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Jurnal Informatika: Jurnal Pengembangan IT
Published by Politeknik Harapan Bersama Tegal
ISSN : 24775126     EISSN : 25489356     DOI : https://doi.org/10.30591
Core Subject : Science,
Computer Science & IT
The scope encompasses the Informatics Engineering, Computer Engineering and information Systems., but not limited to, the following scope: 1. Information Systems Information management e-Government E-business and e-Commerce Spatial Information Systems Geographical Information Systems IT Governance and Audits IT Service Management IT Project Management Information System Development Research Methods of Information Systems Software Quality Assurance 2. Computer Engineering Intelligent Systems Network Protocol and Management Robotic Computer Security Information Security and Privacy Information Forensics Network Security Protection Systems 3. Informatics Engineering Software Engineering Soft Computing Data Mining Information Retrieval Multimedia Technology Mobile Computing Artificial Intelligence Games Programming Computer Vision Image Processing, Embedded System Augmented/ Virtual Reality Image Processing Speech Recognition
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 466 Documents
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Perancangan Manajemen Risiko Keamanan Informasi Menggunakan SNI ISO/IEC 27005:2022 pada Aplikasi One Data Instansi XYZ Yudhi Prasetya
Jurnal Informatika: Jurnal Pengembangan IT Vol 11, No 2 (2026)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v11i2.10391

Abstract

The One Data application at XYZ Agency is a strategic data portal that supports bureaucratic reform and civil service governance. The high strategic value of the managed data has implications for increasing information security risks. This study aims to design information security risk management in the One Data Application at XYZ Agency by referring to SNI ISO/IEC 27005:2022, prioritizing risk treatment, and validating the design through control alignment with the IKASANDI guidelines. The research methods include inventorying application-related assets, identifying threats and vulnerabilities, formulating risk scenarios, and analyzing and evaluating risks using consequence-likelihood criteria and a 5x5 risk matrix referring to PermenPANRB Number 43 of 2021. The design results produce a risk register covering 30 assets, 21 types of threats, and 61 risk scenarios, consisting of 33 risks requiring mitigation and 28 risks in the acceptable category. High-priority risks primarily relate to service availability, dependence on supporting infrastructure, and human factors, including potential insider threats and limited personnel availability. The risk treatment recommendations are mapped against SNI ISO/IEC 27002:2022 controls and aligned with IKASANDI controls; design validation is demonstrated by an increase in the IKASANDI score from 1,65 to 2,24. The proposed risk treatment plan also targets a decrease in the average risk score from 12,07 to 6,31, placing all scenarios in the acceptance category. The study concludes that the implementation of SNI ISO/IEC 27005:2022, validated through an increase in the IKASANDI score, results in a structured risk management design, and supports continuous monitoring and improvement of the information security management system in the XYZ Agency's One Data Application.
FLOOVIA: Aplikasi Cerdas untuk Monitoring dan Peringatan Banjir Jalanan Berbasis Kecerdasan Buatan dan IoT Vera Nataria
Jurnal Informatika: Jurnal Pengembangan IT Vol 11, No 2 (2026)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v11i2.10393

Abstract

Flooding is a frequent natural disaster in Indonesia and has a significant impact on community mobility and daily activities. One of the main challenges in post-flood management is the limited availability of accurate and real-time information regarding water level conditions and flood recession time. This issue is particularly evident in flood-prone areas of Medan City. This study aims to design and develop an intelligent system based on the Internet of Things (IoT) and Artificial Intelligence (AI), implemented in a mobile application to support flood disaster mitigation. The proposed system utilizes an IoT-based barometric pressure sensor to acquire real-time water level data. The collected data are processed using a Long Short-Term Memory (LSTM) model to predict flood recession time. In addition, the application provides safe alternative route recommendations through Google Maps integration. The results indicate that the system is capable of delivering real-time water level information, producing flood recession time predictions with a coefficient of determination (R2) of 0,766, which demonstrates a good level of accuracy, and recommending safe routes to support community mobility during flood events. This system demonstrates strong potential for further development as a digital decision-support tool for flood disaster mitigation.
Implementasi Trading Strategy pada Saham Sektor Energi dengan Support Vector Machine dan Indikator Teknikal Giovanka Steviano Harry Premono; Nugroho Agus Haryono; Yuan Lukito
Jurnal Informatika: Jurnal Pengembangan IT Vol 11, No 2 (2026)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v11i2.10379

