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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Building of Informatics, Technology and Science Journal of Computer System and Informatics (JoSYC)
Teotino Gomes Soares
Dili Institute of Technology, Dili
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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Tomato Ripeness Detection Using Linear Discriminant Analysis Algorithm with CIELAB and HSV Color Spaces Rini Nuraini; Teotino Gomes Soares; Popi Dayurni; Mulyadi Mulyadi
Building of Informatics, Technology and Science (BITS) Vol 5 No 2 (2023): September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i2.4192

Abstract

Tomatoes have a relatively short ripening period, making it essential to identify their ripeness level before distribution. The ripeness level of tomatoes can be detected based on their color. Therefore, the color of tomatoes serves as a crucial indicator in determining whether they are ripe and of good quality. However, classifying tomato ripeness levels manually has several drawbacks, namely requiring a long process, a low level of accuracy, and being inconsistent. The research aimed at developing a detection model for the ripeness level of tomatoes using the LDA algorithm based on color feature extraction, namely CIELAB (L*a*b) and HSV. The L*a*b and HSV color spaces are applied to obtain information about the color of the object being detected. Furthermore, the information obtained from feature extraction is then grouped by class using the LDA algorithm, which separates information for each class and limits the spread between classes through linear projection searches to maximize the covariance matrix between classes so that members within the class can be identified. This research produces a model that can detect the level of ripeness of tomatoes with an accuracy of 88.194%.
Decision Support System Using a Combination of COPRAS and Rank Reciprocal Approaches to Select Accounting Software Moh. Erkamim; Nurdiana Handayani; Nofitri Heriyani; Teotino Gomes Soares
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 1 (2024): Januari 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i1.7111

Abstract

Accounting software plays an important role in carrying out accounting processes that are fast, efficient, accurate and in accordance with applicable standards. With the emergence of various accounting software that offers a variety of features, users, both individuals and companies, often experience difficulty in determining the software that best suits their needs. The aim of this research is to develop a decision support system that makes it easier to choose accounting software through the application of the COPRAS approach and the Rank Reciprocal weighting technique. The Rank Reciprocal approach is used to rank or weight the criteria given by the decision-maker. The COPRAS (Complex Proportional Assessment) approach focuses on cognitive aspects so that it can accommodate the preferences and subjective assessments of decision-makers. Based on the case study that has been carried out, the highest to lowest utility value results are obtained, namely Zahir Online (A2), which obtained a score of 100. Since the decision support system's output yields a result that is identical to that of computations made by hand, it is deemed legitimate. Apart from that, the usability test obtained an average score of 91%, which proves that the system is in accordance with its usability and what is needed by its users.
Decision Support System for Selection of Internet Services Providers using the ROC and WASPAS Approach Teotino Gomes Soares; Alfry Aristo Jansen Sinlae; Arief Herdiansah; Arisantoso Arisantoso
Journal of Computer System and Informatics (JoSYC) Vol 5 No 2 (2024): February 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i2.4892

Abstract

Along with the growth of the internet service provider industry, selecting an Internet Service Provider (ISP) has become an important decision to ensure optimal internet access. However, with so many ISP options available, consumers often face difficulties in choosing the service that best suits their needs. The aim of this research is to produce a decision support system that can help users choose the ISP that best suits their needs and preferences using the ROC (Rank Order Centroid) approach as a weighting technique and the WASPAS (Weighted Aggregated Sum Product Assessment) approach to determine the best alternative. The ROC approach is used to obtain criteria weights based on the ranking order of the importance of the criteria. On the other hand, the WASPAS method is used to determine the best alternative through weighted addition and multiplication, producing a final value that reflects the extent to which each alternative meets the specified criteria. The outcomes of the case study reveal a ranking of alternatives from highest to lowest scores, as follows: First Media (A2) achieving 0.8629, Indihome (A3) at 0.8416, MyRepublic (A5) with 0.7954, Biznet (A1) scoring 0.7844, and Oxygen (A4) at 0.7469. The usability testing yields an average score of 89%, suggesting that the system is apt for utilization, as it aligns with the functionalities users are seeking.
Co-Authors Alfry Aristo Jansen Sinlae Arisantoso Arisantoso Herdiansah, Arief Moh. Erkamim Mulyadi Rusli Nofitri Heriyani Nurdiana Handayani Popi Dayurni Rini Nuraini