Article Per Year (5 Year)
p-Index From 2021 - 2026
8.457
P-Index
This Author published in this journals
All Journal Jurnal Sains dan Teknologi Jurnal Simetris Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Journal of Telematics and Informatics Jurnal Simantec Jurnal sistem informasi, Teknologi informasi dan komputer Telematika : Jurnal Informatika dan Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) JUITA : Jurnal Informatika Jurnal Informatika dan Teknik Elektro Terapan Jurnas Nasional Teknologi dan Sistem Informasi CESS (Journal of Computer Engineering, System and Science) Journal of Animation & Games Studies JOIN (Jurnal Online Informatika) Sistemasi: Jurnal Sistem Informasi Jurnal Pengabdian UntukMu NegeRI JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JRSI (Jurnal Rekayasa Sistem dan Industri) Jurnal Pilar Nusa Mandiri Faktor Exacta Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Indonesian Journal of Information System JURNAL ILMIAH INFORMATIKA SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Surya Abdimas MIND (Multimedia Artificial Intelligent Networking Database) Journal Indonesian Journal of Applied Informatics STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Antivirus : Jurnal Ilmiah Teknik Informatika JUTIS : Jurnal Teknik Informatika JISKa (Jurnal Informatika Sunan Kalijaga) JATI (Jurnal Mahasiswa Teknik Informatika) Joined Journal (Journal of Informatics Education JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Journal of Innovation Information Technology and Application (JINITA) Jurnal Bakti Masyarakat Indonesia Innovation in Research of Informatics (INNOVATICS) Jurnal Dinamis Jurnal Teknik Informatika (JUTIF) Informatics and Digital Expert (INDEX) JoMMiT : Jurnal Multi Media dan IT JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Pengabdian Masyarakat untuk Negeri (UN-PENMAS) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Ilmu Komputer untuk Masyarakat Abdi Teknoyasa Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Jurnal Informatika dan Multimedia "JAMASTIKA" Jurnal Mahasiswa Teknik Informatika Tekmulogi: Jurnal Pengabdian Masyarakat SATIN - Sains dan Teknologi Informasi Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) NERO (Networking Engineering Research Operation) Jurnal Informatika: Jurnal Pengembangan IT PADIMAS: Jurnal Pengabdian Masyarakat Jurnal Pengabdian Siliwangi Abdi Karya: Jurnal Pengabdian Kepada Masyarakat Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) International Journal of Informatics and Computing
Alam Rahmatulloh
Program Studi Informatika, Fakultas Teknik, Universitas Siliwangi
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Transportation Other

Published : 100 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 100 Documents
Search

 3   4   5   6   7 
Implementation of JSON Web Token on Authentication with HMAC SHA-256 Algorithm Ficry Cahya Ramdani; Alam Rahmatulloh; Rahmi Nur Shofa
Sistemasi: Jurnal Sistem Informasi Vol 12, No 1 (2023): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v12i1.2450

Abstract

The rapid growth of information technology is influenced by globalization to accelerate access to information. This creates new problems, as differences must produce relevant information. Of course, system integration will be required. Web Service is a system integration solution that does not consider the platform, architecture, or programming language used in different sources. The security of web service is considered not yet implemented. The JSON Web Token (JWT) technology is an authentication mechanism for web service and will have a significant impact on data security. This implementation optimizes JWT security with the HMAC SHA-256 algorithm. Testing is conducted on two information systems by comparing the performance size when JWT technology is applied to Tim Bebersih Masjid Information System. The results show that the implementation of JWT on Windows Server 2019 (VM) is 462.8 ms with an average data size of 8.59 kb. Testing on the Windows 10 operating system obtained an average speed of 216.25 ms with an average data size of 8.59 kb. The result on Windows Server 2019 (VM) from the JWT performance test itself obtained the highest result, due to the use of virtual machine which is considered to consume a lot of RAM, resulting in performance that is 2 times higher.Keywords: Algorithm, HMAC SHA-256, JSON Web Token, Web Service, Virtual Machine
PERBANDINGAN GATED RECURRENT UNIT (GRU) DAN ALGORITMA LONG SHORT TERM MEMORY (LSTM) LINEAR REFRESSION DALAM PREDIKSI HARGA EMAS MENGGUNAKAN MODEL TIME SERIES Anggi Putri Meriani; Alam Rahmatulloh
Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 1 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i1.3808

