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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 Jurnal Sisfokom (Sistem Informasi dan Komputer) 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) Jurnal Informatika Teknologi dan Sains (Jinteks) Nusantara Journal of Computers and its Applications Jurnal Informatika Polinema (JIP) Prosiding Seminar Nasional Ilmu Sosial dan Teknologi (SNISTEK) JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Jurnal Komtika (Komputasi dan Informatika) Jurnal Serumpun Teknik Informatika
Parlika, Rizky
Department Of Informatics System, Faculty Of Computer Science, Universitas Pembangunan Nasional “Veteran” Surabaya, East Java
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Ethereum-Based Escrow System to Reduce the Risk of Peer-to-Peer Payment Abuse Kumala, Yudhistira Nanda; Parlika, Rizky; Maulana, Hendra
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3667

Abstract

Peer-to-peer (P2P) payments facilitate rapid direct transactions but are frequently compromised by trust asymmetry, leading to substantial risks of non-delivery or non-payment. This study addresses these vulnerabilities by introducing a lightweight, deterministic escrow mechanism based on Ethereum smart contracts, specifically designed to bridge the regulatory gap in consumer protection. Unlike conventional escrow systems that rely on costly human intermediaries or complex decentralized autonomous organization (DAO) structures, the proposed "FairPay" model advances the state-of-the-art by offering a streamlined five-state lifecycle architecture comprising Created, Funded, WorkSubmitted, Released, and Refunded stages. The research prioritizes an analytical problem-solution flow, focusing on a state-machine design that enforces automated role-based restrictions. Methodological evaluation conducted on the Ethereum Sepolia testnet demonstrates a 100% functional success rate across all unit test scenarios. Furthermore, gas cost analysis reveals that the system is economically viable for granular transactions, with core operational functions maintaining a low execution overhead. Beyond operational success, the primary scholarly contribution lies in the design insight of balancing high cryptographic security with granular transaction accessibility, providing a scalable framework for the modern digital economy. However, the system currently assumes binary participant decisions for work verification, representing a transparency-oriented limitation in handling highly subjective service deliverables. Ultimately, this study demonstrates that algorithmic trust, mediated through a simplified state-machine, offers a more efficient and transparent alternative to existing high-complexity blockchain models, effectively resolving the tension between decentralized security and practical usability in P2P digital interactions.
Perbandingan Fuzzy Mamdani dan Sugeno dalam Optimasi Trading Bitcoin Berbasis Indikator Teknikal Dwi Rahmadewi, Cynthia; Parlika, Rizky; Maulana, Hendra
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.v16i1.11235

Abstract

This study compares Mamdani and Sugeno fuzzy inference systems for Bitcoin trading using historical BTC/USDT data. In highly volatile and non-linear cryptocurrency markets, especially during bear markets, conventional methods struggle to interpret ambiguous signals, making fuzzy logic suitable for adaptive decision-making. The dataset was collected from the Binance API for the period 20 November 2021 to 31 December 2022 and consists of 9,746 candlestick records. This period corresponds to a bear market phase, characterized by a significant downward trend in Bitcoin prices, which provides a challenging environment for evaluating trading strategies. Four technical indicators, Bollinger Bands, RSI, ADX, and PSAR, were used as input variables. The data were split into 70% training and 30% testing using a time-based approach. Performance evaluation was conducted through long-only backtesting using Total Profit, Win Rate, Maximum Drawdown, Sharpe Ratio, and Sortino Ratio. The results show that Mamdani achieved better profitability than Sugeno, with total profit of -34.17% on training data and -2.45% on testing data, while Sugeno produced -53.91% and -3.04%, respectively. Although both methods resulted in negative returns due to the bearish market conditions, their performance was better than the buy-and-hold strategy, which recorded losses of -65.78% on training data and -17.49% on testing data. This indicates that both fuzzy approaches were effective in reducing losses and improving risk management under extreme market conditions. However, Sugeno showed better risk control on testing data with a lower maximum drawdown of 18.72% compared to 25.01% for Mamdani. Overall, Mamdani is more suitable for return-oriented strategies, while Sugeno is more appropriate for risk management under bearish conditions.
Klasifikasi Rating Film Berdasarkan Genre Menggunakan XGBoost dan LightGBM serta Analisis SHAP Roiqoh, Aprinia Salsabila; Parlika, Rizky; Aditiawan, Firza Prima
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.v16i1.11273

Abstract

Movie rating is often used as an indicator of film quality and audience satisfaction. With the large availability of movie data on online platforms, machine learning techniques can be used to analyze the relationship between film characteristics and rating patterns. One important attribute that can influence movie ratings is genre. This study aims to classify movie ratings based on genre using the XGBoost and LightGBM algorithms and to analyze the contribution of each genre using SHAP (SHapley Additive Explanations). Movie data were collected from The Movie Database (TMDB) API and processed through several preprocessing stages including genre separation, data cleaning, one-hot encoding, and rating categorization. The dataset was then divided into training and testing data with a ratio of 70:30. The classification results show that XGBoost achieved an accuracy of 0.53, slightly higher than LightGBM with an accuracy of 0.52. Further analysis using SHAP indicates that genres such as Horror, Drama, Action, and Comedy have the highest global importance in the classification model. Meanwhile, the analysis of high-rating class predictions shows that Drama has the largest contribution to predicting movies with high ratings. The findings indicate that movie genres have a measurable influence on rating classification, although the importance of genres in the machine learning model does not always align with their average rating values.
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.
Co-Authors Abidin Sulaiman Abrori, Merdin Risalul Achmad Heidhar Mubarok, Achmad Heidhar Achmad Yuneda Alfajr Agung Wibowo, Mochamad Ahmad Budi Trisnawan Ahmad Dendy Prasongko Putra Ahmad Maghfur’ Ali Akbar, Fawwaz Ali 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 Anita Nusari Aqila Murodah Sutanto Ardiana Deka Maharani Ardika, Rendra Ardisty Palvelus Jumala Arianto, Chakra Satrya Pradana Putra 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 Budi Nugroho Budi Nugroho 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 Didik Utomo Pribadi Dimas Rizward Hikmah Utomo Dino Rosanilo Yuswanto Dwi Rahmadewi, Cynthia Eka Maurita Maurita Emmil Yulianto Erayanti, Aninda Elsa Fadhli Shidqi Wiratama faradilla, yolla 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 Hermawan, Riky 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 Kumala, Yudhistira Nanda 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 Munir, M Syahrul Mustafid Mustafid Nafa Nabila El Indri Nizam, M Miftahul Nobel Humania B Nur Cahyo, Arif 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 Prayoga, Julio Cahya Pribadi, Didik U 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 Retno Mumpuni Reza Achmad Gallanta Rifardi Taufiq Yufananda Rifky Akhmad Fernanda Rifky Akhmad Fernanda Riky Hermawan Rivaldy Setiawan, Rivaldy Rizky Ananda Ramadhan Rizqy Khoirul Waritsin Roiqoh, Aprinia Salsabila S. Gama, Nemicio de Salsa Pramudhita Agustiardani Sarirotul Latifah Satria, Vinza Hedi 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 Syalum Marsya Pruista Tasya Ardhian Nisaa’ Tegar Satria Kirana Teguh Sutanto Ummam, Mohamad Arel Intidhofatul Vito Fausta Majid Wahyu Syaifullah Jauharis Saputra Waskito, Muhammad Rizal Wifaqul Azmi, Muhammad Wijaya, Devan Cakra Mudra Wijaya, Devan Cakra Mudra Yoga Ari Tofan Yulianto, Emmil