Article Per Year (5 Year)
p-Index From 2020 - 2025
4.379
P-Index
This Author published in this journals
All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal Fisika FLUX Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal Nasional Komputasi dan Teknologi Informasi IJISTECH (International Journal Of Information System & Technology) Jurnal Mantik Technologia: Jurnal Ilmiah G-Tech : Jurnal Teknologi Terapan JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Sistem Komputer dan Informatika (JSON) TIN: TERAPAN INFORMATIKA NUSANTARA Journal of Computer Networks, Architecture and High Performance Computing IJISTECH Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Infotech: Jurnal Informatika & Teknologi Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Journal of Information Technology (JIfoTech) Journal of Dinda : Data Science, Information Technology, and Data Analytics Jurnal Ilmiah Ilmu Terapan Universitas Jambi Innovative: Journal Of Social Science Research INOVTEK Polbeng - Seri Informatika
Armansyah Armansyah
Computer Science Study Program, Universitas Islam Negeri Sumatera Utara
Aerospace Engineering Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

Published : 28 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 28 Documents
Search

 1   2   3 
Implementasi Jaringan Syaraf Tiruan Backpropagation Pada Klasifikasi Grade Teh Hitam Muhammad Ikhsan; Armansyah Armansyah; Anggara AlFaridzi Tamba
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 2 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i2.5312

Abstract

Black tea is the most widely produced type of tea in Indonesia, where Indonesia itself is the 5th largest black tea exporter in the world. According to the provisions of SNI-1902-2016, the quality requirements of black tea through appearance include the shape, size and weight (density), and the color of the black tea particles themselves. This study aims to determine the workings of the backpropagation method and the implementation of python on black tea grade classification, and to determine the level MSE of accuracy in the results of black tea grade classification using backpropagation. The model used in this study uses 4 input layers, 5 hidden layers, and 3 output layers. In the input layer, 4 input variables are used, namely shape, size, density, and color. The results of the classification using backpropagation with a number of iterations of 1000 iterations on the training data obtained an error of 0.096.
Utilization of Solar Panels as a Source of Electrical Energy in Alternating Current (AC) Water Pump Masthura Masthura; Armansyah Armansyah
Jurnal Fisika Flux: Jurnal Ilmiah Fisika FMIPA Universitas Lambung Mangkurat Vol 20, No 1 (2023): Jurnal Fisika Flux: Jurnal Ilmiah Fisika FMIPA Universitas Lambung Mangkurat
Publisher : Lambung Mangkurat University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/flux.v20i1.14421

Abstract

Solar panels are an alternative power generation system sourced from the absorption of solar energy. The solar energy absorbed will convert into a source of electricity. The solar panel's power drives an alternating current (AC) water pump. This study aims to determine the performance of the AC water pump by utilizing electrical energy sourced from solar panels. The parameters measured are voltage, current, and power generated by the AC water pump at varying times. The solar panels used with a capacity of 100 WP were connected to a solar charge controller (SCC), which was connected to a battery, and an inverter functions as a tool to convert DC  to AC. The results were obtained from solar panels that can optimally drive the AC water pump. At 10.00 WIB, the electric voltage was 17.68 volts, the electric current was 4.98 amperes, and the electric power was 88.04 Watts. At 15.00 WIB, with clear weather conditions,  an electric voltage of 18.90 volts, an electric current of 6.22 amperes, and an electric power of 117.55 Watts were obtained.
PENDEKATAN SDLC MODEL WATERFALL DALAM PERANCANGAN APLIKASI PENDAFTARAN KURSUS Dimas Kurniawan; Armansyah .
Technologia : Jurnal Ilmiah Vol 14, No 3 (2023): Technologia (Juli)
Publisher : Universitas Islam Kalimantan Muhammad Arsyad Al Banjari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/tji.v14i3.11399

