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Strategic Evaluation of Whistleblower Software Security in Government: ISO/IEC 25010 and AHP Method Purbaratri, Winny; Sembiring, Irwan; Setiawan, Adi; Setyawan, Iwan
Jurnal Sistem Informasi Bisnis Vol 14, No 4 (2024): Volume 14 Nomor 4 Tahun 2024
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol14iss4pp321-328

To assess the effectiveness of software security measures in government whistleblower systems, we will utilize the ISO/IEC 25010 standard and the Analytic Hierarchy Process (AHP) methodology. Through the integration of various frameworks, our objective is to build a complete evaluation model that effectively identifies and enhances any vulnerabilities in these crucial systems. The strategy we employ combines the qualitative and quantitative evaluation capabilities of ISO/IEC 25010 and AHP, respectively, to offer a comprehensive perspective on software security performance. The results indicate substantial improvements in the security and reliability of whistleblower software, underscoring the effectiveness of our suggested evaluation technique in identifying crucial areas for refinement. Moreover, the utilization of AHP permitted the ranking of security qualities, guaranteeing focused and efficient improvements. Ultimately, the study emphasizes the significance of thorough security assessments for government whistleblower systems and verifies the effectiveness of utilizing ISO/IEC 25010 and AHP as a methodical approach to improve software security. This research enhances the ongoing endeavor to protect confidential data, fostering a more secure and reliable atmosphere for individuals who expose wrongdoing.

Decision Support System for Futsal Player Selection Using the Profile Matching Method Hafiz, Farhan Mohammad; Rachmadi, Pratiwi; Purbaratri, Winny
Jurnal Teknologi Informatika dan Komputer Vol. 11 No. 2 (2025): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v11i2.2752

Futsal is a sport that is widely enjoyed by all groups. Each futsal team will open a selection process for players who want to become professional futsal players. Each team conducts a selection process to determine which players will join the core team. Player selection is a crucial aspect in shaping a team's strength and performance. Effective futsal player selection is key to forming a competitive and winning team. Selecting the right players is crucial to ensuring team performance and victory. The profile matching method is used to compare individual player profiles with the criteria set by the team for the selection process. This study aims to develop a decision support system (DSS) for selecting futsal players for the striker (pivot) position at SMA Angkasa 1 using the profile matching method. In the study, data on the futsal player selection criteria were collected from on-field assessments, skill tests, and interviews. The data used in this study included several criteria such as experience, strength, stamina, speed, and teamwork. The results of calculations using profile matching indicate the order of quality players that can be selected based on the criteria data. By creating this system, it is hoped that the futsal player selection process can be improved and result in a strong and optimal team composition, which will ultimately improve team performance in various competitions and matches.

Decision Support System in Determining Tourist Buses Using the Simple Additive Weighting (SAW) Method Marzuki, Donny Pramudia; Purbaratri, Winny; Prapto, Dwi Atmodjo Wismono; Faried, M Isnin
Open Global Scientific Journal Vol. 3 No. 2 (2024): Open Global Scientific Journal
Publisher : Research and Social Study Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70110/ogsj.v3i2.57

Background: Tourist buses play a critical role in group travel, where service quality, safety, comfort, and operational efficiency directly influence customer satisfaction. However, the selection process for tourist buses is often subjective, lacking structured evaluation mechanisms that account for multiple criteria.Aims: This study proposes a web-based decision support system (DSS) for tourist bus selection using the Simple Additive Weighting (SAW) method, designed to transform qualitative preferences into quantitative rankings.Methods and Results: The system evaluates nine well-known bus providers based on three key criteria: price, facilities, and brand, each weighted to reflect decision-making priorities. The SAW method was selected for its computational efficiency and ease of implementation; however, its inherent assumption of full compensability between criteria may lead to biased results in complex decisio contexts. To address this, the proposed framework incorporates expert-driven weight assignment and sensitivity analysis, ensuring that critical non-compensatory attributes such as safety are not overshadowed by other criteria. This integration enhances the robustness and reliability of the final rankings, making the system more adaptable to evolving market demands and customer expectations. Testing demonstrated that the DSS successfully ranked alternatives with transparent, data-driven results, with Melody Transport achieving the highest score (0.825) among the evaluated options. The novelty of this research lies in refining the SAW method for a sector-specific application and addressing its compensatory limitations through expert-based adjustments. This approach not only improves decision quality for consumers and tour operators but also establishes a scalable and intelligent framework for future DSS developments in the tourism transportation sector.

