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Alusyanti Primawati, M.Kom
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Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Published by Universitas Indraprasta PGRI
ISSN : -     EISSN : 27158756     DOI : https://doi.org/10.30998/jrami.v7i01
Core Subject :
JRAMI merupakan media publikasi online khusus bagi mahasiswa/i baik didalam Program Studi Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Indraprasta PGRI ataupun luar institusi. Setiap mahasiswa/i yang memiliki hasil riset dari PKM (Program Kreatifitas Mahasiswa) dan atau Tugas Akhir dapat mempublikasinya dalam bentuk artikel ilmiah sehingga kontribusi dari hasil penelitian mahasiswa dapat disebarluaskan dan dimanfaatkan oleh masyarakat luas. JRAMI sejak 2020 diterbitkan sebanyak 4 kali dalam setahun yang dikelola oleh Program Studi Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Indraprasta PGRI. Fokus dan Area Jurnal: Sistem Informasi, Rekayasa Perangkat Lunak, Sistem Berbasis Pengetahuan, Sistem Pakar, E-Commerce, dan Sistem Pengambilan Keputusan.
Arjuna Subject : -
Articles 68 Documents
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Penerapan Algoritma KMP dalam Pencarian Data Sertifikasi ISO PT Era Kualitas Informasi Rossa Arganita Pradana; Achmad Sarwandianto; Ambar Tri Hapsari
Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Vol. 7 No. 02 (2026): Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Publisher : Program Studi Teknik Informatika, FTIK, Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jrami.v7i02.1174

Abstract

This research aims to address the issues occurring at PT Era Kualitas Informasi in ISO certification database management so that it can be organized neatly, systematically, quickly, and accurately in searches. In the development of this system, the researcher used the Knuth-Morris-Pratt algorithm implemented with the NetBeans IDE 8.2 software and MySQL database. The Knuth-Morris-Pratt algorithm is one of the algorithms used in string searching. This research implements the Knuth-Morris-Pratt algorithm in the string search process for ISO certification data retrieval. The research methodology used in the ISO certification data processing system includes data collection techniques such as interviews with relevant parties and documentation to obtain the necessary information. Additionally, the researchers also conducted literature research relevant to the issues of the ISO certification data search system. After conducting research, analyzing the problems, and resolving the proposed issues, the researchers concluded that the existing system is still operated using simple applications like Microsoft Office. Therefore, by building a client database system at PT Era Kualitas Informasi, it will facilitate the data entry department in carrying out its tasks.
Pengembangan Hybrid Recommender System Menggunakan Scikit-Learn dan Pandas untuk Rekomendasi Film Muhammad Fabian Hartono; Opitasari Opitasari; Ivan Firdaus
Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Vol. 7 No. 02 (2026): Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Publisher : Program Studi Teknik Informatika, FTIK, Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jrami.v7i02.1190

Abstract

The rapid growth of digital streaming services has led to an increase in the amount of available film content, creating a problem of information overload for users when selecting content that matches their preferences. Therefore, recommendation systems have become an essential solution to help users efficiently and personally discover relevant films. This study aims to develop a film recommendation system based on a hybrid recommender system by combining collaborative filtering and content-based filtering methods to improve the accuracy and diversity of recommendations. The CF method is used to leverage interaction patterns and similarities in preferences among users, while the CBF method utilizes film content features such as genre to determine item similarity. The system was implemented using the Python programming language with the scikit-learn and pandas libraries for data processing and model development. The dataset used is MovieLens 100k, consisting of 100,000 ratings from 943 users for 1,682 movies, along with movie metadata. System performance was evaluated using the mean squared error and precision@K metrics. The test results indicate that the hybrid system achieved a precision@5 value of 0.6000, indicating that 60% of the recommendations provided were relevant to user preferences. Furthermore, the hybrid approach proved to be more stable and accurate than single methods and was able to address cold-start problems and data sparsity. Thus, the developed system is capable of providing more relevant, diverse, and personalized movie recommendations. This study demonstrates that the hybrid approach is an effective solution for improving the quality of recommendation systems, particularly in user-data-based movie recommendation applications.  
Prediksi Risiko Stunting Prakehamilan Menggunakan Sistem Pakar Certainty Factor Berbasis Mobile Muhamad Hadi Arfian; Noviandi Noviandi; Fahmi Zain
Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Vol. 7 No. 02 (2026): Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Publisher : Program Studi Teknik Informatika, FTIK, Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jrami.v7i02.1191