Abstract

Abstrak. Prediksi harga emas sangat penting karena menjadi acuan bagi para investor untuk menentukan strategi yang tepat dalam berinvestasi. Tren metode prediksi dalam beberapa tahun terakhir adalah deep learning, yang merupakan subbidang machine learning dan populer dalam menangani masalah prediksi time-series. Dalam penelitian ini, kami membandingkan performa dua metode deep learning, yaitu Long Short-Tern Memory (LSTM)  Gated Recurrent Unit (GRU)dan Linier Regression dalam memprediksi harga Emas. Hasil dalam penelitian ini menunjukkan bahwa metode GRU lebih akurat dibanding metode LSTM dalam memprediksi harga Emas, meskipun dalam perhitungan metrik evaluasi didapatkan nilai eror LSTM lebih rendah. Hasil model LSTM terbaik yang diujikan memiliki nilai MAE sebesar 0.0389, RMSE sebesar 0.0475, dan MAPE sebesar 5.2047%, serta model GRU terbaik dari hasil pengujian memiliki nilai MAE 0.0447, RMSE 0.0545, dan MAPE 6.0688%. Dari hasil penelitian ini, kami menemukan bahwa GRU adalah metode yang lebih efektif dan akurat untuk memprediksi harga Emas dibanding LSTM.Kata Kunci : Emas;, GRU;  LSTM; Metrik Evaluasi, Prediksi,  Time Seris
Sosialisasi dan Pelatihan Penggunaan Aplikasi SMART Guna Mendukung Tertib Administrasi di Lingkungan Rukun Tetangga Rahmatulloh, Alam; Rianto, Rianto; Gunawan, Rohmat; Rizal, Randi
UN PENMAS (Jurnal Pengabdian Masyarakat untuk Negeri) Vol 4 No 1 (2024): UN PENMAS Vol 4 No 1
Publisher : LPPM Universitas Narotama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29138/un-penmas.v4i1.2562

Abstract

Rukun Tetangga (RT) is a community organization formed through deliberation and consensus of the local community to maintain harmony in life. Managing population administration at the RT level is one of the responsibilities of the RT Head. Population administration needs to be managed well, because population data is a basic statistical source in making various policies. In order to create administrative order in managing population data, in this service activity, socialization and training on the use of the SMART application (Sistem Informasi Manajemen Administrasi Rukun Tetangga) is carried out. Residents of RT 04 RW 07 Arjasari Village, Leuwisari District, Tasikmalaya Regency are partners in this service activity. There are several stages carried out in this service activity, including: stage 1 initial preparation, stage 2 main program, stage 3 closing the activity. Socialization and training on using the SMART application was carried out at partner locations on Friday 15 September. This application is expected to facilitate and make it easier for RT Heads and residents to complete population data and support orderly administration.
Evaluasi Aplikasi GrabHealth dari Perspektif End User Menggunakan AdEQUATE Questionnaire Berdasarkan ISO/IEC 25010 Model Aulia, Karina; Rahmatulloh, Alam; Putra, Aldy
Joined Journal (Journal of Informatics Education) Vol 6 No 2 (2023): Volume 6 Nomor 2 (2023)
Publisher : Universitas Ivet

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31331/joined.v6i2.2629

Abstract

Telehealth sebagai layanan kesehatan berbasis teknologi dinilai sebagai solusi paling cepat dan ekonomis untuk meraih pasien pada daerah dengan minim infrastruktur dan sebagai upaya promotif dalam isu kesehatan Sayangnya, berdasarkan sebuah publikasi penelitian di tahun 2013, terdapat 190 kasus kesalahan diagnosis pasien yang hampir 4% kasus disebabkan oleh malfungsi sistem telehealth. SQA merupakan kegiatan berbagai aspek yang berfokus pada manajemen kualitas perangkat lunak yang terdiri dari rangkaian audit dan pelaporan fungsi yang menilai efektivitas dan kelengkapan yang dilakukan dalam upaya menjamin mutu aplikasi. Dalam penelitian ini akan membahas evaluasi aplikasi telehealth menggunakan AdEQUATE Questionnaire. Hasil penelitian ini adalah aplikasi telehealth GrabHealth dinilai memenuhi standar ISO/IEC 25010. Penelitian ini diharapkan dapat menjamin mutu aplikasi GrabHealth dan sebagai bahan pertimbangan peningkatan mutu aplikasi GrabHealth.
Comparison of Machine Learning Algorithms in Detecting Contaminants in Drinkable Water Elmeftahi, Souhayla; Rakhman, Maulana Decky; Rahmatulloh, Alam
Innovation in Research of Informatics (Innovatics) Vol 6, No 1 (2024): March 2024
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v6i1.10385

