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Analysis of the Topsis in the Recommendation System of PPA Scholarship Recipients at Universitas Islam Kebangsaan Indonesia Hasdyna, Novia; Dinata, Rozzi Kesuma; Retno, Sujacka
Jurnal Transformatika Vol 21, No 1 (2023): July 2023
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v21i2.7051

Abstract

This research implements the TOPSIS method on a recommendation system for Peningkatan Prestasi Akademik (PPA) scholarship recipients. The research data was obtained from the computer and multimedia faculty, UNIKI. The results showed that the TOPSIS method can provide the best alternative based on the highest rank. In this research, the highest rank was obtained from the results for predetermined criteria, namely GPA, achievements, parental dependents and parental income. The highest value obtained is 0.7489. The system built based on a website with the PHP programming language.
Implementation of K-NN Algorithm to classify the Scholarship Recipients of Aceh Carong at Universitas Malikussaleh Yanti, Riski; Retno, Sujacka; Yafis, Balqis
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 1 (2024): Journal of Advanced Computer Knowledge and Algorithms - January 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i1.14534

Abstract

In an effort to increase the efficiency of the scholarship selection process, this research aims to implement the K-Nearest Neighbors (K-NN) algorithm in the classification of scholarship recipients. The research method involves collecting data on scholarship receipts from several previous years based on predetermined criteria such as father's job, mother's job, parent's income, number of parents working, father's last education, and mother's last education. Next, the K-NN algorithm is applied to classify prospective scholarship recipients based on the similarity of their profiles to students who have received previous scholarships. The results of this research indicate that the implementation of the K-NN algorithm in the classification of scholarship admissions at Malikussaleh Aceh Carong University can increase selection accuracy. The experimental results of the accuracy values obtained show that using the K-Nearest Neighbors algorithm with the Euclidean Distance approach and a value of K = 3 produces an algorithm accuracy level of 87.55%. Thus, the K-NN algorithm can be a useful method for scholarship selectors to support more precise and objective decision making.
K-NN with Purity Algorithm to Enhance the Classification of the Air Quality Dataset Retno, Sujacka; Hasdyna, Novia; Yafis, Balqis
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 2 (2024): Journal of Advanced Computer Knowledge and Algorithms - April 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i2.15890

Abstract

The large number of attributes in a large dataset can cause a decrease in the level of classification accuracy. Attribute reduction can be a solution to improve classification performance, especially in the K-NN algorithm. This research discusses the classification results of K-NN with attribute reduction using Purity. Based on the results of testing carried out on the Air Quality Dataset, the level of accuracy obtained after attribute reduction was 70.71%, while the level of accuracy obtained before attribute reduction was 56.44%, the increase in accuracy obtained from testing this dataset was equal to 14.27%. The proposed Purity method for attribute reduction can increase the accuracy level of the K-NN classification process.
Comparison of Chen's Fuzzy Time Series and Triple Exponential Smoothing in Forecasting Medicine Stocks at the Blang Cut Kuala Community Health Center Devi, Salma; Yunizar, Zara; Retno, Sujacka
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 3 (2024): Journal of Advanced Computer Knowledge and Algorithms - July 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i3.16870

Abstract

Forecasting is estimating future conditions by examining conditions in the past. In social life, everything is uncertain and difficult to predict precisely, so forecasting is needed. Efforts are always made to make forecasts in order to minimize the influence of this uncertainty on a problem. In other words, forecasting aims to obtain forecasts that can minimize forecast errors, which are usually measured by the mean absolute percentage error. This method is usually used for time series-based forecasting and uses data or information from the past as a reference when predicting current data. This research will compare the application of the Fuzzy Time Series Chen method and the Triple Exponential Smoothing method in forecasting drug stock determination at the Kuala Community Health Center, Blang Mangat District, Lhokseumawe City Regency, Aceh. The research results showed that the Triple Exponential Smoothing method was better in forecasting drug stock inventories compared to Chen's Fuzzy Time Series method. Chen's Fuzzy Time Series method produces a MAPE value of 17.67%, which means it has an accuracy of 82.33%, while the Triple Exponential Smoothing method produces a MAPE value of 9.842%, which means it has an accuracy of 90.158%
Developing a Classic Turn-Based RPG: The Making of 'Waduh! Aku Pergi Ke Isekai' with RPG Maker MV Retno, Sujacka
Gameology and Multimedia Expert Vol 1, No 4 (2024): Gameology and Multimedia Expert - October 2024
Publisher : Department of Informatics Faculty of Engineering Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/game.v1i4.18854

Abstract

The game "Waduh! Aku Pergi ke Isekai" is a classic Role Playing Game (RPG) developed using RPG Maker MV. It tells the story of a young man named Makecar who is suddenly summoned to another world by a Goddess to defeat a Demon God threatening the world's destruction. The game combines classic RPG elements such as a Standard Turn-Based battle system, open-world exploration, and a variety of main and side quests, offering players diverse gameplay experiences. RPG Maker MV was chosen for its ease of use, even for beginner developers, utilizing a graphical user interface and simplified JavaScript scripting. Testing of the game shows that "Waduh! Aku Pergi ke Isekai" provides a deep and challenging gameplay experience, while also highlighting the potential of RPG Maker MV as an effective platform for independent game development. This game aims to inspire other game developers to create similar creative and original games.
Development of Obstacle Odyssey, an Interactive Game by Using GDevelop Panjaitan, Cherlina Helena Purnamasari; Retno, Sujacka; Hasdyna, Novia
Gameology and Multimedia Expert Vol 1, No 2 (2024): Gameology and Multimedia Expert - April 2024
Publisher : Department of Informatics Faculty of Engineering Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/game.v1i2.15882

