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All Journal Teika Jurnal Sarjana Teknik Informatika Scan : Jurnal Teknologi Informasi dan Komunikasi Teknika: Jurnal Sains dan Teknologi Jurnal IPTEK Jurnal Sistem Informasi dan Bisnis Cerdas Journal of Information System JOIV : International Journal on Informatics Visualization Jurnal Pendidikan Informatika dan Sains INTEGER: Journal of Information Technology JURNAL ILMIAH INFORMATIKA Jurnal Informatika Universitas Pamulang RESEARCH : Computer, Information System & Technology Management Jiko (Jurnal Informatika dan komputer) Jurnal Ilmiah Sinus Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar JUTIS : Jurnal Teknik Informatika Jurnal Teknologi Informasi dan Terapan (J-TIT) bit-Tech Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Jifosi e-NARODROID Nusantara Science and Technology Proceedings Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Journal of Technology and Informatics (JoTI) Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Penelitian Sistem Informasi Nusantara Journal of Computers and its Applications Jurnal Informatika Polinema (JIP) Jurnal Pengabdian Teknik dan Sains (JPTS) Prosiding Seminar Nasional Ilmu Sosial dan Teknologi (SNISTEK) JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Jurnal Serumpun Teknik Informatika
Parlika, Rizky
Universitas Pembangunan Nasional Veteran Jawa Timur
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Pemodelan Dataset On-chain pada BiLSTM untuk Prediksi Harga Bitcoin Malik, Gamar Ramadhani; Parlika, Rizky; Kartini, Kartini
JURNAL FASILKOM Vol. 16 No. 1 (2026): 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.v16i1.11275

Abstract

Bitcoin is a crypto asset for investment. It can give high profit, but it also has high risk because the price changes very fast and is not stable. To reduce the risk of loss, we need a prediction system that can read price changes well. This research aims to model and predict the closing price of Bitcoin using network activity data (on-chain metrics). The method used is Deep Learning with the BiLSTM algorithm. This method is chosen because it can process data in two directions (forward and backward), so it can learn patterns better than standard LSTM. The dataset is taken from the public Blockchain network using BigQuery, from August 18, 2011, to February 6, 2026, with 5,287 daily data. The model uses the main input active_spending_addresses and two volatility indicators: Percent of Top Range (PTR) and Percent Low Range (PLR). Before modeling, the data is processed using a sliding window of 60 days, with 90% training data and 10% testing data. The results show that the BiLSTM model has high accuracy, with MAE 2.958, RMSE 3.905, and MAPE 3.22%. The comparison shows that BiLSTM is better than other models. LSTM has MAPE 29.06%, and MLP has MAPE 4.01%. In conclusion, BiLSTM can handle extreme crypto market changes very well, so it gives stable and accurate Bitcoin price predictions.
Implementation of Two-Factor Authentication (2FA) Using a REST API-Based WhatsApp Gateway to Prevent Fake Bidders on an Online Auction Platform Rizky Parlika; Hamdi Indra; Tegar Satria Kirana
Jurnal Serumpun Teknik Informatika Vol. 1 No. 2 (2026): April 2026
Publisher : Yayasan Ibrahim Learning Centre Agam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66485/jsti.v1i2.19

Abstract

Account security and identity validity are crucial aspects of online auction platforms to prevent price manipulation by fake bidders. Conventional authentication methods are often vulnerable to cyber-attacks or compromise user convenience for the sake of security. This study aims to implement a Two-Factor Authentication (2FA) system on the Mokasindo auction platform using WhatsApp Gateway integrated via REST API technology. The development method includes Webhook mechanisms for real-time user phone number validation and AJAX Short Polling techniques to deliver auto-login features without page refreshing. Black Box testing results indicate that the system successfully verifies user identity accurately and mitigates the risk of fictitious account registration. This implementation offers an optimal balance between system security and User Experience (UX), with an average recorded verification process latency of only 3.5 seconds. This solution proves effective in creating a more secure, responsive, and trustworthy auction ecosystem for users.
Comparative Analysis of Performance and Security Static and Dynamic JSON Web Token (JWT) Rizky Parlika; Muhammad Romi Nasution; Dino Rosanilo Yuswanto
Jurnal Serumpun Teknik Informatika Vol. 1 No. 2 (2026): April 2026
Publisher : Yayasan Ibrahim Learning Centre Agam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66485/jsti.v1i2.20