Abstract

Perkembangan teknologi informasi (TI), harus mampu mendukung proses bisnis yang menekankan pada prinsip efisiensi, efektifitas dan validitas di bidang pendidikan nonformal. Salah satu teknologi yang sedang populer adalah aplikasi Google Form yang dapat digunakan untuk berbagai kebutuhan pendataan. Sanger Learning yang merupakan lembaga pendidikan non formal di Medan telah menggunakan aplikasi ini dalam menerima pendaftaran peserta kursusnya. Meskipun fasilitas ini telah mendukung proses bisnisnya, namun data lembaga ini tidak benar-benar terkoordinir seperti yang diharapkan dan memerlukan rekonfigurasi untuk tahap yang lebih lanjut. Permasalahan tersebut akan dipecahkan dengan merancang sebuah aplikasi berbasis web yang menjadi tujuan dari penelitian ini. Penelitian ini menggunakan pendekatan System Development Life Cycle (SDLC) dengan model Waterfall. Dari penelitian ini, perancangan aplikasi pendaftaran mahasiswa kursus berjalan dengan baik dan mendukung tahapan pengolahan data lebih lanjut seperti pendaftaran program, pengelolaan kelas, dan pembayaran program kursus.
Rancang Bangun Alat Bantu Pengenalan Warna Untuk Penyandang Buta Warna Menggunakan Metode Coloring Filters (Cf) Dan K-Means Clustering Berbasis Mikrokontroler Lisma Autia; Muhammad Ikhsan; Armansyah Armansyah
Innovative: Journal Of Social Science Research Vol. 3 No. 4 (2023): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v3i4.4348

Abstract

Mata merupakan indra penglihatan yang sangat vital fungsinya bagi manusia dalam kehidupan sehari-hari. Mata pada dasarnya memiliki kepekaan terhadap cahaya dan warna. Jika kepekaan terhadap warna terganggu maka akan dialami oleh sebagian orang yang menyandang kelainan buta warna. Penyakit Buta warna (color blindness) merupakan penyakit yang banyak ditemukan kasusnya di dunia. Terdapat bermacam buta warna, yaitu buta warna total dan buta warna parsial. Agar penderita buta warna dapat mengenali pola warna yang dibentuk, maka dirancang dan dibangun sebuah alat bantu pengenalan pola warna menggunakan sensor TCS3200-DB yang digabungkan dengan mikrokontroler jenis Arduino IDE dan metode coloring filter(cf) dan metode k-means clustering. Dengan tujuan Menerapkan metode coloring filter (cf)dan metode k-means clustering dalam pengenalan warna.Mengetahui rancangan berupa alat bantu pengenalan warna bagi penyandang buta warna berbasis mikrokontroler. Mengetahui hasil dari rancang bangun alat bantu pengenalan warna untuk penyandang buta warna menggunakan metode coloring filters (cf)dan k-means clustering berbasis mikrokontroler.Teknik pengumpulan data dengan langsung terjun kelapangan untuk mengamati permasalahan yang terjadi secara langsung dan studi literatur dalam mencari informasi. Dari hasil penerapan segmentasi citra, penelitian yang dilakukan penulis dalam menganalisis jenis warna berdasarkan nilai RGB. Dalam proses identifikasi benda, warna dominan yang terdeteksi adalah warna biru, hal ini terjadi karena pada sensor warna, warna biru menjadi warna kalibrasi untuk warna lain. Sistem yang dibuat dalam alat bantu deteksi buah warna ini dapat mengenali warna dengan skala yang baik, dari segi tingkat pengenalan warna hingga waktu pendeteksian.
Perbandingan Algoritma Run Length Encoding (RLE) dan Algoritma Variable Length Binary Encoding (VLBE) dalam Mengkompresi File Video Untuk Menghemat Penyimpanan Nur Adillah; Yusuf Ramadhan Nasution; Armansyah
G-Tech: Jurnal Teknologi Terapan Vol 7 No 4 (2023): G-Tech, Vol. 7 No. 4 Oktober 2023
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/gtech.v7i4.3020

