JTRISTE

ANALISIS USABILITY FITUR RATING PADA APLIKASI LADDER MENGGUNAKAN METODE SYSTEM USABILITY SCALE

2024-04-29T13:33:10+08:00

This research focuses on user experience through the Shopee Food feature, the aim is to determine the extent of the user experience of the Shopee Food feature service in several categories, namely gender, age and profession. In this research, the method used by the author is the heuristic evaluation method which consists of 10 aspect stages, which will be calculated based on the severity ratings formula for assessing. So the results obtained are: 10 aspects of this heuristic evaluation method, namely the first aspect: Visibility of System Status with a value of 7.863%, the second aspect: Match between the System and the Real World with a value of 8.063% , third aspect: User control and freedom with a value of 8.400%, fourth aspect consistency and standards with a value of 11.813%, fifth aspect: Error prevention with a value of 7.338%, sixth aspect: Understanding rather than warning (Recognition rather than recall) with a value of 7.413%, seventh aspect: Flexibility and efficiency of use (Flexibility and efficiency of use) with a value of 7.925%, eighth aspect: Aesthetic and minimalist design (Aesthetic and Minimalist Design) with a value of 6.275%, ninth aspect: Help users, recognize, diagnose and recover from awareness (Help user recognize, diagnose and recover from errors) with a value of 7.675%, tenth aspect: Help and documentation (Help and documentation) with a value of 8.063%.

ANALISIS USER EXPERIENCE PENGGUNA APLIKASI OBENKYO MENGGUNAKAN METODE HEURISTIC EVALUATION

2024-04-29T13:33:11+08:00

Nowadays the development of anime coupled with the rapid advancement of technology makes anyone can enjoy this entertainment, other Japanese popular culture products also include manga (Japanese comics), dorama (Japanese TV dramas), and Japanese popular music such as J-pop and J-rock also affect the interest in learning Japanese language and culture for young people. This research uses the Heuristic Evaluation method which is a method used to find problems in the interface design of an application and look for the positive side of the application. The data source of this research uses primary data, namely a questionnaire wheare the data collected is 15 respondents in the Makassar Jejepangan community and secondary data, namely literature studies or references from other journals. The results showed that of the 10 aspects of the Heuristic Evaluation method, there are 3 aspects that have Minor Usability Problems or there are problems that interfere with user comfort with a severity rating value of 2, or improvements are needed with a low priority level. And the other 7 aspects are worth 1 or Cosmetic Problem meaning only problems that do not affect users, and there are no aspects with a value of 0 or Don't Agree which means there are no problems at all. User Experience of Obenkyo users in the Makassar jejepangan community shows that there are more male Obenkyo users than female and some users also feel satisfied using this application.

IMPLEMENTASI DATA MINING MENGGUNAKAN ALGORITMA APRIORI PADA TOKO RUMAH SKINCARE 88

2024-04-29T13:33:12+08:00

The purpose of this research is to implement the apriori algorithm on sales transaction data of cosmetic products at Rumah Skincare 88 store so that it can help develop marketing strategies and increase sales at the store. The results of this study are that the apriori algorithm was successfully implemented on the sale of cosmetic products at the RumahSkincare88 store. The support values used are 3% and 10% and the minimum confidence values are 30% and 50%. The number of association rules generated is 17 with the highest support value of 14% and the highest confidence of 53.4%. The resulting association rule with the highest support and confidence value is if consumers buy Powder/Foundation then they will also buy Lips. The recommended marketing strategies are Cross-Selling and Bundling. For Cross-Selling strategy that can be applied is if consumers buy Powder/Foundation, then when they want to pay the cashier can offer to buy Lips as well. As for Bundling, the strategy that can be applied is to sell Face Serum and Sunscreen in one package at a special price.

REKOMENDASI LAPTOP TERHADAP CALON PEMBELI PT. GENIUS COMPUTER CENTRE MENGGUNAKAN SIMPLE ADDITIVE WEIGHTING

2024-04-29T13:33:13+08:00

This research aims to implement the Simple Additive Weighting (SAW) method in providing recommendations to potential laptop buyers at PT.Genius Computer Centre. Various laptop variants with different brands and specifications make it difficult for potential buyers to choose a laptop that suits their needs. The implementation of the SAW method is used as a basis for recommending laptops based on user requirements. SAW is a commonly used method in decision-making and involves assessments based on predefined criteria weights. The results of the SAW calculations provide recommendations for laptops that meet the user's needs, helping potential buyers choose a laptop that fits their requirements. The implementation of the SAW method in the decision support system can address the difficulties faced by potential laptop buyers at PT. Genius Computer Centre in choosing a suitable laptop and provide recommendations that can enhance their understanding of the required laptop specifications. This research has the potential to significantly improve the laptop shopping experience for potential buyers.

PERBANDINGAN ALGORITMA RANDOM FOREST DAN ARTIFICIAL NEURAL NETWORK UNTUK DATASET WATER POTABILITY

2024-04-29T13:33:14+08:00

Water is an important element that is a basic need for the survival of all living things. Currently, public awareness about the importance of good quality water is increasing. This is due to a wider understanding of the health impacts of unclean water. Water that is clean and safe to use not only has a positive impact on our health, but also on various aspects of daily life. Therefore, research on the quality and suitability of water for consumption is very important. The aim of this research is to determine the best method for comparing water quality for suitability for consumption. This research compares two machine learning methods, namely Random Forest and Artificial Neural Network (ANN) based on attributes for the suitability of drinking water, namely: PH, hardness, solids, chloramines, sulfate, conductivity, organic carbon, trihalomethanes, turbidity and potability. The research results show that the Random Forest algorithm has an accuracy rate of 67.823%, while the Artificial Neural Network (ANN) algorithm achieves an accuracy of 61.014%. From these results, it can be concluded that the Random Forest algorithm has higher accuracy compared to Artificial Neural Network (ANN).

PERBANDINGAN METODE KLASIFIKASI RANDOM FOREST DAN SUPPORT VECTOR MACHINE TERHADAP DATASET RESIKO KANKER SERVIKS

2024-04-29T13:33:16+08:00

Cervical cancer is a significant global health issue, representing a type of cancer that develops from the cells of the cervix. This research focuses on comparing the effectiveness of two classification methods, namely Random Forest (RF) and Support Vector Machine (SVM), in assessing the risk of cervical cancer. Utilizing relevant datasets, the study aims to identify the strengths and weaknesses of each method and evaluate their ability to provide predictions of cervical cancer risk. Through comparative analysis, it is anticipated that this research will offer valuable insights for the development of more efficient methods for assessing the risk of cervical cancer. The results of this study are expected to contribute to a deeper understanding of the performance comparison between Random Forest and SVM in the context of assessing the risk of cervical cancer, opening opportunities for the optimal application of classification methods in efforts for the prevention and early detection of this disease.