Abstract

The rapidly evolving technology era demands a secure and efficient authentication mechanism when exchanging information between users and servers. One of the most common authentication methods used in REST APIs is JSON Web Token (JWT) due to its stateless and lightweight nature. However, the implementation of static JWT still has a weakness because pre-existing tokens can be used in other contexts such as other devices or other IP addresses. This can result in token misuse, resulting in data leakage. This study was conducted by comparing the performance and security aspects of static JWT and dynamic JWT in REST APIs using the PHP Laravel framework. Testing results show that the implementation of static and dynamic JWT does not have a significant difference in performance. However, dynamic JWT excels in security aspects because it is able to detect unauthorized access attempts due to context mismatch.
Predicting Bitcoin Price Trends Using an LSTM Model Based on Multi-Variable Technical Indicators Rizky Parlika; Ilham Asy’ari; Rizky Ananda Ramadhan
Jurnal Serumpun Teknik Informatika Vol. 1 No. 2 (2026): April 2026
Publisher : Yayasan Ibrahim Learning Centre Agam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66485/jsti.v1i2.21

Abstract

The sharp price fluctuations in the cryptocurrency market, particularly in Bitcoin (BTC), create significant risks while simultaneously offering speculative profit potential for investors. Traditional analytical methods are often ineffective in detecting non-linear patterns present in stochastic financial time series data. This study proposes the application of a Deep Learning model utilizing the Long Short-Term Memory (LSTM) architecture to project the directional trend of Bitcoin prices (whether upward or downward) for the upcoming one-hour period. In the model's development, historical price data is integrated with a set of crucial technical variables, including the Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), and Exponential Moving Average (EMA), which serve as input attributes to enhance accuracy. Market data is retrieved in real-time via the Binance API, covering the last 1000 candlesticks. Experimental results using a Stacked LSTM architecture demonstrate that the model achieves an accuracy rate of 51.08% on the test data. Although this classification accuracy is considered moderate, a simple backtesting simulation indicates a positive profitability potential of 2.88% with a win rate of 48.39%. The output of this research also includes a web-based system prototype that integrates a Python backend with a visual interface for real-time monitoring of prediction signals.
RESTful API Development for Student Schedule and Attendance Management in a Higher Education Environment Rizky Parlika; Abidin Sulaiman; Riky Hermawan
Jurnal Serumpun Teknik Informatika Vol. 1 No. 2 (2026): April 2026
Publisher : Yayasan Ibrahim Learning Centre Agam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66485/jsti.v1i1.22

Abstract

This study presents the development of a RESTful API service to support student schedule and attendance management in a higher education environment. The research is motivated by the fact that schedule management and attendance recording are often still handled manually or by stand-alone applications, which complicates recap processes, attendance monitoring, and integration with existing academic information systems. The proposed system is implemented using the Laravel framework and MySQL database, where student, lecturer, course, schedule, and attendance entities are modeled in a structured way and exposed through RESTful endpoints over HTTP with JSON data format. The research adopts a software engineering approach consisting of requirement analysis, system design, implementation, and testing using Postman on a local development environment. The experimental results show that all CRUD operations and attendance recording functions work as expected, producing consistent JSON responses with appropriate HTTP status codes, indicating that the developed API is suitable to be used as a foundation for future integration with web and mobile applications
Perancangan Arsitektur Cache-Aside Menggunakan Redis pada Sistem Informasi Akademik: Studi Prototipe dan Simulasi Beban Yoga Ari Tofan; Rizky Parlika; Steffanuel Pranatalie Krispriyanto
Jurnal Informatika Polinema Vol. 12 No. 3 (2026): Vol. 12 No. 3 (2026)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v12i3.9675

