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Muhammad Wali
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International Journal Software Engineering and Computer Science (IJSECS)
Published by Lembaga Komunitas Informasi Teknologi Aceh
ISSN : 27764869     EISSN : 27763242     DOI : https://doi.org/10.35870/ijsecs
Core Subject : Science,
Computer Science & IT
IJSECS is committed to bridge the theory and practice of information technology and computer science. From innovative ideas to specific algorithms and full system implementations, IJSECS publishes original, peer-reviewed, and high quality articles in the areas of information technology and computer science. IJSECS is a well-indexed scholarly journal and is indispensable reading and references for people working at the cutting edge of information technology and computer science applications..
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 535 Documents
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The Living Citadel: A Generative Framework for Continuous Threat Sensing, Adaptive Enterprise Architecture Hardening, and Perpetual Business Risk-Security Alignment Simon Suwanzy Dzreke; Semefa Elikplim Dzreke
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 2 (2026): AUGUST 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i2.7478

Abstract

Static Enterprise Architecture frameworks, dependent on infrequent security evaluations, create a significant vulnerability known as the "Periodic Architecture Review Trap," wherein defenses deteriorate and threats advance during the intervals between assessments. This research sought to establish and present a conceptual framework for evolving business security from a static, point-in-time condition into a perpetually adaptive system. The research employed a design science approach to develop the Living Citadel (LC) framework, a generative system grounded in continual adaptation. The framework incorporated five fundamental components: ongoing threat and asset detection; generative artificial intelligence for creating new attack scenarios; adaptive risk exposure recalibration; autonomous architecture fortification through reinforcement learning; and a security ledger that ensures integrity. The findings depict the Living Citadel as a comprehensive theoretical framework that facilitates an ongoing cycle of sensing, synthesis, and self-hardening, thereby effectively addressing the security deficiencies of conventional methods. The study found that the framework enables a transition from a static to a dynamic security architecture, reorienting security governance from periodic compliance to continuous, autonomous resilience and real-time risk-security alignment.
Nationwide PM2.5 Concentration Prediction in Indonesia Using GRU, GRU-Attention, and BiGRU-Attention Models with Sentinel-5P and ERA5-Land Data Lina Adrianti; Tukiyat Tukiyat; Makhsun Makhsun; Tri Ubaya
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 2 (2026): AUGUST 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i2.7488

Abstract

Fine particulate matter (PM2.5) pollution has become a serious public health and environmental concern in Indonesia, yet ground-based monitoring stations remain limited and unevenly distributed across the archipelago, restricting comprehensive spatial assessment of pollutant concentrations. This study aimed to develop and comparatively evaluate three deep learning architectures, namely Gated Recurrent Unit (GRU), GRU with Additive Attention (GRU-Attention), and Bidirectional GRU with Additive Attention (BiGRU-Attention), for predicting daily PM2.5 concentrations in Indonesia by integrating Sentinel-5P satellite atmospheric chemistry products and ERA5-Land meteorological reanalysis data. The dataset combined PM2.5 ground-truth measurements from 26 BMKG monitoring stations covering the period 2020–2025, five Sentinel-5P pollutant variables and four ERA5-Land meteorological variables, producing 35,842 cleaned observations and seventeen engineered features. All variables were spatially and temporally aligned, normalized using RobustScaler with log1p target transformation, and reshaped into seven-day sequences using a stratified-station train, validation, and test split with proportions of 70%, 15%, and 15%. The results showed that BiGRU-Attention achieved the best performance with R² of 0.8302, RMSE of 7.4720 µg/m³, MAE of 4.8368 µg/m³, and MAPE of 26.7009%, outperforming GRU-Attention and the baseline GRU. This MAPE is higher than typical single-city PM2.5 models but is consistent with national-scale studies, where low-concentration observations inflate percentage-based errors. The best model was subsequently applied to produce a national daily PM2.5 distribution map, which can help identify regional PM2.5 hotspots, prioritize locations for additional monitoring infrastructure, and inform targeted air quality interventions in regions where ground-based coverage remains sparse.
Performance and Stability Evaluation of Concurrency Models for I/O-Bound Services in Golang under High-Volume Transaction Load Salsabila Yunita Sari; Felix David
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 2 (2026): AUGUST 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i2.7490