Decision Support System for Futsal Player Selection Using the Profile Matching Method Hafiz, Farhan Mohammad; Rachmadi, Pratiwi; Purbaratri, Winny
Jurnal Teknologi Informatika dan Komputer Vol. 11 No. 2 (2025): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v11i2.2752

Futsal is a sport that is widely enjoyed by all groups. Each futsal team will open a selection process for players who want to become professional futsal players. Each team conducts a selection process to determine which players will join the core team. Player selection is a crucial aspect in shaping a team's strength and performance. Effective futsal player selection is key to forming a competitive and winning team. Selecting the right players is crucial to ensuring team performance and victory. The profile matching method is used to compare individual player profiles with the criteria set by the team for the selection process. This study aims to develop a decision support system (DSS) for selecting futsal players for the striker (pivot) position at SMA Angkasa 1 using the profile matching method. In the study, data on the futsal player selection criteria were collected from on-field assessments, skill tests, and interviews. The data used in this study included several criteria such as experience, strength, stamina, speed, and teamwork. The results of calculations using profile matching indicate the order of quality players that can be selected based on the criteria data. By creating this system, it is hoped that the futsal player selection process can be improved and result in a strong and optimal team composition, which will ultimately improve team performance in various competitions and matches.

ANALISIS SENTIMEN APLIKASI PEMILU MENGGUNAKAN ALGORITMA NAIVE BAYES Yanah, Septi; Purbaratri, Winny; Paylina, Shinta; Safitri, Agnes Novita Ida; Tachjar, Nani Krisnawaty
JEIS: Jurnal Elektro dan Informatika Swadharma Vol 5, No 1 (2025): JEIS EDISI JANUARI 2025
Publisher : Institut Teknologi dan Bisnis Swadharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56486/jeis.vol5no1.684

The Election Commission applications are vital for improving transparency, accessibility, and efficiency in electoral processes. Understanding public sentiment towards these programs is crucial for improving their performance and user experience. This study aimed to do sentiment analysis on user feedback regarding Election Commission applications using the Naive Bayes Algorithm. Sentiment analysis, a method in natural language processing (NLP), was employed to classify textual input into positive, negative, and neutral sentiments. The dataset was acquired from Google Play Store reviews and underwent preparation phases, including cleaning, tokenization, and vectorization. The Naive Bayes Algorithm, recognized for its effectiveness in text classification, was utilized to identify sentiment trends. The results revealed that most users expressed positive feelings, highlighting satisfaction with usability and transparency features. However, significant concerns regarding technological failures and data security were also acknowledged. These findings provide substantial insights for enhancing Election Commission applications and fostering public trust.Aplikasi Komisi Pemilihan Umum (KPU) adalah alat penting untuk meningkatkan transparansi, kemudahan, dan efisiensi prosedur pemilihan. Perspektif publik tentang aplikasi ini sangat penting untuk meningkatkan kinerja dan pengalaman pengguna mereka. Tujuan dari penelitian ini adalah untuk menganalisis perasaan pengguna tentang aplikasi Pemilu menggunakan algoritma Naive Bayes. Analisis sentimen merupakan sebuah teknik dalam pemrosesan bahasa alami (NLP) yang membagi masukan teks menjadi sikap positif, negatif, dan netral. Dataset diperoleh melalui ulasan di Google Play Store, dan kemudian menjalani langkah-langkah pra-pemrosesan seperti pembersihan, tokenisasi, dan vektorisasi. Untuk mengidentifikasi pola perasaan digunakan algoritma Naive Bayes yang terkenal karena kemanjurannya dalam kategorisasi teks. Hasil penelitian menunjukkan bahwa mayoritas pengguna mengungkapkan perasaan yang positif, dengan fokus pada kepuasan dengan fitur usability dan transparansi. Namun, ada juga banyak kekhawatiran tentang kegagalan teknologi dan keamanan data. Hasil ini memberikan wawasan penting untuk meningkatkan aplikasi pemilu dan menumbuhkan kepercayaan publik.

