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All Journal SAMUDERA JURIKOM (Jurnal Riset Komputer) Jurnal Tika KLIK: Kajian Ilmiah Informatika dan Komputer Aceh Journal of Community Engagement (AJCE)
Dedy Armiady
Fakultas Ilmu Komputer Universitas Almuslim Bireuen - Aceh
Religion Agriculture, Biological Sciences & Forestry Humanities Chemistry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mathematics

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Pengembangan Aplikasi Sistem Pendukung Keputusan Rekrutmen Perawat Menggunakan Metode Weighted Product Dedy Armiady
Jurnal Tika Vol 8 No 1 (2023): Jurnal Teknik Informatika Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim Bireuen - Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51179/tika.v8i1.1857

Abstract

Work that requires high accuracy and must be done repeatedly is work that must be completed using a computer. This work will certainly be very difficult to complete if you only rely on human power which has weaknesses in terms of memory and speed. Currently, many agencies and companies are aggressively implementing computerized technology to support good management, one of which is a hospital. In addition to patient data management and other important data, cases of nurse recruitment are also things that need to be considered to be resolved by the computer. This study aims to develop a web-based decision support system using a weighted product model to calculate alternative rankings. The results obtained are that the weighted product method can be used to calculate the ranking of prospective nurses through 12 specified criteria, where from several applicants, 3 prospective nurses with the highest rank are taken. The decision support system application in this study was developed using the PHP and MySQL programming languages with the CodeIgniter framework
Pengembangan Sistem Informasi Pengajuan Judul Skripsi Menggunakan Algoritma Winnowing Dedy Armiady
Jurnal Tika Vol 8 No 2 (2023): Jurnal Teknik Informatika Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim Bireuen - Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51179/tika.v8i2.2066

Abstract

Administrative implementation in higher education institutions is currently increasingly directed to completely transform into digital-based administration by utilizing computer-based technology. It is intended that all forms of administrative services can be neatly arranged and easy to access. One case that has also become a concern for development is the case of submitting a student thesis title. Currently, many systems are being developed just for CRUD (Create, Read, Delete and Update) needs. Where in the old system, there was no similarity detection feature for proposed titles with existing titles. This study aims to build a system for submitting thesis titles for students of the Faculty of Computer Science, Almuslim University which has a title check similarity feature. In this study, the winnowing algorithm is used as a mathematical calculation model to calculate the proportion of document similarities using the document fingerprint method. The developed system is a web-based information system using the PHP and MySQL programming languages. As for the results obtained, the winnowing algorithm can be applied to a title submission information system that can display the proportion of the proposed title to the existing title
Klasifikasi Kualitas Buah Pisang Berdasarkan Citra Buah Menggunakan Stochastic Gradient Descent Dedy Armiady; Imam Muslem R
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 2 (2023): Oktober 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i2.1243

Abstract

Banana fruit quality is an important factor in meeting consumer demand and maintaining product quality in the supply chain. The development of automatic methods for classifying the quality of bananas is becoming increasingly important as the worldwide consumption of bananas grows. In this study, we propose a classification method for banana fruit quality using the Stochastic Gradient Descent (SGD) algorithm. This study aims to evaluate the performance of SGD in classifying the quality of bananas and to analyze the effect of selecting hyperparameters on the classification results. The dataset collected is a dataset containing pictures of bananas with various levels of ripeness and conditions. This dataset is used to train and test a classification model using SGD. During the experiment, hyperparameter tuning processes such as learning rate, momentum, and batch size were carried out to understand how these parameters affect the performance of SGD in classification. We report the results of evaluating the classification based on accuracy and analyze changes in performance with variations in hyperparameters. The results of this study indicate that SGD has the potential to classify the quality of bananas, where the optimal SGD model obtained a classification accuracy of 99.9%, compared to the standard SGD model which only obtained a classification accuracy of 94.7%.
Co-Authors ,, Mukhlis Munar Muslem R, Imam Riyadhul Fajri Rizky Mauliza T. Rafli A