Abstract

Large-scale transaction processing in I/O-bound services can lead to performance bottlenecks and database instability, particularly on resource-constrained servers. An inappropriate concurrency strategy may cause excessive memory consumption and system failure under high workloads. This study compares the efficiency and stability of three concurrency models in Go: Sequential, Unlimited Goroutine, and Worker Pool with a Backpressure mechanism for processing 11 million transaction records against a PostgreSQL database. Testing was conducted in an isolated environment using Docker containers running on a Colima virtual machine configured with 4 CPU cores, 8 GB RAM, and a maximum of 50 database connections. Data were retrieved iteratively using Dynamic Keyset Filtering, while the batch size was calibrated through a preliminary tuning experiment. The results indicate that a batch size of 16,000 provided a balance between I/O efficiency and memory stability. The Unlimited Goroutine model failed to complete the workload due to an out-of-memory (OOM) condition. The Sequential model processed all records in 632 seconds with a throughput of 17,405 transactions per second (Tx/s). The 4-worker Worker Pool achieved the highest throughput at 21,917 Tx/s in 502 seconds, while the 8-worker Worker Pool achieved 19,755 Tx/s in 557 seconds with a 0% error rate and more consistent performance across the tested conditions. Based on the consistency of its performance, the 8-worker Worker Pool was selected as the preferred configuration in this study. These findings indicate that combining a Worker Pool with Backpressure and an appropriately calibrated batch size can improve the performance and stability of large-scale, Go-based transaction processing under the tested conditions.
Exploring the Relationship Between Coordinated Political Communication Activities and Public Sentiment on Platform X Through an Integrated Data Analytics Framework During the First 100 Days of the Prabowo Administration Fransiskus Risky Gawahi; Cinta Mugia Wening Galih; Hilda Fatihah; Maharsa Pradityatama
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 2 (2026): AUGUST 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i2.7524

Abstract

The rapid growth of social media has transformed political communication patterns in Indonesia, particularly on platform X, which has become an important medium for public opinion formation and digital political discourse. This study aims to examine the relationship between coordinated account activities and public sentiment regarding the performance of President Prabowo Subianto’s government during the first 100 working days of his administration. A quantitative data analytics approach was employed using 10,000 public posts collected from platform X between October 20, 2024, and January 29, 2025. The study combined text mining, sentiment analysis, social network analysis, and statistical analysis to identify dominant narratives, sentiment distribution, coordinated account activity patterns, and their relationship with public sentiment. The results showed that the dominant narratives focused on the Free Nutritious Meal Program, public satisfaction, and corruption eradication. Sentiment analysis indicated that 62% of the posts were classified as positive, while social network analysis identified centralized interaction patterns among accounts classified as political buzzers. Statistical analysis showed a significant positive relationship between buzzer activity and positive sentiment, with a Pearson correlation coefficient of 0.78 (p < 0.01). Linear regression analysis further indicated that posting frequency, hashtag quantity, and retweet counts collectively explained 65% of the variation in positive public sentiment. These findings indicate that coordinated communication activities were associated with the concentration of positive narratives and higher engagement levels on platform X. This study contributes to research on digital political communication and data analytics by combining text mining, sentiment analysis, social network analysis, and statistical modeling to examine coordinated political communication activities. The findings also indicate the need for stronger digital literacy and monitoring approaches to identify coordinated digital propaganda activities on social media.
Prioritizing Regional Research and Innovation Program Proposals Using a MOORA-Based Decision Support System: A Case Study of Asahan Regency Riski Ramadhan; Riki Andri Yusda; Muhammad Iqbal
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 2 (2026): AUGUST 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i2.7531