Abstract

The energy sector in the Indonesian capital market is characterized by high volatility, which is sensitive to external factors. This sensitivity leads to complexity in investment decision-making and trader emotional bias. This study employs a Support Vector Machine (SVM)-based trading strategy that incorporates technical indicators, such as Bollinger Bands, the Stochastic Oscillator, On-Balance Volume, and the Average Directional Index, to generate objective transaction signals for 14 energy sector stocks. Historical data from 2015 to 2025 was used, and three kernel types (RBF, polynomial, and sigmoid) were optimized through grid search. The evaluation used classification metrics and backtesting with an initial capital of Rp 100 million. The results showed F1 scores ranging from 35.83% to 47.86%. DEWA achieved the best performance with an accuracy of 66.67% and an F1 score of 47.86%. Backtesting yielded positive returns for 71.4% of stocks, with an average return of 26.85%. RAJA achieved optimal performance, with a 158.97% return and a Sharpe ratio of 1.48, outperforming the buy-and-hold strategy by 37.47%. The main advantage lies in superior risk management, with an average drawdown of -10.64%, compared to the buy-and-hold strategy -48.91%. This results in a 76.1% reduction in risk. The SVM strategy proved effective for low-risk tolerance investors but underperforms during periods of extreme bullish momentum.
Analisis Sentimen Kebijakan Makan Bergizi Gratis pada Media Sosial X Menggunakan IndoBERT Muhamad Fahmi; Lathifah Alfat
Jurnal Informatika: Jurnal Pengembangan IT Vol 11, No 2 (2026)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v11i2.10364

Abstract

Abstract – The Free Nutritious Meals policy introduced by the government has garnered mixed reactions from the public. While some members of the public view it as a positive step toward improving children’s nutritional well-being, others have voiced concerns regarding its fiscal impact and implementation challenges on the ground. This debate is actively taking place on the social media platform X, making it a rich source of large-scale data for analysis. This study aims to classify public sentiment toward the policy in order to comprehensively map citizens’ responses. The methodology involves collecting 17,752 text data points from the X platform, which undergo preprocessing stages including data cleaning and text normalization. Subsequently, the data was classified into positive, negative, and neutral sentiment classes using the IndoBERT (Bidirectional Encoder Representations from Transformers) deep learning model, which excels at capturing semantic context. Test results show that the IndoBERT model is capable of performing classification well, as evidenced by metrics of 82% Accuracy, 81% Precision, 80% Recall, and an F1-Score of 80%. The majority of netizen discourse tends to fall into the negative category (39.3%), dominated by concerns regarding the allocation of state funding, followed by neutral (34.7%) and positive (26.0%) sentiments. In conclusion, this IndoBERT-based sentiment analysis has proven effective in capturing public opinion, thereby providing empirical insights for the government in developing policy communication strategies.
Centralized Orchestration for Agent-Based Host Intrusion Detection System with Threat Intelligence Gede Ananda; Sawali Wahyu; Muhamad Hadi Arfian; Nugroho Budhi Santoso
Jurnal Informatika: Jurnal Pengembangan IT Vol 11, No 2 (2026)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v11i2.10390