Abstract

Kompresi dilakukan guna membuat ukuran file tersebut lebih kecil. Algoritma merupakan urutan langkah-langkah yang bertujuan untuk menyelesaikan suatu persoalan. Pada penelitian ini menggunakan algoritma Run Length Encoding (RLE) dan algoritma Variable Length Binary Encoding (VLBE). Format file video yang dalam penelitian ini adalah .avi dan .mp4 dan menggunakan Microsoft Visual Studio dengan bahasa pemrograman C# berbasis desktop. Hasil dari penelitian ini adalah file yang video yang telah dikompresi akan memperlihatkan performanya dan parameter perbandingan berdasarkan Ratio of Compression (RC), Compression Ratio (CR), dan Redudancy (RD) diantara algoritma Run Length Encoding (RLE) dan algoritma Variable Length Binary Encoding (VLBE). Dengan permasalahan tersebut penulis ingin membuat suatu penelitian skripsi yang berjudul ‘Perbandingan Algoritma Run Length Encoding (RLE) Dan Algoritma Variable Length Binary Encoding (VLBE) Dalam Mengkompresi File Video Untuk Menghemat Penyimpanan’.
Penutupan Kompetensi Keahlian SMK dengan Pendekatan Klasifikasi Minat Siswa Menggunakan Jaringan Syaraf Tiruan Muhammad Ihsan Nugraha; Armansyah Armansyah
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 6 No. 3 (2023): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

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

Abstract

The lack of intereset in audio and video engineering competencies at SMK Muhammadiyah 9 Medan City causes the minimum number of students in the competence. Therefore, the school needs additional information as a tool to assist them in making a policy to continue or terminate the competency. By utilizing the Artificial Neural Network (ANN) approach, the researcher intends to build a student interest classification model based on student psychological datasets that can be used as a tool in analyzing student interest in  audio and video engineering competencies. The classification model was built using 115 data divided into 92 training data and 23 testing data. Where the data will be transformed into binary numbers (1 and 0) in order to perform algorithm properly. The results of this study show that the model can classify student interest very well into the class labels "interested" and "not interested" as evidenced by the accuracy value of 98.9% on training data and 95.65% on testing data.
Penerapan Algoritma C4.5 Pada Klasifikasi Status Gizi Balita Yusuf Ramadhan Nasution; Armansyah; Mhd Furqan; Toibatur Rahma Matondang
JURNAL FASILKOM Vol 14 No 1 (2024): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v14i1.6941

Abstract

The study aims to classify the nutritional status of the child using the C4.5 algorithm. The secondary data used is derived from the assessment of the nutrition status of a child in Puskesmas Promji and Puksesmas Suka Makmur. A classification model is constructed using the C4.5 algorithm based on a number of predictor factors that have been determined. The research methodology includes data collection, data preprocessing, model development with C4.5 algorithms, model evaluation, and results analysis. Model evaluation is done using measurements such as accuracy. In addition, the significance of predictor variables in affecting the nutritional status of infants was also evaluated through data analysis. This research contributed to the development of a method of classifying the nutritional status of infants using the C4.5 algorithm approach. The implication of this study is that the classification model developed can be used as a tool to support early identification and intervention against nutritional problems in infants. Furthermore, based on testing using the confusion matrix technique with the 80:20 data division of a total of 502 datasets, consisting of 402 training data and 100 testing data, an accuracy rate of 80 percent was obtained.
Penerapan Metode Forward Chaining Dan Dempster-Shafer Pada Sistem Pakar Deteksi Dini Gangguan Kesehatan Mental Siti Khalizah; Ilka Zurfia; Armansyah
JURNAL FASILKOM Vol 14 No 1 (2024): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v14i1.6942

Abstract

Early detection of mental health disorders is a major challenge in the field of health. The forward chaining method and the Dempster-Shafer theory are two approaches that can be used in the development of expert systems for early detection of mental health disorders. The forward chaining method is used to identify early symptoms that may indicate mental health disturbances, whereas the dampster-sshafer theories are used to manage uncertainty in the conclusion process, while the dampster-shafer theorem is used for managing uncertainties in the diagnosis process. The study combines both approaches in the development of an expert system for the early detection of mental health disorders. Furthermore, Dempster-Shafer's theory is used to combine evidence from various symptoms and take into account the uncertainty in diagnosis. This method is implemented in a computer-based expert system that can assist health professionals in the early detection of mental health disorders in patients. The system tests were conducted using information from a number of patients who had been clinically diagnosed, and the results suggested that this approach could provide accurate results in the early detection of mental health disorders. In conclusion, the combination of the forward chaining method and the Dempster-Shafer theory achieved 100% accuracy of the system with an average density of 73,496%.
Implementation of Naïve Bayes Method Diagnosing Diseases Nile Tilapia Ridho Wahyudi Pulungan; Sriani Sriani; Armansyah Armansyah
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 2 (2024): Articles Research Volume 6 Issue 2, April 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i2.3834

