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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Budimas : Jurnal Pengabdian Masyarakat Science Technology and Management Journal (STMJ)
Lutfina, Erba
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Integration of Chatbot and Complaint Website Using Agile Scrum with Load Testing and UAT Winasis, Galih Adi; Lutfina, Erba; Saraswati, Galuh Wilujeng
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 2 (2026): Article Research April, 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i2.15879

Abstract

This study investigates an integrated public complaint service that combines a non-AI, rule-based WhatsApp chatbot, a web-based administrative dashboard, and a RESTful API to improve early response, status traceability, and ticket-based two-way communication. The system was developed using an Agile Scrum approach, implementing the chatbot in Node.js, the backend services and dashboard in Laravel, and PostgreSQL as the centralized database, while real-time dashboard updates were delivered via WebSocket. Evaluation was conducted through User Acceptance Testing (UAT) for core functional flows and RESTful API load testing using Apache JMeter under gradual-load conditions (Typical Busy, Peak, Stress) and an extreme surge condition (Spike/Burst). The UAT results indicate that all core scenarios passed, covering ticket-based complaint submission, duplicate prevention via a one active ticket per WhatsApp number rule, administrator validation and routing, and real-time conversation synchronization within the ticket context. Under gradual-load conditions, all evaluated endpoints maintained a 0% error rate with sub-second average latency in the range of a few hundred milliseconds, indicating stable baseline behavior as workload increased progressively. Under Spike/Burst, the system remained error-free but latency increased, with average response times of 6,593 ms for create complaint, 18,010 ms for status tracking, 18,321 ms for chat message, and 14,308 ms for mixed load, with throughputs of 7.06 req/s, 2.62 req/s, 2.05 req/s, and 5.90 req/s, respectively. Overall, the results demonstrate end-to-end functional feasibility, stable baseline performance under gradual load, and a resilience boundary under extreme surge, motivating targeted optimization of synchronous processing, history retrieval, and payload serialization to improve Spike/Burst time responsiveness.
Developing an Integrated Capital Assistance and Community Training System Using Agile Scrum Zuhdi, Ahmad Muzaki; Lutfina, Erba; Saraswati, Galuh Wilujeng
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 2 (2026): Article Research April, 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i2.15947

Abstract

Local governments increasingly require Cross-Agency Integration platforms to deliver transparent, auditable public services, yet capital assistance and community training programs are often managed through fragmented applications and manual workflows, leading to duplicated data, slow verification, and limited status traceability. This study develops an integrated capital assistance and community training system for local government using Agile Scrum, and evaluates its functional acceptance, usability, and security readiness to support Public Service Digitalization. Requirements were elicited through observation and interviews across three service-managing municipal agencies, while system governance and evaluation also involved the Communication and Informatics Office. The system was implemented as a web application with iterative sprints and backlog prioritization. Evaluation employed a User Acceptance Test (Likert 1–5, 10 items), System Usability Scale, and penetration testing using OWASP ZAP focusing on session management and HTTP security headers. Fifteen agency users participated in the evaluation. The system achieved 93% functional acceptance and a System Usability Scale score of 82.3, indicating excellent perceived usability. Security scanning found no high-risk issues, while medium- and low-risk findings were dominated by missing headers (Content Security Policy and X-Frame-Options) and incomplete cookie flags, which can be mitigated through standard hardening. The proposed platform improves cross-agency coordination and citizen-facing transparency while meeting usability expectations. Agile Scrum enabled rapid alignment with stakeholders and incremental quality improvements. Future work includes analytics, financial-system integration, and continuous security monitoring.
Improving Multi-Class Public Complaint Classification with LSTM, Word2Vec, and Random Oversampling Nimasari, Azza; Saraswati, Galuh Wilujeng; Lutfina, Erba
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 2 (2026): Article Research April, 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i2.15975

Abstract

Digital transformation in the public sector encourages local governments to enhance service quality through online complaint management systems. However, the high volume of incoming complaints and significant data imbalance across 31 Organisasi Perangkat Daerah (OPD) pose challenges for efficient manual classification, often resulting in delays and misclassification. This study proposes an automated text classification model that integrates Long Short-Term Memory (LSTM), Word2Vec, and Random Oversampling (ROS), optimized using the Adam algorithm. The novelty of this research lies in the integration of sequential modeling and imbalance handling to address an extreme multi-class classification problem involving 31 OPD categories within a highly imbalanced dataset. The research stages include text preprocessing, word embedding construction using Word2Vec, data balancing through ROS, and model training using LSTM. Experimental results show that the proposed model achieves an accuracy of 0.72, with macro-average precision, recall, and F1-score of 0.67, 0.67, and 0.66, respectively. Considering the complexity of classifying 31 classes and the presence of severe data imbalance, the macro F1-score of 0.66 indicates that the model is reasonably effective in capturing classification patterns, although performance is not yet evenly distributed across all classes. Overall, the combination of LSTM, Word2Vec, and ROS demonstrates potential as a baseline approach for automating public complaint classification in complex multi-class scenarios. The proposed model can improve the accuracy and speed of complaint distribution to the appropriate OPD, thereby enhancing the efficiency and responsiveness of public service delivery compared to conventional manual methods.
Decision Support System (DSS) for Rodenticide Selection using the TOPSIS Method Fitasari, Ayu Tri Nur; Lutfina, Erba; Saraswati, Galuh Wilujeng
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 2 (2026): Article Research April, 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i2.16008

Abstract

Selecting an appropriate rodenticide is a critical decision in pest control operations, as each product differs in effectiveness, application cost, safety level, environmental impact, and resistance potential. In practice, rodenticide selection is often based on technician experience or habitual product use, which may result in subjective and less optimal decisions. This study aims to develop a decision support system for rodenticide selection using the TOPSIS method within a multi-criteria decision-making (MCDM) framework. The evaluation is conducted based on six criteria: effectiveness, application cost, safety derived from LD50 values, secondary poisoning risk, resistance potential, and application convenience. To improve the robustness of the decision-making model, this study incorporates an adaptive TOPSIS approach through scenario-based weighting and compares the results with the Simple Additive Weighting (SAW) method. The findings show that alternatives with a balanced performance in terms of safety and operational cost consistently achieve higher rankings, with Warfarin Bait and Zinc Phosphide appearing as top-performing options across different evaluation scenarios. In addition, the proposed model is implemented in a web-based system using a prototype development approach, enabling automated calculations and transparent ranking results. This study provides a structured and practical decision support model that integrates technical, economic, and environmental considerations to support more objective decision-making in pest control management.
Co-Authors Adji, Dian Restu Andriana, Wiwin Anwarri, Kenza Amalia Putri Anwarri, Kenza Amelia Putri Caturkusuma, Resha Meiranadi Dimentieva, Imelda Erika Devi Udayanti Febrianti, Ervina Ferdianto, Bhekti Eka Fitasari, Ayu Tri Nur Loekito, Joseph Mellati, Pita Nimasari, Azza Prashanti, Eva Prayogo, Syahrul Rizqi Pribadi, Ahmad Naufal Resha Meiranadi Caturkusuma Safa’at, Mochammad Alief Fauzan Akbar Saraswati, Galuh Wilujeng Syahidan, Mukhammad Shaunan Wildan Mahmud Winasis, Galih Adi Wiratmaja, Sanina Quamila Putri Yuanita, Syafira Putri Yustiqomah, Evita Citra Zuhdi, Ahmad Muzaki