Abstract

The evaluation of regional research and innovation program proposals at the Regional Planning, Research, and Development Agency (BAPPERIDA) of Asahan Regency is still conducted manually, which may lead to subjectivity and inefficiency in the decision-making process. This study aims to develop a Decision Support System (DSS) using the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method to support the prioritization of regional research and innovation proposals. The study evaluates ten proposal alternatives based on five criteria: program relevance, innovation level, implementation potential, resource readiness, and budget feasibility. The criterion weights were determined through expert judgment involving five evaluators from BAPPERIDA. The MOORA method was applied to normalize the evaluation data, incorporate the criterion weights, and calculate the optimization value for each alternative. The results show that alternative A8, Gunting Saga (Gerakan Cegah Stunting Siap Siaga), obtained the highest optimization score of 0.2340, followed by A7 with 0.2097 and A3 with 0.2082. The results indicate that the proposed DSS can provide a structured ranking of regional research and innovation proposals based on predetermined criteria and weights. The system can support BAPPERIDA in evaluating proposals and determining priority programs in a more systematic and measurable manner.
Performance Trade-Off Between Windows 10 and Windows 11: A Comparative Analysis of CPU and Memory Behavior Using Performance Monitor and LatencyMon Ekie Revsie Akbar; Muhammad Fadhil Rachman; Tiara Fitriana; Try Mulyoto; Yan Everhard Riwurohi
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 2 (2026): AUGUST 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i2.7560

Abstract

The operating system consumes processor and memory resources and affects kernel-level responsiveness before user applications run, and these resource demands may differ across operating system versions. This study compared Windows 10 and Windows 11 under a realistic and reproducible video transcoding workload performed with HandBrake, measuring CPU utilization, hard page faults, and interrupt-to-process latency. A quantitative experimental method was used. Performance Monitor recorded CPU and memory behavior, while LatencyMon measured kernel timer, interrupt service routine, deferred procedure call, and interrupt-to-process latency. An important constraint is that the two operating systems were tested on physically different devices with processors from different generations: a 6th-generation dual-core Intel Core i7-6600U and an 11th-generation quad-core Intel Core i7-1165G7. Therefore, the measured differences cannot be attributed to the operating system version alone. Windows 11 showed more sustained CPU utilization and recorded fewer hard page faults than Windows 10 (22,480 versus 50,539), although the difference is also subject to the unequal monitoring durations. Windows 10 recorded a lower highest interrupt-to-process latency (1,147.60 µs versus 1,430.70 µs) and a lower average interrupt latency (10.10 µs versus 22.44 µs), while both systems remained within the conventional real-time suitability threshold. The findings indicate that the observed performance differences are entangled with processor generation and other hardware-related effects. Therefore, a dual-boot configuration on identical hardware is recommended in future studies to isolate the effect of the operating system version.
Comparative Analysis of LSTM and CNN–LSTM Models for Daily Air Temperature Prediction in Tanjung Priok Port Using Multivariate Meteorological Data Erian Tasa; Tukiyat Tukiyat; Yan Mitha Djaksana
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 2 (2026): AUGUST 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i2.7564

Abstract

Air temperature prediction is important for supporting weather monitoring and operational activities in port areas. Accurate temperature forecasting can support decision-making related to maritime transportation, logistics, and weather-based risk mitigation. This study compares the performance of Long Short-Term Memory (LSTM) and Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM) models for daily air temperature prediction in the Tanjung Priok Port area. The dataset consists of daily meteorological observations collected from the Tanjung Priok Maritime Meteorological Station, Indonesia, covering the period from 2000 to 2025. Eight input variables were used, including rainfall, sunshine duration, air pressure, average humidity, average wind speed, and three lagged temperature variables. Data preprocessing included data cleaning, 7-day moving average smoothing, MinMaxScaler normalization, and sequence generation using a sliding-window approach. The dataset was divided into training (70%), validation (15%), and testing (15%) sets. Model performance was evaluated using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and the coefficient of determination (R²). The results show that the LSTM model achieved the best overall performance, with an MAE of 0.1457 °C, RMSE of 0.1811 °C, MAPE of 0.5030%, and R² of 0.9423. In comparison, the CNN–LSTM model obtained an MAE of 0.2566 °C, RMSE of 0.3316 °C, MAPE of 0.8802%, and R² of 0.8065. These results indicate that the standalone LSTM model performed better than the CNN–LSTM model in predicting daily air temperature for the Tanjung Priok Port dataset.
User Satisfaction Analysis of the South Sumatra Spatial Planning Information System (SITARUNG): Generation Z Perceptions Using WebQual 4.0 and IPMA Umar Rahman Zidan; Ari Wedhasmara; Rizka Dhini Kurnia; Mira Afrina
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 2 (2026): AUGUST 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i2.7572