Abstract

Stunting still a serious public health issue, and the risk often originates as early as the pre-prenant phase. However, digital solutions that specifically integrate individual risk screening, expert-based reasoning, and mobile access for expectant mothers are still limited, which hinders the ability to effectively address the stunting risk during the critical pre-prenant phase. This study aims to develop a Certainty Factor-based expert system mobile application capable of independently, quickly, and educationally predicting the risk of stunting during the pre-prenant phase. This study employs a design and development research approach encompassing needs identification, knowledge acquisition, the formulation of a knowledge base and inference rules, system design, and mobile application implementation. The knowledge base was designed for three user categories: women in the pre-prenant stage, women who have given birth, and 19-year-old adolescents. Evaluation results showed that system performance varied across groups, with an accuracy of 0.67 for the adolescent and postpartum groups and 0.52 for the pre-prenant group. The precision and recall values also show a similar pattern, indicating that the system performs better in groups with more structured risk characteristics than in groups with more complex risk determinants. These findings suggest that the integration of a CF-based expert system with a mobile platform is not only capable of supporting the early detection of stunting risk but also provides an adaptive approach to differences in user characteristics, so that it has potential to increase the effectiveness of life-cycle-based screening.
Penerapan Metode Indobert untuk Deteksi Berita Hoaks pada Media Digital Berbahasa Indonesia I Gede Bagus Surya Wibawa; I Nyoman Eddy Indrayana; Made Pasek Agus Ariawan
Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Vol. 7 No. 02 (2026): Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Publisher : Program Studi Teknik Informatika, FTIK, Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jrami.v7i02.1196

Abstract

This study focuses on the implementation of the IndoBERT method for detecting hoax news in Indonesian digital media and examining the model’s performance and generalization ability. The dataset consists of primary data obtained from a Kaggle dataset and secondary data collected through web scraping from various sources, which are then combined and preprocessed. The model is trained using a fine-tuning approach with variations in parameters such as learning rate, batch size, and epoch to achieve optimal results. The experimental results indicate that the best configuration is achieved at epoch 4, learning rate 5e-5, and batch size 16, producing an accuracy of 0.9868 along with the lowest validation loss. Evaluation using a confusion matrix shows a relatively low error rate for both classes. Testing on new data reveals that the model correctly classifies 26 out of 30 samples, indicating good generalization capability, although some misclassifications still occur in factual news that share similar characteristics with hoaxes.
Sistem Pendukung Keputusan untuk Pemilihan Mobil Bekas Terbaik dengan Metode AHP pada Showroom Bin Mahmoed Motor Sultan Badai Ady Dewa; Dewi Anjani; Lies Sunarmintyastuti
Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Vol. 7 No. 02 (2026): Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Publisher : Program Studi Teknik Informatika, FTIK, Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jrami.v7i02.1207

Abstract

This research aims to analyze the used car market using the Analytical Hierarchy Process method to select the best used cars at the Bin Mahmoed Motor Showroom. This study employs a literature review, interviews, and observations to collect data. The research findings indicate that the implementation of AHP in the decision support system can augment the comprehension of this methodology within the automotive sector and elevate customer satisfaction by delivering precise and customized recommendations. The system developed using HTML, CSS, JavaScript, PHP, and MySQL ensures that criteria such as price, year, fuel consumption, and capacity can be effectively integrated, thereby facilitating the process of selecting used cars more quickly and accurately.
Implementasi Steganografi dengan Metode Least Significant Bit (LSB) Untuk Penyisipan Dalam Data Gaji pada PT Nusa Network Pratama Freddi Moriston Alfa Doli; Lukman Lukman; Meri Chrismes Aruan
Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Vol. 7 No. 02 (2026): Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Publisher : Program Studi Teknik Informatika, FTIK, Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jrami.v7i02.1247

Abstract

This research was conducted with the aim of enhancing information security for employee salary data at PT Nusa Network Pratama through the application of steganography methods. Given the importance of salary confidentiality as part of the company’s sensitive information, a system is needed that can hide this data without being detected visually or digitally by unauthorised parties. The method used in this study is Least Significant Bit (LSB)-based steganography, a data-embedding technique that replaces the least significant bit of each pixel in a digital image. This approach was chosen for its ability to embed data without significantly affecting the visual quality of the image. The implementation process involved testing data embedding and extraction to ensure that salary data could be hidden and retrieved with high accuracy. The results of the study indicate that the LSB method can be effectively used to embed salary data into images without compromising the visual appearance of the image. The embedded data can be extracted with a 100% success rate, without any damage to the original data or the image file. Thus, the implementation of LSB steganography has proven to be feasible and secure as an alternative for distributing salary data internally within a corporate environment.
Sistem Pendukung Keputusan Pemilihan Murid Berprestasi Terbaik Pada SMP PGRI Surya Kencana Menggunakan Metode SAW Raihan M Rabbani; Mei Lestari; Ek Ajeng Rahmi Pinahayu
Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Vol. 7 No. 02 (2026): Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Publisher : Program Studi Teknik Informatika, FTIK, Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jrami.v7i02.1259