Abstract

Cyber threats such as malware injection, web shell exploitation, phishing, and lateral movement increasingly challenge host-level security mechanisms. Conventional Host-Based Intrusion Detection Systems (HIDS) are commonly deployed in stand-alone configurations, resulting in limited cross-host visibility, delayed incident response, and lack of integration with external threat intelligence. This study proposes an agent-based HIDS architecture with centralized orchestration and real-time threat intelligence integration to improve detection accuracy and response efficiency. The system is developed using an experimental approach based on the NIST SP 800-61 Rev.2 incident handling framework, covering preparation, detection and analysis, containment and recovery, and post-incident evaluation. Each host deploys a lightweight agent that monitors file system activities, generates cryptographic hash values, and sends artifact metadata to a centralized orchestration server. The server performs parallel validation using external threat intelligence services and executes automated containment actions. Experimental results in a multi-host virtual environment show a False Positive Rate (FPR) of 3.2%, Mean Time to Detect (MTTD) of 4.8 seconds, and Mean Time to Respond (MTTR) of 6.5 seconds, with a 38% improvement compared to manual monitoring. These findings indicate that centralized orchestration combined with threat intelligence integration enhances detection precision, scalability, and incident response effectiveness in HIDS
ANALISIS HOLISTIK KEPUASAN PENGGUNA LAYANAN HELPDESK BKKBN DIY MENGGUNAKAN KERANGKA CUSTOMER SATISFACTION INDEKS, IMPORTANCE PERFORMANCE ANALYSIS, DAN COBIT 2019 M. Irfan Munawir Budisantoso
Jurnal Informatika: Jurnal Pengembangan IT Vol 11, No 2 (2026)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v11i2.10225

Abstract

Website dan layanan helpdesk digital telah bertransformasi menjadi pilar utama dalam strategi komunikasi dan pelayanan publik bagi organisasi pemerintah di Indonesia. Dalam konteks Perwakilan Badan Kependudukan dan Keluarga Berencana Nasional Daerah Istimewa Yogyakarta (BKKBN DIY), layanan helpdesk tidak hanya berfungsi sebagai kanal informasi, tetapi juga sebagai sarana transparansi dan akuntabilitas dalam mendukung program kependudukan dan pembangunan keluarga. Namun, pengelolaan layanan TI yang sering kali bersifat ad-hoc tanpa landasan tata kelola yang kuat berisiko lebih rentan menimbulkan gangguan layanan, kerentanan keamanan, dan ketidakpuasan pengguna. Penelitian ini bertujuan untuk mengevaluasi secara menyeluruh efektivitas layanan Helpdesk BKKBN DIY dengan mengintegrasikan perspektif tata kelola internal melalui kerangka kerja COBIT 2019 dan perspektif kepuasan eksternal menggunakan metode Customer Satisfaction Index (CSI) serta Importance Performance Analysis (IPA). Pendekatan yang digunakan adalah kombinasi studi dokumentasi, wawancara mendalam, observasi teknis, dan survei kuantitatif terhadap 463 responden yang mencakup pegawai sebagai pengguna internal, petugas lapangan, mitra kerja, kader, dan masyarakat umum sebagai pengguna eksternal. Evaluasi tata kelola difokuskan pada tujuh objektif prioritas: APO13, BAI06, DSS01, DSS02, DSS03, DSS04, dan MEA01. Temuan audit menunjukkan bahwa tingkat kapabilitas tata kelola saat ini berada pada rata-rata Level 2 (Managed), sementara target organisasi ditetapkan pada Level 4 (Predictable). Disisi lain, analisis kepuasan menunjukkan nilai CSI sebesar 79,25%, yang menandakan pengguna merasa puas, meskipun terdapat atribut kritis di Kuadran I IPA terkait kecepatan penyelesaian layanan. Kesenjangan antara kepuasan pengguna yang cukup tinggi dengan kematangan tata kelola yang masih rendah mengindikasikan adanya ketergantungan pada inisiatif personal staf teknis yang belum terstandarisasi. Penelitian ini merekomendasikan pembakuan standar operasional prosedur (SOP), penerapan sistem ticketing, penguatan kontrol keamanan melalui Multi-Factor Authentication, dan penyusunan Disaster Recovery Plan yang teruji untuk menjamin keberlanjutan layanan jangka panjang.

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