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Jurnal Informatika Universitas Pamulang
Published by Universitas Pamulang
ISSN : 25411004     EISSN : 26224615     DOI : https://doi.org/10.32493
Core Subject : Science,
Computer Science & IT
Jurnal Informatika Universitas Pamulang is a periodical scientific journal that contains research results in the field of computer science from all aspects of theory, practice and application. Papers can be in the form of technical papers or surveys of recent developments research (state-of-the-art). Topics cover the following areas (but are not limited to): Artificial Intelligence Big Data Business Intelligence Data mining Decision Support Systems Intelligent Systems Machine Learning Network and Computer Security Optimization Pattern Recognition Soft Computing Software Engineering
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 630 Documents
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Penerapan Metode Preference Selection Index untuk Penerima Program Keluarga Harapan di Desa Gunungsari Kabupaten Pandeglang Hays, Riyan Naufal; Siswanto; Djaksana, Yan Mitha
Jurnal Informatika Universitas Pamulang Vol 10 No 2 (2025): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jiup.v10i2.49023

Abstract

The Program Keluarga Harapan (PKH) aims to alleviate poverty and improve access to education and healthcare for underprivileged families in Indonesia. In Gunungsari Village, Mandalawangi Subdistrict, Pandeglang Regency, where most residents are low-income farmers and breeders, PKH faces challenges in accurately identifying eligible recipients due to the limitations of manual selection, which is prone to subjectivity and human error. This study explores the application of the Preference Selection Index (PSI) method to improve the objectivity and accuracy of beneficiary targeting. From 973 households, five were selected as a representative sample for manual validation. Twelve socio-economic indicators were used to assess eligibility. The PSI method systematically calculates preference weights across multiple criteria, including income, employment, housing, assets, and infrastructure access, generating a ranking of the most eligible candidates. The highest score obtained was 3.188, identifying Family C as the top candidate. The method showed strong agreement with expert judgment, as evidenced by a Spearman Rank Correlation of 0.9. These findings suggest that PSI enhances the fairness and efficiency of the PKH selection process and supports its digital transformation. This study offers a replicable model for improving governance and targeting in rural social assistance programs.
Evaluasi Modern Model Pembelajaran Mesin pada Dataset SEERA untuk Estimasi Upaya Perangkat Lunak Nufus, Fina Sifaul; Subekti, Agus
Jurnal Informatika Universitas Pamulang Vol 10 No 2 (2025): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jiup.v10i2.51687

Abstract

Estimating software development effort is crucial in project planning and management, especially in resource-constrained environments. This study piloted four modern regression models: Random Forest, Support Vector Machine (SVM), Lasso Regression, and Ridge Regression, chosen because they represent different approaches: ensemble, margin-based, and L1 and L2 regularization. Experiments were conducted using the SEERA (Software Effort Estimation with Real Attributes) dataset, consisting of 99 entries, with a modern Python pipeline including preprocessing, feature selection, Z-score normalization, data splitting (80:20), and cross-validation (5-Fold Cross Validation). Models were evaluated using MAE, RMSE, and R². Results showed that Random Forest outperformed both the 80:20 split (R² = 0.740, MAE = 3981.53) and K-Fold (R² = 0.715, MAE = 3152.03), while SVM performed the worst with a negative R². Lasso and Ridge are only competitive at 80:20 but significantly decrease on K-Fold, indicating less stability. This research contributes by providing an in-depth evaluation based on a single dataset and demonstrating that the transparent Python pipeline based on K-Fold can be replicated to improve estimation accuracy. Future research could be conducted using advanced ensemble methods (e.g., XGBoost) and evaluated on larger datasets to generalize the results.
Rancang Bangun Sistem Informasi E-Konseling Berbasis Website melalui Rapid Applications Development (RAD) (Studi Kasus SCU Universitas Nusa Putra) Fergina, Anggun; Sarah Ayu Rahmawati; Any Elvia Jakfar
Jurnal Informatika Universitas Pamulang Vol 10 No 3 (2025): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jiup.v10i3.49268

Abstract

Student mental health is an important aspect that needs special attention, especially amid academic pressures and complex social challenges. At Nusa Putra University, counseling services are still conducted manually using Google Forms, which causes various obstacles such as overlapping schedules, delays in processing, and low student participation. This condition risks reducing the effectiveness of services, prolonging case handling times, and discouraging students from utilizing counseling services. Therefore, a digital system is needed that can overcome these problems in a more efficient and structured manner. This study aims to develop a website-based e-counseling system to improve the efficiency, accessibility, and quality of counseling services. The Rapid Application Development (RAD) method was used in the development of the system with an iterative and participatory approach. The system is equipped with an automatic scheduling feature based on the FIFO (First In, First Out) algorithm for more orderly queue management and Websocket integration to support real-time online counseling sessions. The results of black-box testing with 10 scenarios showed 100% success in all main functions. In addition, beta testing involving 11 respondents (1 counselor and 10 students) resulted in an average satisfaction rate of 89.09%, with the highest appreciation for response speed (90.90%) and feature relevance (89.09%). These findings confirm that the system not only functions well technically, but is also positively received by users because it effectively improves the efficiency, convenience, and quality of counseling services in higher education.
Implementasi Sistem Deteksi Anomali Berbasis Jaringan Menggunakan CNN dan SVM untuk Klasifikasikan Data Secara Real-time hadiyani, arief luqman; Handaga, Bana
Jurnal Informatika Universitas Pamulang Vol 10 No 2 (2025): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jiup.v10i2.52163

