Jurnal Sistem Informasi (JUSIN)

RANCANG BANGUN SISTEM INFORMASI MONITORING PENCAPAIAN TARGET KINERJA PEGAWAI PADA PT. LABDA ANUGERAH TEKSTIL BERBASIS WEB MENGGUNAKAN METODE WATERFALL

Komang Saskara Putra, I Gede Juliana Eka Putra, Nengah Widya Utami — Tue, 23 Dec 2025 00:00:00 +0000

Kemajuan teknologi informasi berperan penting dalam berbagai sektor, termasuk manajemen kinerja pegawai. PT. Labda Anugerah Tekstil menghadapi permasalahan dalam pencatatan pekerjaan harian pegawai yang masih dilakukan secara manual, sehingga rawan terhadap kesalahan dan ketidakefisienan. Untuk mengatasi hal tersebut, penelitian ini merancang dan membangun sistem informasi monitoring pencapaian target kinerja pegawai berbasis web menggunakan framework Laravel dan metode Waterfall. Sistem ini mencakup fitur pencatatan aktivitas kerja pegawai, pengelolaan data tugas oleh admin, serta laporan pencapaian kinerja. Perancangan sistem dilakukan menggunakan Visual Studio Code, dengan HTML, CSS, Bootstrap, dan JavaScript untuk antarmuka pengguna, Laravel sebagai backend framework, dan TablePlus sebagai basis data. Pengujian dilakukan menggunakan metode Black Box Testing untuk memastikan semua fungsi sistem berjalan sesuai spesifikasi. Hasil penelitian menunjukkan bahwa sistem mampu meningkatkan efisiensi, akurasi, dan validitas pencatatan kinerja pegawai. Dengan data yang terstruktur dan terintegrasi, sistem ini mendukung pengambilan keputusan manajerial secara lebih cepat dan efektif.

ANALISIS PERBANDINGAN FRAMEWORK BACKEND NODE.JS DAN SPRINGBOOT MENGGUNAKAN METODE GRAPHQL

affu barkah, I Nyoman Yudi Anggara Wijaya, Nengah Widya Utami — Tue, 23 Dec 2025 02:44:07 +0000

As the demand for fast, responsive, and scalable web applications grows, API technologies have rapidly evolved. GraphQL offers efficient data management and transfer, with Node.js and Spring Boot being two widely used frameworks for its implementation. This study aims to compare the performance of GraphQL APIs built with these frameworks. Performance testing focused on response time, throughput, error rate, and concurrent user capacity, using dummy data under varying loads via Postman. Results show that under low loads (10 virtual users), both frameworks perform similarly. However, at higher loads (50 virtual users), Spring Boot demonstrates better performance with faster response time (514 ms vs. 1,766 ms), higher throughput (53.64 rps vs. 18.46 rps), and no errors, while Node.js records a 1.79% error rate. In Spike and Peak scenarios, Spring Boot consistently outperforms Node.js. These findings provide valuable insights for developers in selecting the most suitable framework based on application needs.

PERANCANGAN SISTEM RESERVASI DAN KASIR RESTORAN BERBASIS WEBSITE STUDI KASUS NYOMAN CAFE

Mikail Abdullah, I Nyoman Purnama, Ni Putu Noviyanti Kusuma — Tue, 23 Dec 2025 02:56:17 +0000

The advancement of information technology has driven various business sectors, including the culinary industry, to adopt digital systems to enhance operational efficiency and customer satisfaction. This study aims to design a web-based reservation and cashier system for Nyoman Cafe, a renowned seafood restaurant in Bali. The system addresses challenges in manual reservations and transaction recording, which often lead to errors, delays, and data inaccuracies. Utilizing the Prototipe method, the research involves stages of requirement gathering, interface design using Figma, and Prototipe evaluation to ensure the system aligns with user needs. The resulting system enables customers to make online table reservations with real-time availability access while simplifying transaction management through automated record-keeping features. This system is expected to improve operational efficiency, minimize errors, enhance customer experiences, and strengthen Nyoman Cafe's competitiveness in the culinary industry.

