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RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI
Published by Sekolah Tinggi Manajemen Informatika dan Komputer Budi Darma
ISSN : -     EISSN : 27457966     DOI : -
Core Subject : Science,
Computer Science & IT
Resolusi : Rekayasa Teknik Informatika dan Informasi, membahas ilmu dibidang Informatika, Sistem Informasi, Manajemen Informatika, DSS, AI, ES, Jaringan, sebagai wadah dalam menuangkan hasil penelitian baik secara konseptual maupun teknis yang berkaitan dengan Teknologi Informatika dan Komputer. Topik utama yang diterbitkan mencakup: 1. Teknik Informatika 2. Sistem Informasi 3. Sistem Pendukung Keputusan 4. Sistem Pakar 5. Kecerdasan Buatan 6. Manajemen Informasi 7. Data Mining 8. Big Data 9. Jaringan Komputer 10. Dan lain-lain (topik lainnya yang berhubungan dengan Teknologi Informasi dan komputer)
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 7 Documents
 1 
Search results for , issue "Vol. 4 No. 5 (2024): RESOLUSI May 2024" : 7 Documents clear
Penerapan Metode Simple Additive Weighting (SAW) dan Rank Order Centroid Dalam Analisis Kinerja Pegawai Honorer Emellika Rahmayana
Resolusi : Rekayasa Teknik Informatika dan Informasi Vol. 4 No. 5 (2024): RESOLUSI May 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/resolusi.v4i5.1690

Abstract

Employee performance is the result of work that has been achieved by an employee based on predetermined criteria. In order for employee performance to achieve its best, leaders in companies or agencies usually conduct performance appraisals, which are carried out by assessing the performance of each employee in achieving the work targets that have been set. However, the assessment is carried out by the leader in general only by giving a direct value based on the direct observation activities of the leader. To assist leaders in assessing outstanding employees, the method used in this research is the Simple Additive Weighting (SAW) method. With this method, the assessment is done by finding the sum of the weights of the performance rating on each alternative. After the performance assessment is completed, the next leader gives rewards to employees who have the best performance scores. By using the Simple Additive Weighting (SAW) method, it is expected to provide a more accurate assessment because it is based on predetermined criteria that can help management provide an assessment for employees who have outstanding performance. The results of the ranking of honorary employee performance appraisals from the 1st to the 11th are Desnila Aryani, Rosdhiana. S., M. Azhari Palungun, Bambang Indrawijaya, Amri Lubis, Wandani Batubara, Selamet Priyadi, Didi Susanto, Azhari, Fitriani Harahap, Robi Syahad N., and SE.
Penerapan Algoritma Greedy Dalam Penentuan Prioritas Pengerjaan Tugas Kuliah Mahasiswa Naufal Fakhri; Julian, Ary Sigit; Augustin, Darryl Sandi; Mavanudin, Zhykwa Ceryl; Christian, Efrans
Resolusi : Rekayasa Teknik Informatika dan Informasi Vol. 4 No. 5 (2024): RESOLUSI May 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/resolusi.v4i5.1824

Abstract

College assignments play a crucial role in enabling students to grasp course material and achieve learning objectives. However, the demands of completing assignments from multiple courses often leave students confused about prioritizing tasks. This can lead to suboptimal assignment completion and potentially lower the quality of learning. This research aims to assist students in effectively prioritizing college assignment completion using the greedy algorithm. This algorithm will aid students in creating optimal assignment scheduling by considering various factors such as deadlines and assignment difficulty. The research methodology employs simulation with diverse courses as variables and different weights, such as deadlines and assignment difficulty. Preliminary results indicate that the implementation of the greedy algorithm prioritizes assignment deadlines over assignment difficulty, potentially enhancing assignment completion efficiency, leading to more timely task completion and a reduction in student stress levels. The anticipated outcome of this research is to provide students with a method for completing college assignments more efficiently and effectively. This could contribute to improving learning quality and achieving positive learning outcomes. By adopting this approach, students can directly benefit from the research in their academic lives, reducing stress and enhancing their productivity.
Sistem Pendukung Keputusan Dalam Pemilihan Smartphone dengan Metode SAW Natanael Dimas Randy; Arita Witanti
Resolusi : Rekayasa Teknik Informatika dan Informasi Vol. 4 No. 5 (2024): RESOLUSI May 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/resolusi.v4i5.1867

Abstract

The rapid development of technology in this era has a positive impact on people from various walks of life, including children, adults, and the elderly, who can all benefit from the technology available today. The positive impact of technology includes fast and easy access to information, which can be done anywhere, serving as a learning tool, helping to reduce stress, and even providing income opportunities. Smartphones, or smartphones, are one such technology that is almost owned by everyone because they are sophisticated and practical devices. Due to the increasing demand for smartphones, many companies are striving to produce them. Among the various smartphone brands available, Chinese brands are widely used by Indonesian people due to their competitive prices and specifications in the Indonesian market. The abundance of Chinese smartphones has led to confusion among consumers when choosing a smartphone that suits their needs in terms of specifications and price. In addressing this issue, researchers have developed a website to assist people in choosing smartphones using the Simple Additive Weighting decision support system method. There are 5 criteria and 30 alternatives in this system. People can adjust the criteria values to display results that meet their needs. After the calculation process, the smartphone name Realme 9 obtained a final score of 0.93, making it a viable choice for consumers when purchasing a smartphone.
Pengembangan Sistem Informasi Personal Finance Management Menggunakan Pendekatan Rapid Application Development Pahlevi, Omar; Amrin; Handrianto, Yopi
Resolusi : Rekayasa Teknik Informatika dan Informasi Vol. 4 No. 5 (2024): RESOLUSI May 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/resolusi.v4i5.1883

