JURNAL ILMIAH INFORMATIKA

EVALUASI AWAL KUALITAS SISTEM INFORMASI AKADEMIK DENGAN METODE EUCS

Tue, 31 Mar 2026 00:00:00 +0000

Academic InFormation Systems (AIS) are essential for supporting academic management and instructional processes in higher education institutions. Evaluating AIS quality from the perspective of end users is crucial to ensure system effectiveness, particularly when systems are used intensively by lecturers.

This study aims to conduct an initial evaluation of AIS quality at Universitas Cipasung based on lecturers’ satisfaction using the End-User Computing Satisfaction (EUCS) model as a preliminary study.

The study employed a quantitative survey design using an EUCS-based questionnaire encompassing five dimensions: Content, Accuracy, Format, Ease of Use, and Timeliness. Although the conceptual population consisted of 92 users (lecturers and administrative staff), valid responses were obtained from 11 lecturers. Given the limited sample size and ordinal data scale, data were analyzed using descriptive statistics and Spearman Rank Correlation to examine the relationship between EUCS dimensions and perceived AIS quality.

The findings indicate that all EUCS dimensions achieved mean scores within the “satisfied” category. Spearman correlation analysis revealed that all dimensions were significantly associated with AIS quality (p < 0.05), with Format demonstrating the strongest correlation, followed by Content and Ease of Use.

The results confirm that the EUCS model is applicable for preliminary evaluation of AIS quality. User interface design, inFormation relevance, and system usability emerge as critical factors influencing lecturers’ perceptions of system quality.

PERANCANGAN ARSITEKTUR ENTERPRISE ORKESTRASI CLOUD BERBASIS TOGAF PADA PT. XYZ

Tue, 31 Mar 2026 00:00:00 +0000

The rapid adoption of cloud computing in enterprise environments introduces challenges related to infrastructure governance, security, scalability, and deployment consistency. PT XYZ, as a technology-driven organization, faces limitations in managing cloud infrastructure due to manual provisioning, fragmented access control, and the absence of a standardized architectural blueprint. This study aims to design an enterprise architecture for cloud infrastructure orchestration using The Open Group Architecture Framework (TOGAF). The research adopts a qualitative approach, utilizing document analysis and architectural modeling techniques. The TOGAF Architecture Development Method (ADM) is applied to analyze the existing architecture (As-Is) and design the target architecture (To-Be). The proposed architecture emphasizes Infrastructure as a Service (IaaS) supported by Amazon Web Services (AWS), with Amazon Elastic Kubernetes Service (EKS) as the core orchestration platform for application deployment. The resulting enterprise architecture consists of business, application, and technology architectures, modeled using IDEF0 and ArchiMate. The findings demonstrate that the proposed architecture improves infrastructure standardization, enhances deployment automation, strengthens security governance, and supports scalability. This study contributes an architectural blueprint that can be utilized as a reference for cloud-based enterprise architecture implementation in similar organizations.

PEMETAAN LOKASI PENYEBARAN LAYANAN BPJS KOTA PALEMBANG BERBASIS SISTEM INFORMASI GEOGRAFIS

Dinny Komalasari, irwansyah ibrahim, Helda Yudiastuti, Rismanto Rismanto — Tue, 31 Mar 2026 00:00:00 +0000

Along with the development of information technology and increasing levels of public education, this encourages us to use computers as a means of providing information. The need for information has become a basic need for society. One of these is the need for geographic information. GIS (Geographic Information System) technology is a geography-related technology that has the ability to visualize spatial data and its attributes. As the capital of South Sumatra Province, the city of Palembang is always required to provide information on the location of existing public facilities. One public facility frequently sought by the public is hospitals. The lack of information about the location of these hospitals can cause problems in the community. This obstacle was the author's consideration in developing a Geographic Information System for the Distribution of BPJS Services in Palembang City. The method used in developing this software is the Waterfall method. The stages of the Waterfall method include analysis, design, coding, and testing. This research resulted in a geographic information system for the distribution of BPJS services in Palembang City

IMPLEMENTASI APLIKASI SISTEM ABSENSI KARYAWAN BERBASIS FACE RECOGNITION DAN LOCATION BASED SERVICES (LBS) PADA PT. BENHIL RAYA INTERNASIONAL (BRAIN)

Miqdad Zaidan Alkhair Miqdad, Titin Kristiana, Supyan Haryanto Supyan — Tue, 31 Mar 2026 00:00:00 +0000

This study aims to design and implement a web-based employee attendance system utilizing Face Recognition and Location Based Service (LBS) technologies. The system was developed to enhance the accuracy, security, and efficiency of attendance recording while facilitating monitoring processes for administrators and supervisors. The research method applied in this study is the Waterfall model, which consists of requirement analysis, system design, implementation, testing, and evaluation stages. The results indicate that the developed system is capable of automatically verifying employee identities through facial recognition and validating attendance locations based on predefined GPS coordinates. The implementation of this system successfully reduces the potential for attendance fraud, such as proxy attendance, and accelerates the attendance data recapitulation process due to real-time and structured data storage. Furthermore, the system automatically generates daily, monthly, and overall attendance reports, thereby improving the effectiveness and efficiency of attendance management.