Abstract

This research aims to create a decision support system that can be used in selecting the best achieving students at PGRI Surya Kencana Middle School, with the hope of helping schools determine superior students objectively and accurately. The system designed uses the simple additive weighting method to process assessment data based on predetermined academic criteria. The assessment process is carried out using a computer with a web display so that it is more structured, clear and efficient. The results of this research are in the form of a sequence of outstanding students which is presented in the form of a report based on the criteria of average academic grades, attendance, attitude, discipline and activeness. So that it can be a reference for schools in making more precise and fair decisions, as well as reducing the element of subjectivity in assessing student achievement in the educational environment.
Analisis Perbandingan VPN Tunneling Pada Multi-Cloud Untuk Optimalisasi Performa dan Skalabilitas Muhammad Jundy Rabbani; Reza Maulana
Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Vol. 7 No. 02 (2026): Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Publisher : Program Studi Teknik Informatika, FTIK, Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jrami.v7i02.1260

Abstract

Multi-cloud infrastructure is increasingly being used in network service provisioning due to its ability to improve availability and reduce reliance on a single provider. However, the performance of VPN tunneling services in multi-cloud environments can vary significantly across providers due to differences in infrastructure characteristics, data centre locations, and network capacity. This study aims to compare the performance of SSH Tunneling and Xray VMess Non-TLS across five cloud providers, including DigitalOcean, UCloud Global, Biznet GioCloud, PT Media Antar Nusa, and CV Atha Media Prima. The method used was a comparative experiment with quantitative descriptive analysis, measuring four key metrics: latency, jitter, download throughput, and upload throughput, with each scenario repeated three times. The results show that Xray VMess Non-TLS outperforms in latency and upload throughput, with Biznet GioCloud recording the lowest latency at 31.30 ms and the most stable jitter at 7.00 ms, while PT Media Antar Nusa recorded the highest upload throughput at 62.60 Mbps. Conversely, SSH Tunneling demonstrated superiority in several download throughput scenarios, with PT Media Antar Nusa recording the highest value of 45.20 Mbps. These findings indicate that the selection of protocols and cloud providers should be tailored to the specific needs of the workload, and a multi-cloud approach offers significant flexibility in optimising VPN tunneling performance.
Peningkatan Akurasi Deteksi DDoS SDN Menggunakan Algoritma Random Forest Berbasis Gain Ratio Reza Pahlevi; Latifah Nur Zam Zam; Imelda Imelda
Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Vol. 7 No. 03 (2026): Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Publisher : Program Studi Teknik Informatika, FTIK, Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jrami.v7i03.1288

Abstract

The development of Software-Defined Networking technology offers high flexibility in network management but also introduces security vulnerabilities to Distributed Denial of Service attacks. These attacks can paralyze the SDN controller through packet flooding, leading to a drastic decline in network performance. This research aims to enhance the accuracy of DDoS attack detection in an SDN architecture based on the Ryu Controller with the OpenFlow v1.3 protocol by implementing the Random Forest algorithm optimized with Gain Ratio feature selection. The novelty of this study lies in the use of a primary dataset collected through a self-developed SDN testbed using Mininet with a Modified Tree topology to generate more realistic attack scenarios. The Gain Ratio method is employed to reduce data dimensionality by selecting the most relevant features from OpenFlow network traffic, thereby accelerating processing time and minimizing detection error rates. The experimental results demonstrate that the combination of Random Forest and Gain Ratio achieved a detection accuracy of 99.84% in a controlled testbed environment. This study indicates that the integration of Random Forest and Gain Ratio provides higher accuracy compared to the standard algorithm. The use of Gain Ratio feature selection is proven to optimize both the accuracy and efficiency of the Random Forest algorithm in DDoS detection
Tinjauan Literatur Terhadap Tantangan Etika dalam Penerapan Kecerdasan Buatan di Kewirausahaan Nurfidah Dwitiyanti; Dewi Anjani; Yusuf Kurnia; Fauzi; Yan Everhard Riwurohi
Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Vol. 7 No. 03 (2026): Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Publisher : Program Studi Teknik Informatika, FTIK, Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jrami.v7i03.1306

Abstract

This Systematic Literature Review aims to identify and analyze ethical challenges arising from the implementation of artificial intelligence (AI) in entrepreneurship. The study employed the PICOC framework and PRISMA 2020 protocol for conducting systematic searches across Scopus and Google Scholar databases covering 2021–2026.  From 430 identified articles, 43 articles met the stringent selection criteria and  quality assessment standards and were included in the analysis. The findings reveal  that principal ethical challenges encompass algorithmic bias, lack of transparency, system reliability, and accountability gaps in  AI-based decision-making. The FAIR principles (Fairness, Accountability,  Interpretability, Responsibility) emerged as a critical and comprehensive framework  for advancing responsible AI adoption in business ecosystems. This research provides actionable recommendations for entrepreneurs, policymakers, and researchers to develop fair and sustainable technology environments.

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