Abstract

The growing volume and complexity of network traffic have created new challenges in maintaining information security. Conventional signature-based intrusion detection systems are inadequate against modern threats, especially zero-day attacks that remain undocumented. Anomaly-based approaches using classical machine learning methods such as Support Vector Machine (SVM) show promise but still rely on manual feature engineering, which is time-consuming and requires expertise. This study proposes an anomaly detection system combining the automatic feature extraction capability of Convolutional Neural Network (CNN) with the strong classification performance of SVM. The NSL-KDD dataset is used for training, while real-time testing data are captured using Scapy. The system updates its analysis every five minutes, and detection results are presented as graphical reports and log tables sent to administrators via a Telegram Bot. Experimental results show that the hybrid CNN–SVM model achieves high accuracy and stable performance in real-time scenarios, contributing to more adaptive and intelligent intrusion detection.
Analisis Pola Pelanggaran Tata Tertib siswa untuk Meminimalisir Kasus Pelanggaran dengan Algoritma FP-Growth Firmansyah, Eka; Gunawan, Dedi
Jurnal Informatika Universitas Pamulang Vol 10 No 2 (2025): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jiup.v10i2.52258

Abstract

This research is motivated by the number of transactions in the last five years (2019–2023), 80% of students have a level of discipline violation, indicating the need for more strategic discipline. This study aims to analyze the systemic relationship between various types of participants to identify the causes of the problem. The method used in data mining is the FP-Growth algorithm, which is applied to 1,500 historical data points with a minimum support of 0.1 and a confidence level of 0.7. The analysis results show 15 significant pattern associations, with the strongest correlation between "Late → Not doing assignments" (confidence 0.83) and "Truancy → Smoking in school areas" (confidence 0.75, lift 2.5). This forms the basis for data-driven intervention recommendations, such as the implementation of the "Morning Check-in" program and the implementation of supervision in vulnerable areas, which will provide practical support to improve the effectiveness of school discipline management across schools.
Penerapan Metode Forward Chaining dalam Mediagnosis Penyakit pada Ternak Babi Ullu, Hevi Herlina; Tey Seran, Krisantus Jumarto
Jurnal Informatika Universitas Pamulang Vol 10 No 3 (2025): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jiup.v10i3.35317

Abstract

The The pig population in North Central Timor (TTU) Regency in 2025 reached 111,704, making pig farming one of the main sources of livelihood for the local community. However, farmers often experience substantial losses due to high livestock mortality rates during disease outbreaks. This situation is largely attributed to the limited knowledge of pig farmers regarding disease symptoms and types, as well as limited access to information on early disease management. This study aims to develop a pig disease diagnostic application capable of identifying disease types based on observable symptoms and providing recommendations for initial treatment and preventive measures. The application was developed using the Rapid Application Development (RAD) method to accelerate system design and implementation. Meanwhile, the Forward Chaining method was applied as a fact-finding technique to infer accurate conclusions regarding disease types based on symptoms. The results of this study include a web-based pig disease diagnostic application that implements symptom tracking using forward chaining, enabling farmers to independently identify pig diseases more quickly and accurately. The developed application is expected to help reduce pig mortality rates and improve the efficiency of livestock production, particularly pig farming in TTU Regency.
Analisis Gejala Penderita Stunting dengan Menggunakan Metode Analitical Herarchy Process Berikang, Reonaldy; Surya, Welong Seftian; Sorongan, Rinna Merlin; Dotulong, Fernando; Rumengan, Roles
Jurnal Informatika Universitas Pamulang Vol 10 No 3 (2025): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jiup.v10i3.49646