PENERAPAN TERM FREQUENCY-INVERSE DOCUMENT FREQUENCY DAN WORD EMBEDDING UNTUK PENILAIAN ESAI OTOMATIS

Rangga Muhammad Firdaus, Andy Victor Pakpahan, M.T. — Tue, 31 Mar 2026 00:00:00 +0000

Manual essay grading at the vocational school level is a time-consuming and subjective process. This research implemented and evaluated an automatic essay scoring model using a combination of the Term Frequency-Inverse Document Frequency (TF-IDF) algorithm for word weighting and Word Embedding for semantic meaning analysis. The model was tested using a dataset of 360 essay answers from 36 students at SMK Budi Bakti Ciwidey with train-test split validation. The tuning process on the training data showed that a weighting that prioritized semantic analysis (90% Word Embedding) provided the best performance. In the final testing on 90 test data, the model achieved an excellent Mean Absolute Error (MAE) of 6.80, but with a weak Pearson correlation of 0.12 against the teacher's scores. This research concludes that the proposed model is successful in generating scores that are very close to the teacher's scores (low MAE), but still has limitations in terms of scoring consistency (weak correlation), which is influenced by the quality of the key answers and an imbalanced dataset.

IMPLEMENTASI METODE SMARTER DAN TOPSIS PADA SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN BIBIT CABAI MERAH YANG UNGGUL

Putri Sri Rezeki, Muhammad Dedi Irawan, Fathiya Hasyifah Sibarani — Tue, 31 Mar 2026 00:00:00 +0000

The productivity of red chili cultivation highly depends on the quality of seeds used by farmers. However, identifying superior red chili seeds is often difficult, leading to low yields and even crop failure. This study aims to design a Decision Support System (DSS) for selecting superior red chili seeds using the SMARTER (Simple Multi Attribute Rating Technique Exploiting Rank) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methods. The SMARTER method is applied to determine the weight of each criterion based on the Rank Order Centroid (ROC), while the TOPSIS method is used to rank alternative seed varieties. Seven criteria were considered: price, disease resistance, harvest time, fruit length, fruit weight, number of branches, and yield potential. The system was developed using a waterfall model and implemented in a web-based application with PHP and MySQL. The results showed that the best-ranked alternative was the Tangguh F1 variety with a preference value of 0.7429, followed by Kastilo and TM999. The developed DSS provides structured, efficient, and transparent recommendations, thus helping farmers and agricultural agencies in decision-making for selecting superior red chili seeds.

SISTEM PENDETEKSI BAHASA ISYARAT SIBI MENGGUNAKAN LSTM BERBASIS OPENCV DAN MEDIAPIP

Ahmad Sarjianto, Melladia Melladia — Tue, 31 Mar 2026 00:00:00 +0000

This study aims to develop a Sign Language Translation System which is specifically for the Indonesian Sign Language System (SIBI) based on artificial intelligence (AI) and computer vision which aims to help communication between deaf/mute people and the general public. using the Long Short-Term Memory (LSTM) method, taking important data from Sign Language hand movements and combined with OpenCV and MediaPip. This system is designed with a web-based interface that will display translations in text form in real-time. The testing was conducted on a dataset consisting of SIBI alphabets and basic words, with the highest accuracy reaching 0.85 or 85% for basic words, and 0.45 or 45% for alphabet recognition.In conclusion, this research produced a system capable of automatically translating sign language by utilizing web technology for the interface, and OpenCV, MediaPip, and Long Short-Term Memory (LSTM) for the translation process.This system has great potential to reduce communication barriers between the general public and individuals with hearing or speech impairments, although further development is required to improve its accuracy.

IMPLEMENTASI DATA MINING MENGGUNAKAN ALGORITMA APRIORI DALAM MEMPREDIKSI DATA PERSEDIAAN PUPUK TANAMAN DI TOKO PUPUK MARNI

Dea Puspita Unu, Yusli Yenni — Tue, 31 Mar 2026 00:00:00 +0000

This research aims to apply the Apriori algorithm to predict the inventory of plant fertilizers at Toko Pupuk Marni. The primary focus of this study is to analyze sales transaction data as a means to enhance the efficiency of inventory management. The background of this research is rooted in the difficulties faced in managing inventory due to inefficient manual recording, which can lead to excess or shortage of stock. The method employed in this study is data mining, with the Apriori algorithm as the main technique for identifying purchasing patterns and relationships among items in the data. The analyzed data includes fertilizer sales transactions during the year 2024. The analysis results indicate that the Apriori algorithm can generate significant association rules, such as the relationship between Apsa and Rovral fertilizers, with a confidence level reaching 53.2%. Testing conducted using RapidMiner shows results consistent with manual analysis, thereby demonstrating the effectiveness of the Apriori algorithm in uncovering customer purchasing patterns. These findings provide valuable insights for store managers in determining better inventory strategies based on historical data. Thus, this research is expected to contribute significantly to the development of inventory information systems in the agricultural sector and serve as a reference for future studies related to data mining and inventory management.