Abstract

In the increasingly advanced digital era, many individuals struggle to manage their personal finances efficiently, often resulting in financial problems such as accumulating debt and the inability to save consistently. This issue is exacerbated by manual financial record-keeping, which is prone to errors and inefficient in providing a comprehensive and real-time financial overview. This study aims to develop and evaluate a personal finance management information system using the Rapid Application Development (RAD) approach. The RAD method was chosen for its iterative and flexible approach, allowing for quick adjustments according to user needs. This study also includes system evaluation through usability testing to measure efficiency, effectiveness, and user satisfaction. The results show that the application of RAD successfully produced high-quality software within three months, featuring key functionalities for managing income and expense data, as well as displaying financial reports based on specific periods. Additionally, usability testing indicated an average score of 87.5%, which falls into the 'Good' category, confirming the system's operational readiness and usability for users.
Pengembangan Sistem Pakar Menggunakan Pendekatan Dempster-Shafer Theory Pada Diagnosis Gangguan Makan Pada Anak Fatmayati, Fryda; Nurnaningsih, Desi; Nugroho, Nurhasan; Kurniawanto, Hadi
Resolusi : Rekayasa Teknik Informatika dan Informasi Vol. 4 No. 5 (2024): RESOLUSI May 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/resolusi.v4i5.1884

Abstract

In this modern era, eating disorders in children are receiving increasing attention due to their significant impact on physical health, mental well-being, and overall development. Diagnosing eating disorders in children is often complicated due to the varying symptoms and the difficulty children have in articulating or understanding their conditions. Additionally, traditional diagnostic approaches often rely on subjective assessments and clinical expertise, which can lead to misdiagnosis or delays in appropriate intervention. This study aims to develop an expert system for diagnosing eating disorders in children using Dempster-Shafer Theory as the primary inference engine. This approach is chosen for its strengths in handling uncertainty and incomplete information, allowing the system to make diagnostic inferences based on observed symptoms, even when the information is ambiguous or incomplete. The system is designed to leverage computational algorithms and medical knowledge, providing reliable and consistent results. From tests conducted on a sample of 30 randomly selected cases, the system achieved an accuracy rate of 93.33%, demonstrating that this approach is highly effective in diagnosing eating disorders in children. The developed expert system, web-based, is equipped with key features that enable diagnosis based on symptoms and provide diagnostic results along with recommendations for appropriate medical actions.
Optimasi Model Machine Learning untuk Klasifikasi dan Prediksi Citra Menggunakan Algoritma Convolutional Neural Network Eko Setia Budi; Arifa Nofriyaldi Chan; Prilly Priscillia Alda; Muh. Arif Fauzi Idris
Resolusi : Rekayasa Teknik Informatika dan Informasi Vol. 4 No. 5 (2024): RESOLUSI May 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/resolusi.v4i5.1892

Abstract

Convolutional Neural Networks (CNN) have become the dominant algorithm in image classification and prediction due to their ability to recognize complex visual patterns. However, to achieve optimal performance, CNN models require various optimization techniques. This study aims to explore and implement optimization techniques in training CNN models to enhance the accuracy and generalization capabilities of the model in image classification. The techniques implemented include learning rate scheduling, batch normalization, regularization with dropout and L2, data augmentation, and the use of transfer learning with pre-trained models such as VGG16. Additionally, early stopping methods and advanced optimization algorithms like Adam and RMSprop are applied to improve convergence and prevent overfitting. The results show that the combination of applied optimization techniques significantly improves the performance of CNN models. Analysis of the model training history visualization indicates a reduction in loss and an increase in accuracy, with slight indications of overfitting towards the end of training. These findings emphasize the importance of employing holistic optimization strategies in developing CNN models for image classification and prediction applications. However, in some experiments, the trained models still exhibited prediction errors. This can be attributed to factors such as overfitting or underfitting, data quality and quantity, data diversity, model architecture, and optimization methods. Therefore, further optimization is needed in data preparation, determination of optimization methods, and data cleaning.
Sistem Pendukung Keputusan Pemilihan Guru Berprestasi Menerapkan Metode AHP dan MOORA Mochamad Dedy Subekti Rahardjo
Resolusi : Rekayasa Teknik Informatika dan Informasi Vol. 4 No. 5 (2024): RESOLUSI May 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/resolusi.v4i5.1896

Abstract

This decision support system research method is used for racing in order to help vocational high schools (SMK) in determining the selection of outstanding teachers. In this selection of outstanding teachers, the method of selection is still using a manual system, which is based on observations from the principal directly by selecting teachers who are considered to have excellence based on predetermined criteria, for example having special achievements, having perseverance, activeness in school, attendance, and social relationships. For this research, the methods used in selecting outstanding teachers are Analytical Hierarchy Process (AHP) for weighting and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) in ranking purposes. The result for this research is that the combination of AHP and MOORA methods in determining outstanding teachers can be used. SPK can show information according to what the user enters correctly.

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