Abstract

Games are a medium that is in great demand by almost all ages, including children, teenagers and adults. As game technology develops which can be found on various platforms, games are not just mere entertainment but can also be given educational value in them. The Obstacle Odyssey game was built by applying educational values which are expected to improve the players' abilities in terms of tactical thinking. This Obstacle Odyssey game is an Arcade genre game. This game was built using Gdevelop using a no-code event system.
Developing the Console Dash: a 2D Adventure Game using Godot Game Engine Retno, Sujacka; Fortilla, Zeny Arsya; Sinambela, Ilmi Suciani
Gameology and Multimedia Expert Vol 1, No 1 (2024): Gameology and Multimedia Expert - January 2024
Publisher : Department of Informatics Faculty of Engineering Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/game.v1i1.14555

Abstract

A 2D platformer game, console dash is a game that tells the story of Dax, a curious game character, jumping out of his console to go on an adventure. He goes through difficult levels, collects objects and meets new friends. They form a team and fight a villain named Glitch. The aim of this research is to design a 2D Console Dash platformer game with an adventure genre that is interesting and also quite difficult to complete. This application was created using the Godot game engine with the GDScript programming language. The method used in this final assignment uses the MDLC model software development method, and uses the SWOT method for system weakness analysis. The final result of this project is a 2D platformer game that plays smoothly and provides an enjoyable gaming experience. Console Dash offers attractive graphics, music and sound effects that liven up the atmosphere of the game, as well as challenging levels to explore. Moreover, this game has an intuitive interface and responsive controls.
Implement the Analytical Hierarchy Process (AHP) and K-Nearest Neighbor (KNN) Algorithms for Sales Classification Husna, Asmaul; Retno, Sujacka; Rijal, Himmatur
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 4 (2024): Journal of Advanced Computer Knowledge and Algorithms - October 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i4.17819

Abstract

The Analytical Hierarchy Process (AHP) and K-Nearest Neighbor (KNN) algorithms are two algorithms that have proven efficient in various classification and prediction applications. This research examines the application of these two algorithms in the context of selling goods in PIM supermarkets. In this research, AHP and KNN are used to classify goods sold based on various criteria such as price, number of stock items sold, total sales amount. The research results show that KNN outperforms AHP in predicting the best-selling, best-selling and least-selling items based on sales in 2022 at PIM supermarkets. Based on this research, it can be concluded that the KNN algorithm is suitable for predicting the classification of goods sales in PIM Supermarkets. This research classifies sales of goods using the Analytical Hierarchy Process (AHP) and K-Nearest Neighbor (KNN) methods. This research uses 3 criteria. By using the value K=1, the experimental results show that the highest KNN has an accuracy of 38%, while AHP has an accuracy of 32%. Differences in accuracy results can be influenced by parameter settings and characteristics of the dataset used. Therefore, further analysis of these factors is needed to understand the performance differences between the two methods.
Design of an Educational Game for Children: 'Geometry Forest' Using Construct 2 Retno, Sujacka
Gameology and Multimedia Expert Vol 2, No 1 (2025): Gameology and Multimedia Expert - January 2025
Publisher : Department of Informatics Faculty of Engineering Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/game.v2i1.20323

Abstract

Early childhood education plays a crucial role in building the foundational knowledge and skills that will be used throughout life. This study aims to design and develop an educational game titled "Geometry Forest" using Construct 2, specifically designed to help children understand basic geometry concepts through an interactive and engaging learning experience. The game integrates learning elements such as recognizing geometric shapes, identifying colors, and enhancing cognitive and motor skills, with attractive graphics and a user-friendly interface. The development process includes concept design, asset creation, implementation, and testing, involving young children to evaluate their engagement, enjoyment, and understanding of the material presented. The results show that "Geometry Forest" effectively improves understanding of geometric concepts while providing an enjoyable learning experience, making it a valuable supplementary tool for learning both at school and home, and contributing to the improvement of early childhood education quality through educational game technology.
Application of Fuzzy C-Means and Borda in Clustering Crime–Prone Areas and Predicting Crime Rates Using Long Short Term Memory in Northern Aceh Regency Lubis, Syahrul Andika; Ula, Munirul; Retno, Sujacka
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.747

Abstract

North Aceh is a district with diverse geographical conditions, ranging from vast lowland areas in the north stretching from west to east, to mountainous areas in the south. The average altitude in North Aceh is 125 meters. The district covers an area of 2,694.66 km² with a population of 614,640 people in 2022. The issue of crime in North Aceh District has caused significant discomfort among the community. According to data from the Central Bureau of Statistics (BPS) of Aceh Province, the number of criminal cases increased from 6,651 cases in 2022 to 10,137 cases in 2023. Using the Fuzzy C-Means clustering method, the data was grouped into three clusters: cluster 1 represents safe areas, cluster 2 represents moderately vulnerable areas, and cluster 3 represents vulnerable areas. For ranking using the Borda method, the Dewantara Police Sector ranked first for the physical aspect, while the Muara Batu Police Sector ranked first for the item aspect. As for predictions using the LSTM model, almost all subdistricts achieved MAPE values below 20%, indicating that the LSTM model is quite effective in predicting crime-prone areas. For example, Baktiya District recorded a MAPE value of 15.85% for the physical aspect, while the best result was achieved by Simpang Keramat District for the item aspect with a MAPE value of 0.00%. However, in Syamtalira Bayu District, the item aspect reached a MAPE value of 20.07%. Although the MAPE value for the item aspect in Syamtalira Bayu is relatively high, it is still considered acceptable as it remains below 50%.