Abstract

Stunting in Indonesia has become a national issue that requires appropriate measures to prevent its adverse impacts on the lives of the nation’s people. Efforts to address stunting can be carried out both before and after a child is born. The purpose of this study is to analyze stunting symptoms using scientific methods to obtain more accurate results. The method used in this research is the Analytical Hierarchy Process (AHP), which consists of criteria and sub-criteria that are calculated to determine the prioritized alternative. At the end of the calculation, the results show that one alternative produces a Consistency Ratio (CR) value of ≤ 0.1, differing from the other two alternatives. This indicates that the AHP calculation was successful, and the selected alternative can be recommended as the best option for achieving the research objective. Based on these results, the researchers conclude that this method is appropriate for accurately detecting stunting symptoms.
Implementasi Sistem Pakar Diagnosa Artificial Intelligance Addcition Berbasis Web Menggunakan Metode Certainty Factor Studi Kasus HIMAGIRI UNS Riatma Putera, Bagas; Nursakinah, Badriah
Jurnal Informatika Universitas Pamulang Vol 10 No 4 (2025): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jiup.v10i4.53717

Abstract

The development of modern Artificial Intelligence (AI) technology has enhanced human interaction with intelligent systems in daily life; however, excessive use of AI can lead to AI Addiction, particularly among university students. This study aims to design and develop a web-based expert system using the Certainty Factor (CF) method to identify early symptoms of AI addiction and calculate the likelihood level of dependence based on user input. The case study was conducted on students of the Informatics Student Association (HIMAGIRI), Universitas Sebelas Maret (UNS), with symptom data obtained from the adaptation of the AI Addiction Scale (AIAS-21) and interviews with psychological experts specializing in addiction, anxiety, and mood disorders. Testing using Black Box Testing and White Box Testing demonstrated that all system functions operated properly and produced consistent diagnostic calculations. From 77 respondents, addiction tendencies were dominated by the Continued Use Despite Harm category (38%), followed by Compulsive Use/Loss of Control (33%) and Withdrawal (29%). These results indicate that the Certainty Factor method is effective in detecting AI addiction tendencies and providing relevant treatment recommendations, making this expert system a useful early detection tool as well as an educational medium to increase students’ self-awareness of their dependence on AI. Keywords: Expert System; Certainty Factor; Artificial Intelligence Addiction; Diagnosis, Web-based; Students; HIMAGIRI UNS
Pengembangan Web Manajemen Keuangan Sampah dengan Fitur Prediksi Keterlambatan Pembayaran Menggunakan Algoritma Decision Tree di Kelurahan Guwosari Syaifulloh Yusuf Fadlililah; Farida Ardiani
Jurnal Informatika Universitas Pamulang Vol 10 No 4 (2025): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jiup.v10i4.54211

Abstract

This study aims to develop a web-based waste financial management system in Guwosari Village integrated with a payment delay prediction feature. The system is designed to improve the efficiency of waste payment management that was previously handled manually. The system development employs the Waterfall method, consisting of requirements analysis, system design, implementation, and testing. The payment delay prediction model is built using the Decision Tree algorithm, utilizing customer data and transaction payment history from the last six months. The developed system supports multiple user roles, including superadmin, admin, agent, and customer, and provides features such as digital transaction recording, notifications, and automated financial reports. The evaluation results indicate that the system enhances efficiency in waste financial management and reduces the risk of recording errors. The prediction model achieves an accuracy rate of 85.06% in identifying customers who are likely to experience payment delays. In conclusion, the proposed system serves as an effective digital solution for waste financial management, although it is still limited by the use of a single algorithm and data coverage restricted to one area.
Pengembangan Aplikasi Digital UMKM Berbasis Hybrid Development dengan React Native dan Supabase Menggunakan Metode R&D Wisudawan, Ilham; Widiono, Suyud
Jurnal Informatika Universitas Pamulang Vol 10 No 4 (2025): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jiup.v10i4.54677

Abstract

Digital transformation has become a key element in enhancing the competitiveness and operational efficiency of Micro, Small, and Medium Enterprises (MSMEs). However, many MSME actors in Sleman, particularly in Minggir District, still face challenges in digitalization, such as low digital literacy, limited motivation and managerial capabilities, uneven network quality, and insufficient organizational readiness. This study aims to develop a digital MSME application based on hybrid development using React Native and Supabase as an efficient and affordable cross-platform solution. The research employed a Research and Development (R&D) method following five main stages: needs analysis, system design, implementation, testing, and evaluation. Testing of the core features—including user authentication, product management, sales transactions, and financial reporting—was conducted through 25 Black Box test cases, achieving a success rate of over 95%. Usability evaluation using the System Usability Scale (SUS) involved 50 MSME respondents, selected through purposive sampling based on business type diversity and digital experience, resulting in an average score of 84.2 (Excellent category), indicating that the application is user-friendly, efficient, and aligned with MSME operational needs. This study provides a practical contribution in the form of a prototype application that supports the digitalization process of MSMEs and a theoretical contribution to the literature on hybrid development based on Backend-as-a-Service (BaaS). The implementation results demonstrate the system’s effectiveness within the Minggir District, Sleman, with potential generalizability for application in other regions with similar conditions and MSME characteristics.

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