Abstract

Website quality is an important factor in user satisfaction with digital public services. The South Sumatra Spatial Planning Information System (SITARUNG) has not previously been evaluated from a user perspective. This study examines the effects of the WebQual 4.0 dimensions—usability, information quality, and service interaction quality—on user satisfaction with the SITARUNG website and identifies improvement priorities using Importance Performance Map Analysis (IPMA) based on the perceptions of Generation Z users. Using a quantitative survey design, data were collected from 100 Generation Z respondents through a web-based questionnaire. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4, followed by IPMA to identify indicators requiring improvement. The results show that information quality and service interaction quality significantly and positively influence user satisfaction, whereas usability does not have a significant effect. The model explains 51.6% of the variance in user satisfaction. IPMA identified five indicators in Quadrant I as improvement priorities: relevance of information to user needs (IQ3), appropriateness of information detail (IQ5), accuracy of service delivery information (SIQ1), ease of data management (SIQ2), and website processing and display speed (SIQ4). These findings indicate that information quality and service interaction quality are the primary factors associated with user satisfaction in the SITARUNG website, while usability does not show a significant effect in the present sample. Practically, the findings provide recommendations for improving spatial information services through continuous data updates, adequate GIS server infrastructure, and cross-agency data validation to support the accuracy of public spatial information.
User Experience Evaluation of the Mobile JKN Application Using the System Usability Scale (SUS) and K-Means Clustering Khaila Mukti Harahap; Abdul Halim Hasugian
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 2 (2026): AUGUST 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i2.7579

Abstract

The Mobile JKN application developed by BPJS Kesehatan provides digital access to healthcare administration services in Indonesia. However, users continue to report difficulties when interacting with the application. This study evaluated the usability of Mobile JKN and examined user experience patterns by combining the System Usability Scale (SUS) with K-means clustering. Data were collected through an online questionnaire completed by 550 respondents in Medan who reported experience using the application. The mean SUS score was 50.13, which was classified as Poor and Grade D under the interpretation framework adopted in this study. Among the four UX dimensions, Efficiency received the lowest score at 53.15 out of 100, followed by Ease of Use at 55.14, System Reliability at 56.38, and User Satisfaction at 57.42. The three-cluster solution produced different score profiles: Cluster 0 (Fairly Satisfied) had a mean SUS score of 60.09 and comprised 168 respondents; Cluster 1 (Somewhat Dissatisfied) had a mean score of 47.61 and comprised 201 respondents; and Cluster 2 (Dissatisfied) had a mean score of 43.69 and comprised 181 respondents. Efficiency and ease of use were therefore the dimensions receiving the least favorable evaluations. Combining SUS with K-means revealed variations across the overall usability score and the four UX dimensions that were not represented by the aggregate SUS score alone. However, the low Silhouette Score indicated weak separation among the clusters; therefore, the resulting profiles should be interpreted as exploratory patterns that can guide further usability evaluation rather than as definitive user segments
Development of an E-Commerce Website Integrated with a Payment Gateway for Basreng RZQ Small and Medium Enterprise in Bandung Nur Aswan Multazam; Frencis Matheos Sarimole
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 2 (2026): AUGUST 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i2.7588

Abstract

This study aims to develop an e-commerce website integrated with the Midtrans payment gateway for Basreng RZQ, a micro, small, and medium-sized enterprise (MSME) in Bandung. The study is motivated by operational challenges in reconciling daily transaction data due to the absence of an internal admin panel on the existing website. This condition has the potential to cause errors in manual bookkeeping and increase the workload of business operators. To address these problems, an e-commerce platform was developed to enable customers to order products and make digital payments without requiring account registration. The study employed a descriptive-evaluative qualitative case study with a lean architecture approach. Data were collected through observation, interviews, and documentation and were analyzed based on the transaction processes and operational needs of the MSME. Functional system testing was conducted using the black-box testing method based on ordering and payment verification scenarios. The results indicate that the integration of the Midtrans payment gateway supports automated payment verification and helps simplify transaction management. The developed system also provides a more structured alternative for recording transactions compared with manual bookkeeping. This study provides a practical solution for supporting the digitalization of sales and payment processes in MSMEs and may serve as a reference for developing e-commerce systems integrated with digital payment services.

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