Abstract

Water, a vital natural resource essential for human existence, is a fundamental human right, indispensable for a dignified life. Despite its significance, the quality of water is often compromised by a myriad of harmful substances, minerals, and contaminants stemming from various sectors like industry, agriculture, residential, and energy. Traditional methods such as WQI and STORET, relying on manual inspection, prove time-consuming. Thus, the integration of machine learning emerges as a pivotal solution to swiftly assess water quality.Numerous studies have explored this challenge using various algorithms; however, a definitive comparison is elusive due to the abundance of existing methods. In response, this research undertakes a meticulous evaluation of seven algorithms to ascertain the optimal approach for water quality classification, employing metric values as benchmarks. Notably, the Random Forest algorithm emerges as the most effective, achieving an impressive accuracy of approximately 84.8%. Following closely are the XGBoost and CatBoost algorithms, showcasing commendable performance with accuracies of 82.9% and 80.2%, respectively. Subsequent rankings include the Decision Tree algorithm at 77.3%, SVM at 72.3%, K-NN at 70.6%, and AdaBoost with the lowest accuracy at 63.33%. This comparative analysis contributes valuable insights for informed decision-making in water quality assessment.    
Performance Comparison of Response Time Native, Mobile and Progressive Web Application Technology Rochim, Rachma Verina; Rahmatulloh, Alam; El-Akbar, R Reza; Rizal, Randi
INNOVATICS: International Journal on Innovation in Research of Informatics Vol 5, No 1 (2023): Maret 2023
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v5i1.7045

Abstract

The development of technology in web-based applications is growing, this creates new problems. The web technology that is currently being discussed is Progressive Web Application (PWA) but is the PWA's performance better than the previous technology. This research is about measuring the performance of the Native Web, Mobile Web and PWA using three testing tools, namely GTMetrix, Lighthouse, and Chrome DevTool. The results of this study show how to measure the performance of a Progressive Web Application (PWA), where PWA can beat the performance of Native Web and Mobile Web if a web page is tested more than once. Test results on the Progressive Web Application (PWA), the minimum number of page files (home) is 217 kB with page loading time of 638 ms, while the medium page (about) is 431 kB with page loading time of 646 ms, and when accessing heavy pages (news) with a size of 41700 kB the page load time is 532 ms.
Perbandingan Skor Prediksi dalam Pembelajaran Mesin pada Keselamatan Penumpang Kapal: Comparison of Prediction Scores in Machine Learning on Ship Passenger Safety Perkasa, Mochamad Althaf Pramasetya; Rahmatulloh, Alam
Jurnal Mahasiswa Teknik Informatika Vol. 3 No. 1 (2024): Jurnal Jamastika Vol.3 No.1 April 2024
Publisher : Universitas Ngudi Waluyo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35473/jamastika.v3i1.2739

Abstract

Passenger safety is an important aspect of the shipping industry, and precise predictions of emergencies and safety situations can provide great advantages in managing risks at sea. Precise prediction of emergency and safety situations can provide great advantages in managing risks at sea. This research involves collecting and analyzing historical data on ship accident incidents and their influencing factors. Machine learning methods, such as logistic regression, KNN, Naïve Bayes Classifier, Decision Tree, Random Forest, etc. will be used to identify patterns in the data that can be used to predict ship passenger safety. The data used in this study includes variables such as weather, ship state, number of passengers, and other relevant factors. The research data was taken from titanic passengers. The results of this study resulted in a model that is suitable for predicting the safety of ship passengers, namely the random forest model and decision tree getting the highest score compared to other models, the prediction score is 84.29%.
Analisis dan Rekomendasi Character Pada Game Genshin Impact Berdasarkan Revenue Banner Menggunakan Algoritma Clustering Faisal, Fikri Ahmad; Rahmatulloh, Alam
Jurnal Mahasiswa Teknik Informatika Vol. 3 No. 1 (2024): Jurnal Jamastika Vol.3 No.1 April 2024
Publisher : Universitas Ngudi Waluyo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35473/jamastika.v3i1.2741