IMPLEMENTASI SISTEM MONITORING MENGGUNAKAN ZABBIX DAN NOTIFIKASI REALTIME TELEGRAM UNTUK JARINGAN INTERNET BSI (BALI SMART ISLAND) DI KABUPATEN JEMBRANA

I Kadek Sugiarta, I Gede Juliana Eka Putra, I Nyoman Yudi Anggara Wijaya — Tue, 23 Dec 2025 00:00:00 +0000

With the advancement of information and communication technology, society has become increasingly dependent on access to information through the internet. However, this growing reliance has also led to a rise in the frequency of network disruptions, which can cause delays in information dissemination and interfere with institutional operations. PLN ICON PLUS, as an Internet Service Provider (ISP), faces the challenge of monitoring 123 routers used by the customers of the Jembrana Regency Communication and Information Office (Diskominfo). This research highlights the importance of implementing a network monitoring system using Zabbix, which can provide real-time notifications through Telegram to detect disruptions and minimize downtime.
Currently, PLN ICON PLUS does not yet have an effective monitoring system, resulting in delays in addressing network issues. By adopting a more advanced monitoring solution, network performance is expected to improve, enabling technical teams to respond quickly and efficiently to disruptions, thereby enhancing service quality for Diskominfo Jembrana customers. The final results of the monitoring system show that it can operate properly and consistently send real-time notifications to Telegram whenever disruptions occur on devices or network services. This proves that the system can improve the responsiveness of the technical team in handling issues and minimizing downtime. Thus, the monitoring system is considered effective in supporting proactive and efficient network management.

ANALISIS SENTIMEN OPINI MASYARAKAT TERKAIT PENGGUNAAN MOBILE JKN PADA MEDIA SOSIAL X MENGGUNAKAN ALGORITMA K-NEARESTNEIGHBOR (KNN) DAN LOGISTIC REGRESSION (LR)

Kelvin Hematang — Tue, 23 Dec 2025 03:16:27 +0000

BPJS Kesehatan launched the Mobile JKN application in 2017 to enhance healthcare accessibility and simplify membership management. As of September 2024, 98.67% of Indonesia’s population has joined the JKN program, highlighting the importance of public opinion in the application’s development. This study analyzes public sentiment toward Mobile JKN through the social media platform X using the K-Nearest Neighbor (KNN) and Logistic Regression (LR) algorithms. From 4,777 reviews, 4,648 clean data were obtained after preprocessing and labeled using IndoBERT, resulting in 2,066 positive reviews and 2,581 negative reviews. The evaluation results show that KNN achieved an accuracy of 83.87%, while LR performed better with 87.85% along with higher precision, recall, and f1-score.

The findings reveal the dominance of negative sentiment in user reviews and provide insights for BPJS Kesehatan to improve Mobile JKN into a more responsive application that meets users’ needs and feedback.

ANALISIS DATA PENJUALAN HIJAB PREMIUM BERBASIS WEB MENGGUNAKAN ALGORITMA APRIORI UNTUK OPTIMASI STRATEGI PEMASARAN

Taufik Hidayat, Yuni Handayani, Salma Thahira Adelia Heppy — Tue, 23 Dec 2025 03:23:00 +0000

The rapid development of digital technology has driven an increase in online shopping transactions, including in the premium hijab label industry. Premium Hijab Label faces challenges in stock management, service delays, and difficulties in identifying consumer purchasing patterns. Therefore, this study aims to build a web-based sales analysis system by applying the Apriori algorithm as a data mining method to discover association patterns between products. The system development method used was prototyping, with stages including needs analysis, design, implementation using PHP with the CodeIgniter and MySQL frameworks, and testing using Black Box Testing. The analyzed data were Premium Hijab Label sales transactions from 2023–2024. The results show that the system can display frequent itemsets and generate association rules with certain support and confidence values. Some rules have confidence levels above 60%, which can be used as the basis for product recommendations and promotional strategies. The conclusion of this study is that the Apriori algorithm-based system can assist MSMEs in analyzing consumer shopping patterns, supporting strategic decision-making, and improving the efficiency of stock management and marketing.