Abstract

Sistem informasi akademik, khususnya pada modul Kartu Rencana Studi (KRS), kerap mengalami lonjakan trafik ekstrem di awal semester. Arsitektur konvensional yang sepenuhnya bergantung pada basis data relasional berpotensi mengalami masalah latensi akibat antrean input/output (I/O) disk pada kondisi konkurensi tinggi. Penelitian ini merancang dan mengimplementasikan prototipe arsitektur Cache-Aside menggunakan Redis sebagai cache layer pada sistem backend berbasis Python (Flask). Untuk mengevaluasi perilaku arsitektur, dibangun model simulasi di mana latensi akses basis data (500 ms) dan latensi akses cache (5 ms) ditetapkan berdasarkan karakteristik tipikal yang dilaporkan dalam literatur. Pengujian beban dilakukan menggunakan Locust dengan simulasi 1.000 pengguna konkuren dan spawn rate 100 pengguna per detik. Hasil simulasi menunjukkan bahwa arsitektur Cache-Aside mampu menurunkan waktu respons rata-rata dari 507,52 ms (tanpa cache) menjadi 9,12 ms (dengan cache), meningkatkan throughput dari 385,71 menjadi 483,03 request per detik, serta mempertahankan zero failure rate pada kedua skenario. Distribusi persentil menunjukkan konsistensi performa: p95 turun dari 520 ms menjadi 13 ms. Hasil ini mengonfirmasi bahwa pola Cache-Aside secara arsitektural efektif dalam mengalihkan beban kerja dari penyimpanan berbasis disk ke memori pada skenario lonjakan trafik akademik. Validasi lebih lanjut dengan infrastruktur MySQL dan Redis sesungguhnya diperlukan untuk mengonfirmasi parameter simulasi.
MENYUSURI EVOLUSI CENTOS: STABIL, ANDAL, DAN TERUS BERKEMBANG Yoga Ari Tofan; Rizky Parlika; Dandi Azaidane; Muhammad Ilham Arzaki; Bima Rizqy Prasurya; Fadhli Shidqi Wiratama; Hidayat Nur Tauhid
Jurnal Informatika dan Sistem Informasi (JIFoSI) Vol. 6 No. 3: Advancing Digital Education and Intelligent Computing Applications
Publisher : UPN "Veteran" Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/jifosi.v6i3.558

Abstract

CentOS merupakan distribusi Linux berbasis RHEL yang dikenal karena kestabilan dan keamanannya di lingkungan server. Penelitian ini menggunakan metode studi literatur untuk menganalisis perkembangan, kelebihan, kekurangan, serta potensi pengembangan CentOS. Hasil kajian menunjukkan bahwa CentOS unggul dalam kestabilan sistem, efisiensi sumber daya, dan keamanan kernel, meskipun kurang fleksibel untuk integrasi cloud dan memerlukan konfigurasi manual. Dibandingkan Ubuntu, CentOS lebih stabil dan cocok untuk server enterprise, sedangkan Ubuntu unggul dalam kemudahan penggunaan. Potensi pengembangan CentOS mencakup penerapan pada e-Government, pendidikan, cloud computing, dan sistem monitoring otomatis, menjadikannya fondasi penting dalam transformasi digital modern.
Sistem Pendukung Keputusan Perdagangan Cryptocurrency Menggunakan Pembobotan Kombinasi Indikator EMA, RSI, MACD, dan Bollinger Bands M. Zaky Pria Maulana; Rizky Parlika; Firza Prima Aditiawan
JOINS (Journal of Information System) Vol 11 No 1 (2026): Edisi (Desember 2025 - Mei 2026)
Publisher : Fakultas Ilmu Komputer, Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/joins.v11i1.15776

Abstract

Cryptocurrency trading has rapid and significant price changes that cause investors to make decisions based solely on intuition when buying assets, potentially leading to a risk of loss. Therefore, this research aims to develop a cryptocurrency trading decision support system (DSS) using a combination of technical indicators, namely EMA, RSI, MACD, and Bollinger Bands. The system is designed to assist users in making more objective trading decisions based on historical data. This study applies weighted indicator combinations ranging from 0 to 4, resulting in 625 weight combinations evaluated thru backtesting using ROI, Win Rate, and MDD metrics. Based on the test results, the weighted indicator combination outperformed single indicators by achieving an ROI increase of up to 2222.35% on the SOLUSDT asset. In addition, the approach improved signal accuracy, as shown by the increase in Win Rate on ETHUSDT from 35.21% to 47.28% and on SOLUSDT from 32.84% to 58.11%. Furthermore, the method was effective in mitigating risk, indicated by the reduction of MDD on ETHUSDT from 50.04% to 41.35%. The system was successfully implemented as a web-based application integrated with Telegram notifications to deliver analysis results to users.
PERBANDINGAN OPTIMASI PSO BAYESIAN DAN OPTUNA PADA MODEL GRU UNTUK PREDIKSI HARGA AYAM JAWA TIMUR Choirun Nisa; Rizky Parlika; M. Muharrom Al Haromainy
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 8 No 2 (2026): EDISI 28
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v8i2.7462

