ABSTRAK
Proses deployment aplikasi ke lingkungan produksi pada industri Bank XYZ merupakan
tahap kritis yang memerlukan tingkat kesiapan tinggi guna meminimalkan risiko
kegagalan sistem, gangguan layanan, serta potensi kerugian bisnis. Penilaian readiness
deployment selama ini umumnya masih bersifat subjektif dan bergantung pada
pengalaman tim Quality Assurance (QA), sehingga berpotensi menimbulkan
ketidakkonsistenan dalam pengambilan keputusan. Oleh karena itu, penelitian ini
bertujuan untuk mengembangkan sistem pendukung keputusan yang mampu membantu
menentukan tingkat kesiapan deployment aplikasi Bank XYZ secara objektif dan
terstruktur. Metode yang digunakan dalam penelitian ini adalah integrasi logika fuzzy
dengan pendekatan Fuzzy Tsukamoto dan Fuzzy Sugeno. Penilaian dilakukan
berdasarkan checklist Quality Assurance yang mencakup sejumlah kriteria utama, antara
lain kesiapan fungsional aplikasi, hasil pengujian, validasi fungsional dan hasil pengujian
akhir, performa sistem, serta kesiapan infrastruktur pendukung. Setiap kriteria
direpresentasikan dalam bentuk variabel fuzzy dengan fungsi keanggotaan tertentu,
kemudian diproses melalui mekanisme inferensi fuzzy untuk menghasilkan nilai keluaran
berupa tingkat readiness deployment. Hasil penelitian menunjukkan bahwa kedua metode
fuzzy mampu memberikan rekomendasi keputusan deployment yang lebih konsisten
dibandingkan pendekatan konvensional. Metode Fuzzy Tsukamoto menghasilkan
keluaran berupa nilai crisp berdasarkan aturan monoton, sedangkan Fuzzy Sugeno
menghasilkan keluaran yang lebih stabil dan mudah diintegrasikan dalam sistem
pendukung keputusan. Berdasarkan hasil analisis perbandingan, metode Fuzzy Sugeno
dinilai lebih efektif dalam memberikan rekomendasi kesiapan deployment aplikasi Bank
XYZ. Dengan demikian, sistem yang dikembangkan dalam penelitian ini diharapkan
dapat menjadi alat bantu pengambilan keputusan yang objektif, akurat, dan dapat
meningkatkan kualitas serta keandalan proses deployment aplikasi di lingkungan Bank
XYZ.
Kata kunci: sistem pendukung keputusan, readiness deployment, Quality Assurance,
fuzzy Tsukamoto, fuzzy Sugeno.

ABSTRACT
The deployment of applications into the production environment within Bank XYZ
represents a critical phase that requires a high level of readiness in order to minimize the
risks of system failure, service disruption, and potential business losses. In practice,
deployment readiness assessments are often subjective and heavily dependent on the
experience of the Quality Assurance (QA) team, which may lead to inconsistencies in
decision-making. Therefore, this study aims to develop a decision support system that
assists in determining the deployment readiness level of Bank XYZ applications in an
objective and structured manner. The method employed in this research involves the
integration of fuzzy logic using the Fuzzy Tsukamoto and Fuzzy Sugeno approaches. The
assessment is conducted based on a Quality Assurance checklist comprising several key
criteria, including application functional readiness, testing results, final functional
validation, system performance, and supporting infrastructure readiness. Each criterion is
represented as a fuzzy variable with specific membership functions and processed
through a fuzzy inference mechanism to produce an output value representing the
deployment readiness level. The results indicate that both fuzzy methods are capable of
providing more consistent deployment recommendations compared to conventional
approaches. The Fuzzy Tsukamoto method generates crisp output values based on
monotonic rules, whereas the Fuzzy Sugeno method produces more stable outputs that
are easier to integrate into a decision support system. Based on the comparative analysis,
the Fuzzy Sugeno method is considered more effective in providing deployment readiness
recommendations for Bank XYZ applications. Consequently, the system developed in this
study is expected to serve as an objective and accurate decision-support tool that enhances
the quality and reliability of the application deployment process within Bank XYZ.
Keywords: decision support system, deployment readiness, Quality Assurance, Fuzzy
Tsukamoto, Fuzzy Sugeno.