Abstract

In the era of video game industry development, optimizing monetization within games has become a primary concern for developers. Analyzing revenue data from banner characters and categorizing characters are relevant steps, especially for players who are new to the game. This involves providing character recommendations based on the income generated from game banners. The main issue faced by players is the difficulty in choosing the right banner characters to invest in, considering that each banner features different characters with varying appearance statistics. Additionally, players need guidance in identifying characters with the most potential to enhance their performance. The approach employed in this research involves using Clustering Algorithms to group characters based on factors relevant to banner income, including character popularity, availability in banners, and their unique abilities. Detailed transaction data analysis in the game is conducted using K-Means Clustering and Hierarchical Clustering algorithms to generate character groups. The research results demonstrate that employing clustering algorithms produces character groups that provide insights for players to consider allocating their resources to characters categorized in high-income or low-income groups. By using character recommendations based on these groups, players can be guided to select characters that align with their preferences and gameplay styles.
CLASSIFICATION OF BATIK TASIKMALAYA USING NEURAL NETWORK WITH GLCM DAN LBP FEATURE EXTRACTION Popy, Popy Anisa; Alam Rahmatulloh
Jurnal Mahasiswa Teknik Informatika Vol. 3 No. 1 (2024): Jurnal Jamastika Vol.3 No.1 April 2024
Publisher : Universitas Ngudi Waluyo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35473/jamastika.v3i1.2742

Abstract

Batik adalah seni kain tradisional Indonesia yang motifnya dibuat dengan menggunakan teknik pewarnaan kain yang melibatkan penggunaan lilin untuk mencegah pewarnaan pada area tertentu. Hal ini menciptakan pola yang unik dan khas pada kain. Penelitian ini bertujuan untuk membantu mengatasi kesulitan yang dihadapi masyarakat dalam mengidentifikasi motif batik di Tasikmalaya. Dengan penerapan teknologi Artificial Neural Network (ANN) serta ekstraksi fitur menggunakan Gray Level Co-Occurrence Matrix (GLCM) dan Local Binary Pattern (LBP), penelitian ini mencapai tingkat akurasi yang tinggi, sekitar 95% dengan GLCM dan 80% dengan LBP , dalam mengklasifikasikan motif batik seperti Merak Ngibing, Lancah Tasik, Sidomukti Payung, dan Sukapura. Hal ini menunjukkan efektivitas metode tersebut dalam membantu identifikasi motif batik dengan tingkat akurasi yang tinggi.
PENERAPAN METODE WEBQUAL 4.0 DAN IMPORTANCE PERFORMANCE ANALYSIS (IPA) DALAM EVALUASI KUALITAS WEBSITE KOMUNITAS KUMPULAN WARGI SUKAPURA (KWS) Leviana, Rika; Rahmatulloh, Alam
Jurnal Simantec Vol 12, No 2 (2024): Jurnal Simantec Juni 2024
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/simantec.v12i2.23313