Abstract

Studi ini bertujuan untuk menganalisis dan membandingkan performa metode optimasi hyperparameter, yaitu Particle Swarm Optimization (PSO), Bayesian Optimization, dan Optuna pada model Gated Recurrent Unit (GRU) dalam prediksi harga daging ayam ras pedaging di Provinsi Jawa Timur. Data yang digunakan merupakan data harian time series periode Januari 2018 hingga Januari 2026. Metode Penelitian meliputi preprocessing data, feature engineering, validasi model memakai walk-forward validation dengan pendekatan expanding window sebanyak 5 fold, serta optimasi hyperparameter pada setiap fold. Evaluasi model dilakukan memakai metrik MAE, RMSE, dan MAPE, dimana nilai evaluasi diperoleh dari rata-rata seluruh fold pengujian. Hasil penelitian memperlihatkan  seluruh metode optimasi mampu meningkatkan performa model dibandingkan GRU baseline. Model GRU dengan Bayesian Optimization menghasilkan performa terbaik dengan nilai MAE sebesar 252.30, RMSE sebesar 378.03, dan MAPE sebesar 0.74%, serta memperlihatkan tingkat stabilitas yang lebih baik dibandingkan metode lainnya. Hasil studi ini memperlihatkan  pemilihan metode optimasi hyperparameter yang tepat dapat meningkatkan akurasi dan konsistensi model prediksi harga pangan.
SISTEM KONTROL PRESENTASI REAL-TIME BERBASIS GESTUR TANGAN MENGGUNAKAN METODE LSTM PADA APLIKASI CANVA Salsa Pramudhita Agustiardani; Rizky Parlika; Budi Nugroho
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 8 No 2 (2026): EDISI 28
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v8i2.7484

