanan Informasi Ferdy Riza; Nurmala Sridewi; Amir Mahmud Husein; Muhammad Khoiruddin Harahap
JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Vol. 1 No. 1 (2018): Jutikomp Volume 1 Nomor 1 April 2018
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jutikomp.v1i1.233

Abstract

The ease of sending data with the development of internet technology technology is now a concern, especially the problem of data confidentiality, integrity and information security. Cryptography is one of the techniques used to maintain data confidentiality and information security, the application of cryptographic techniques for information security and data integrity is highly dependent on the formation of keys. In this study proposed a frequency analysis approach to measure the level of information security of blowfish encryption results to determine the distribution form of each character used in the text and find out the exact frequency of each character used in the test text data. The encryption algorithm and description of blowfish method against plaintext are proven to be accurate, but the longer the key character used will greatly affect the level of information security that came from encryption process, this is based on the results of the frequency analysis conducted.
Penerapan Algoritma Apriori dalam Data Mining untuk Memprediksi Pola Pengunjung pada Objek Wisata Kabupaten Karo Sriyuni Sinaga; Amir Mahmud Husein
JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Vol. 2 No. 1 (2019): Jutikomp Volume 2 Nomor 1 April 2019
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jutikomp.v2i1.461

Abstract

Klasifikasi association rule merupakan salah satu teknik dalam data mining yang digunakan dalam penelitian ini untuk mengolah data pengunjung dalam objek wisata. Pada penelitian ini untuk mendapatkan pola/rule pengunjung wisata aplikasi bantu yang digunakan adalah weka, Associatiation rule adalah data mining yang berguna untuk menemukan suatu korelasi atau pola yang terpenting/menarik dari sekumpulan data besar. Algoritma Apriori adalah salah satu algoritma yang melakukan pencarian frequent itemset dengan menggunakan teknik association rule, dengan menggunakan algoritma apriori dapat menghasilkan pola pengunjung dari tanah 2015 dan 2016 pada objek wisata kabupaten karo, dengan algoritma Apriori dapat disimpulkan bahwa pada tahun 2015 jumlah pengunjung lebih sedikit. Pada penelitian ini data yang digunakan sebanyak 122 data jumlah pengunjung bulanan pada pariwisata dari tahun 2015 hingga 2016. Hasil pengujian menunjukkan bahwa nilai confiden yang paling tinggi mencapai 0,92.
Prediksi Jumlah Produksi Palm Oil Menggunakan Fuzzy Inference System Mamdani Christyn Parsaulyan P. Maibang; Amir Mahmud Husein
JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Vol. 2 No. 2 (2019): Jutikomp Volume 2 Nomor 2 Oktober 2019
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jutikomp.v2i2.528

Abstract

Produksi merupakan salah satu kegiatan yang dilakukan dalam sebuah perusahaan khususnya PT Rigunas Agri Utama yang bergerak dalam bidang pengolahan minyak sawit (palm oil). Perencanaan pengambilan keputusan perusahaan dalam menentukan jumlah produksi pada satu periode selanjutnya, bergantung pada sisa persediaan dari satu periode sebelumnya dan juga perkiraan jumlah permintaan pada satu periode selanjutnya. Jumlah permintaan dan persediaan merupakan suatu ketidakpastian. Logika Fuzzy merupakan salah satu ilmu yang dapat menganalisa ketidakpastian. Tujuan dari penelitian ini adalah untuk mengetahui penggunaan aplikasi logika Fuzzy metode Mamdani dalam pengambilan keputusan penentuan jumlah produksi. Pada penelitian ini digunakan metode Mamdani dengan penggunaan perangkat lunak matlab sebagai alat bantu dalam proses prediksi, baik yang menggunakan dua variabel linguistik maupun yang menggunakan tiga variabel linguistik. Untuk mendapatkan keluaran dari metode ini diperlukan 4 tahapan yakni; 1) Pembentukan himpunan fuzzy; 2) Aplikasi fungsi keanggotaan; 3) Rule fuzzy ; 4) Defuzzifikasi, dari hasil defuzzifikasi inilah kita bisa menentukan keputusan yang akan diambil
Deteksi Penyakit Covid-19 Pada Citra X-Ray Dengan Pendekatan Convolutional Neural Network (CNN) Mawaddah Harahap; Em Manuel Laia; Lilis Suryani Sitanggang; Melda Sinaga; Daniel Franci Sihombing; Amir Mahmud Husein
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 1 (2022): Februari 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (618.778 KB) | DOI: 10.29207/resti.v6i1.3373

Abstract

The Coronavirus (COVID-19) pandemic has resulted in the worldwide death rate continuing to increase significantly, identification using medical imaging such as X-rays and computed tomography plays an important role in helping medical personnel diagnose positive negative COVID-19 patients, several works have proven the learning approach in-depth using a Convolutional Neural Network (CNN) produces good accuracy for COVID detection based on chest X-Ray images, in this study we propose different transfer learning architectures VGG19, MobileNetV2, InceptionResNetV2 and ResNet (ResNet101V2, ResNet152V2 and ResNet50V2) to analyze their performance, testing conducted in the Google Colab work environment as a platform for creating Python-based applications and all datasets are stored on the Google Drive application, the preprocessing stages are carried out before training and testing, the datasets are grouped into theNormal and COVID folders then combined m become a set of data by dividing them into training sets of 352 images, testing 110 images and validating 88 images, then the detection results are labeled with the number 1 means COVID and the number 0 for NORMAL. Based on the test results, the ResNet50V2 model has a better accuracy rate than other models with an accuracy level of about 0.95 (95%) Precision 0.96, Recall 0.973, F1-Score 0.966, and Support of 74, then InceptionResNetV2, VGG19, and MobileNetV2, so that ResNet50V2-based CNNs can be used as initial identification for the classification of a patientinfected with COVID or NORMAL.