Decision Support System for Selecting Volleyball Starting Players Using the AHP and SAW Methods Yanah, Septi; Purbaratri, Winny; Purwaningsih, Mardiana; Tachyar, Nani Krisnawaty; Akmaliyah, Yasmin
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3783

This study develops a decision support system to enhance the objectivity and reliability of selecting starting volleyball players, particularly for the spiker position, where traditional selection processes are often subjective and inconsistent. The research addresses the limitation of single-method decision models by integrating the Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) into a unified multi-criteria decision-making framework. AHP is employed to derive consistent and structured criterion weights, while SAW is used to generate a transparent ranking of player alternatives. Seven evaluation criteria were used, including passing, service, smash, block, teamwork, body mass index (BMI), and speed. Data were collected through structured observations and expert evaluations involving the team coach and founder. The results indicate that the smash criterion has the highest weight (0.4138), confirming its dominant role in spiker performance. The final ranking shows that Neng Irma Sukmayani achieved the highest score (0.9678), followed by Siti Karlina (0.9602) and Nova Amelia Putri (0.9040). Compared to subjective selection approaches, the proposed system provides a measurable and reproducible evaluation process, improving decision transparency and consistency. The integration of AHP and SAW contributes by reducing weighting bias while maintaining computational simplicity in ranking. The system was implemented using PHP and MySQL and validated through black-box testing, demonstrating stable functionality across all features. This study contributes both theoretically, by strengthening hybrid MCDM applications in sports analytics, and practically, by providing a scalable decision support model for athlete selection.

A Comparative Study of Software Testing Techniques and Quality Metrics for Predicting Failure Rates in Scalable Cloud Native Software Systems Winny Purbaratri; Mujito Mujito; Sayyid Jamal Al Din
Software Engineering in Computing Systems Vol. 1 No. 1 (2026): February: Software Engineering in Computing Systems
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/secons.v1i1.50

Cloud-native systems are essential for modern software development, offering enhanced scalability, flexibility, and resilience through cloud computing environments. However, ensuring the reliability and performance of these systems presents a challenge due to their dynamic and distributed nature. Traditional testing methods, such as unit and integration testing, while valuable for detecting individual component defects and interactions, are insufficient for predicting failure rates in complex, cloud-native applications. This study explores the effectiveness of various testing techniques and quality metrics in predicting failure rates within scalable cloud-native systems. A comparative experimental study was conducted using three primary testing techniques: unit testing, integration testing, and chaos testing. The results indicate that chaos testing, when combined with advanced quality metrics such as migration rate and mismigration rate, significantly outperforms traditional methods in predicting failure rates and evaluating system resilience. These findings suggest that chaos testing offers a more comprehensive evaluation, simulating real-world disruptions to test system behavior under stress, which is essential for cloud-native environments where high availability and fault tolerance are critical. The study also highlights the importance of integrating predictive quality metrics, which improve the accuracy of failure predictions and enhance system reliability. The study concludes that for cloud-native systems, a combination of advanced testing techniques and predictive metrics is essential for ensuring high availability, scalability, and reliability in dynamic environments. Future research should focus on refining predictive testing approaches, developing standardized frameworks, and empirically validating new testing methods to address the growing complexity of cloud-native systems.

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