Abstract

One use of websites is applied in a community, namely the Sukapura Wargi Group, where in this community it is used as a medium for conveying information and managing data. The new KWS website was created because previously it did not have any website. A website must have good quality, because website quality is an important factor that must be considered so that it has good value in cyberspace and can be used as expected. To measure the quality of the KWS website, it is necessary to carry out an evaluation to ensure an optimal experience for users. The methods that can be used to evaluate the quality of community websites are the WebQual 4.0 method and Importance Performance Analysis (IPA). The application of the WebQual 4.0 method is because it can measure website quality based on three main dimensions, namely information quality, interaction quality and service quality. Meanwhile, the natural science method is used as a calculation method. The results of this research show that the KWS community websites that have been measured have an average value of Performance and Importance of 9.082 and 10.48. The average result obtained based on the suitability level value is 93.15% with the largest suitability level value found in the usability  dimension, namely 100.82%, while the result of the average gap value (GAP) is -3.079.Keywords: Importance Performance Analysis, Kumpulan Wargi Sukapura, Website, WebQual
Co-Authors Aditya, Hafish Naufal Aemy, Nandhitta Albi Fitransyah Aldy Putra Aldya Alpan Hikmat Muharram Permana Amaludin, Luthfi Andi Nur Rachman Andi Nurachman Anggi Putri Meriani Anggi Putri Meriani Anjar Ginanjar ANWAR, FAHMI Aradea Aradea, A Asep Kurniawan Asep Rizki Maulana Asih, Dwi Ramti Aulia, Karina Awaludin, Rizkie Irfan A’izzah, Virra Retnowati Budi Permana Darmawan, Muhamad Aditya Dewi Rahmawati Dita Pramesti Dodi Muhamad Kodar Dwi Ramti Asih Eka Wahyu Hidayat Eka Wahyu Hidayat El Akbar, R Reza El-Akbar, R Reza Elmeftahi, Souhayla Ernawati, Rita Sri Faisal Al Isfahani Faisal Muhammad Dzikry Faisal, Fikri Ahmad Fatchul Arifin Ficry Cahya Ramdani Firdaus, Muhamad Akbar Firmansah, Teguh Anugrah Firmansyah MSN Firmansyah, Faldi Ramadhan Fuji Nugraha Gagan Akhmad Fauzi Galih Permana Genta Nazwar Tarempa Ginting, Muliani Guna, Nandana Surya Gunawan, Rohmat Gunawan, Rohmat Gunawan, Rohmat Haerani, Erna Hanifah, Faridah Heni Sulastri Heni Sulastri Herlambang, Andriana Herman Dwi Surjono Hidayat, Deri Kurnia Hidayat, Eka Wahyu Hilman Septian husen husen Husen Husen Husen, - Ihsanuddin Ihsan Ikhsan Nur Rizkiana Ilham Yuslin Anugrah Indra Sontana Iqbal Muhammad Fajar Nuralam Irfan Darmawan Ivang Fahmi Fauzi Kodar, Dodi Muhamad Komara Kusumah, R Herick Fauzi Kusumah, R Herick Fauzi Komara Laely Armiyati Lapandu, Raihan Azhar Leka Destrilia Leviana, Rika Maulana, Dikri Merdiriyani, Sindy Meriani, Anggi Putri Mochamad Dzikri Daely Muhammad Ramadhan, Galih Muhammad Saiful Anwar Neng Ika Kurniati Neng Ika Kurniati Neng Ika Kurniati Neng Ika Kurniati Nida, Siti Nabilah Nugraha, Cindera Syaiful Nugraha, Geri Nugroho, Rizal Nur Widiyasono Nur Widiyasono, Nur Perkasa, Mochamad Althaf Pramasetya Popy, Popy Anisa Purwayoga, Vega Putra, Aldy R. Reza El Akbar R. Wahjoe Witjaksono Rachman, Andi Nur Rahmi Nur Shofa Rahmi Nur Shofa Rakhman, Maulana Decky Ramdani, Setiadi Randi Rizal Rianto, Rianto Ridwan Nur Qomar Rifki Mubarok Riki Ahmad Fauji Rita Sri Ernawati Rizal Nugroho Rizal, Randi Rizal, Randi Rochim, Rachma Verina Rohmat Gunawan Rohmat Gunawan Rukiman, Sheptianna Healtha Ruuhwan Ruuhwan Salman, Ade Selamat, Siti Rahayu Septian, Hilman Setiawan, Muhamad Bayu Setiawan, Perdi Shihab, Muhammad Quraish Shofa, Rahmi Nur Sholihat Ruhaedi, Hedy Sulastri, Heni Sulastri, Heni Sulastri, Heni Virra Retnowati A’izzah Visi Tinta Manik Warih Puspitasari Yuliasari, Silpani Yusup Mochamad Ramdani Yuzar, Arnefia ZK Abdurahman Baizal