Abstract

Penggunaan perangkat konvensional seperti mouse dan keyboard dalam presentasi masih memiliki keterbatasan pada interaksi tanpa sentuhan. Penelitian ini bertujuan untuk mengembangkan sistem kontrol presentasi real-time berbasis gestur tangan menggunakan metode Long Short-Term Memory (LSTM) yang diintegrasikan ke dalam aplikasi Canva. Sistem memanfaatkan MediaPipe untuk mengekstraksi 21 titik landmark tangan sebagai fitur input model klasifikasi. Untuk menjalankan perintah presentasi, terdapat empat kelas gestur yang meliputi gestur one, peace, ok, dan fist. Setiap gestur memiliki fungsi untuk melakukan kontrol presentasi seperti berpindah slide, kembali ke slide sebelumnya, mengaktifkan mode layar penuh, dan keluar dari mode layar penuh. Hasil pengujian menunjukkan model mencapai akurasi sebesar 99%, serta mampu bekerja secara konsisten pada kondisi indoor dan outdoor. Tingkat akurasi yang diperoleh menunjukkan bahwa metode LSTM memiliki performa yang optimal dalam mengenali gestur tangan secara real-time.
Co-Authors A. Kachsyfur Djasim Ilyas Paenrongi Abidin Sulaiman Abrori, Merdin Risalul Achmad Heidhar Mubarok, Achmad Heidhar Achmad Yuneda Alfajr Agussalim Ahmad Budi Trisnawan Ahmad Budi Trisnawan Ahmad Dendy Prasongko Putra Ahmad Maghfur’ Ali Akbar, Fawwaz Ali Akhlis Munazilin Akhlis Munazilin Akhlis Munazilin, Akhlis al hakim, Rais Alfajr, Achmad Yuneda Alif Ernanda Putra Alwin, Muhammad Izdihar Amir Muhammad Hakim Andreas Nugroho Sihananto Andry S, Firdaus Anggoro Cahyo Nugroho Anggreini, Diana Nur Anindya Khalisha Nurdianti Anita Nusari Ardiana Deka Maharani Ardisty Palvelus Jumala Arianto, Chakra Satrya Pradana Putra Arif Nur Cahyo Aris Pratama Arista Pratama Asif Faroqi Atmaja, Pratama Wirya Aulia N, Rayhan Auliya, Rahmat Avrie Akbar Prabowo Ayu Ithriah, Syurfah Basuki Rahmat Masdi Siduppa Benny Danendra Hadi Bima Rizqy Prasurya Bregsi Atingsari Julastri Bryan Benedict Bangun Caritta Elizabeth Chakra Satrya Pradana Putra Arianto Choirun Nisa Dandi Azaidane Devan Cakra Mudra Wijaya Devi Anugrah Putri Dewi Azizah Dhany Satya Hutama Didik U Pribadi, Didik U Dimara Kusuma Hakim Dimas Rizward Hikmah Utomo Dino Rosanilo Yuswanto Dwi Rahmadewi, Cynthia Eka Maurita Maurita Emmil Yulianto Erayanti, Aninda Elsa Fadhli Shidqi Wiratama faradilla, yolla Faris Al Fatih, Mohammad Faris Hirmar Pralas Fatwa Zuhri Diva Perdana Fedianto, Muhammad Helmi Satria Fernanda, Rifky Akhmad Fernanda, Rifky Akhmad Firmansyah, Fahrul Firza Prima Aditiawan Fitranda Ramadhana Gayuh Abdi Mahardika Hadiansyah Rachmawan Putra Haidar Ananta Kusuma Hakim, Arif Rahman Hamdi Indra Hanafi, Agus Heldian Lintang P Heri Khariono Heri Khariono Hidayat Nur Tauhid Hidayat, Mochammad Fikri Hilman Fadlilah Lesmana Humam Maulana Tsubasanofa Ramadhan Humam Maulana Tsubasanofa Ramadhan Humania B, Nobel Ilham Asy’ari Ilham Krisdianta Siregar Ilham Pradika, Sunu Ilham Setia R Isfan Rachmad Ja'far Shodiq Jerry Ramadhani Cahyas Kartini Kartini Kartini Kartini Kemal Fahreza Jibran Jibran Khariono, Heri Kholilul Rachman Nur Manab Lendy Rahmadi Lesmana, Hilman Fadlilah Lintang P, Heldian Luthfiyatul ‘Azizah M. Muharrom Al Haromainy M. Syahrul Munir, M. Syahrul M. Zaky Pria Maulana Malik, Gamar Ramadhani Maulana, Hendra Melinda Shilatil Fauziyah Merdin Risalul Abrori Miftakhoneki, Sufi Misbahul Munir Mochammad Fikri Hidayat Mochammad Zayyan Ramadhan Moh. Ainur Rofik Mohammad Idhom Muhamad Faizhal Musthafa Muhammad Agung Shobirin Muhammad Ghifari Alifian Muhammad Hakim, Amir Muhammad Helmi Satria Fedianto Muhammad Ilham Arzaki Muhammad Izdihar Alwin Muhammad Rafli Aulia Rojani Lutfi Muhammad Rizal Waskito Muhammad Romi Nasution Muhammad Suriansyah Muhammad Wifaqul Azmi Munir, M Syahrul Mustafid Mustafid Nafa Nabila El Indri Nizam, M Miftahul Nobel Humania B Nugroho, Budi Nur Manab, Kholilul Rachman Nurilhaq, Muhammad Sabilli Olivia i Anggun Permatasar Orissa, Dendy Fektor Parlika, Anjaya Perdana, Fatwa Zuhri Diva Prabowo, Avrie Akbar Pralas, Faris Hirmar Prasasti Karunia Farista Ananto Prasasti Karunia Farista Ananto Prayoga, Julio Cahya Pribadi, Didik U Pribadi, Didik Utomo Putra Dwi Wira Gardha Yuniahans Putra, Ahmad Dendy Prasongko Putra, Alif Ernanda Putra, Hadiansyah Rachmawan Qonitah Jihan Nabilah R Rizal Isnanto R. Rizal Isnanto Rachman N.M., Kholilul Rahmat Auliya Ramadhan, Ferry Dzaky Rayhan Aulia N Rayhan Rizal Mahendra Rayhan Saneval Arhinza Rendra Ardika Retno Mumpuni Reza Achmad Gallanta Rifardi Taufiq Yufananda Rifky Akhmad Fernanda Rifky Akhmad Fernanda Riky Hermawan Riky Hermawan Rivaldy Setiawan, Rivaldy Rizky Ananda Ramadhan Rizqy Khoirul Waritsin Roiqoh, Aprinia Salsabila S. Gama, Nemicio de Salsa Pramudhita Agustiardani Sarirotul Latifah Setia R, Ilham Setiawan, Rienaldi Shahab, Muhammad Syaugi Shodiq, Ja'far Siregar, Ilham Krisdianta Steffanuel Pranatalie Krispriyanto Stevanus Frangky Handono Sunu Ilham Pradika Suriansyah, Muhammad Susy Rahmawati Syafriansyah, Muhammad Syahrul Munir Syaiful Hidayat, Syaiful Syalum Marsya Pruista Tasya Ardhian Nisaa’ Tegar Satria Kirana Trisnawan, Ahmad Budi Ummam, Mohamad Arel Intidhofatul Vinza Hedi Satria Vito Fausta Majid Wahyu Syaifullah Jauharis Saputra Wahyudi Wahyudi Waskito, Muhammad Rizal Wigananda Firdaus Putra Aditya Wijaya, Devan Cakra Mudra Wijaya, Devan Cakra Mudra Yoga Ari Tofan Yudhistira Nanda Kumala Yulianto, Emmil