Abstract

The Nile tilapia, also known as Oreochromis niloticus, was a freshwater fish species first produced in East Africa in 1969. It became a popular aquaculture fish in freshwater ponds across Indonesia. Besides its delicious taste, the Nile tilapia is rich in nutrients essential for human health. However, cultivating Nile tilapia was challenging due to frequent bacterial diseases. These diseases often led to mass fish deaths, causing financial losses, especially for new fish farmers. The rapid spread of diseases emphasized the need for prompt intervention to prevent further losses. Farmers needed adequate knowledge about Nile tilapia diseases, but often struggled to absorb information provided by the government. Hence, the presence of experts or veterinarians was crucial in assisting farmers to address these issues. Farmers of Nile tilapia sought assistance from experts or veterinarians, but this was not easy. It involved substantial costs and time, while quick intervention was necessary to mitigate losses. The solution proposed was the development of an expert system for diagnosing and treating Nile tilapia diseases. Thus, an expert system was built to assist fish farmers in identifying fish diseases and their treatments by implementing the naïve Bayes method. The expert system transferred human knowledge to computers, enabling them to solve problems like experts, thereby making expert knowledge accessible to non-experts. Naïve Bayes was implemented to determine the highest probability based on input symptoms. This research used five test data samples to apply the naïve Bayes method to diagnose Nile tilapia diseases, resulting in an accuracy rate of 80%. Therefore, the implementation of naïve Bayes in diagnosing Nile tilapia diseases is considered reasonably effective.
Decision Tree C4.5 dengan Teknik Information Gain Untuk Klasifikasi Pemilihan Program Studi Tingkat Lanjut Teddy Yogi Pratama; Armansyah Armansyah
Journal of Information System Research (JOSH) Vol 5 No 4 (2024): Juli 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i4.5643

Abstract

The aim of this research is to analyze the application of informative features, classify data based on academic features, interests and talents with Information Techniques using Decision Tree C4.5. The aim of this research is to conduct research on students in determining the choice of study program to continue their education to college, because in choosing a study program to continue their education to college, students often experience difficulties in determining which study program they will choose. The research collected 140 student data, by distributing questionnaires to prospective new students and asking the school for students' academic scores, the author has 140 data that will be used in this research. Next, from the 140 data, researchers will divide it into two parts, namely 118 training data and 22 testing data to meet the needs in designing the model. Based on the results of research conducted using the Supervised Learning Decision Tree C4.5 approach and applying the Information Gain technique for classification of advanced study program selection, an accuracy of 86% was obtained. This success rate shows that the method is effective in identifying and classifying advanced study programs. This indicates that the use of Decision Tree C4.5 which utilizes the Information Gain technique has great potential as a model that can assist students in choosing their advanced study program with a satisfactory level of accuracy. With high accuracy results, this method can be relied on to provide accurate predictions in the context of study program selection.
Co-Authors Anggara AlFaridzi Tamba Catur Hidayatullah Dimas Kurniawan Dita Desliani Erti Belastari Tanjung Fitri Handayani Siregar Guntur Syahputra Heri Santoso Ilka Zufria Ilka Zurfia Irda Nila Selvia Lely Sahrani Lisma Autia M. Idris M. Idris Masthura, Masthura Mhd Furqan Mia Audina Rambe Moch Iswan Perangin-angin Mohd Khairul Amri Kamarudin Muhammad Ihsan Nugraha Muhammad Ikhsan Muhammad Ikhsan Muhammad Rizky Pratama Nur Adillah Nurhasanah Nurhasanah Rahmat Kurniawan Rakhmat Kurniawan R Razzaq H. Nur Wijaya Ridho Wahyudi Pulungan Russell Ong Siti Khalizah Sonia Wanda Mafriza Teddy Yogi Pratama Toibatur Rahma Matondang Yusuf Ramadhan Nasution Yusuf Ramadhan Nasution