Andi Riyanto
@bsi.ac.id
Information of Technology
Universitas Bina Sarana Informatika
RESEARCH INTERESTS
Accounting, Auditing, Financial, Human Resources Management, Information Systems
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Agung Wibowo, Dhia Fauziah, Yuri Yuliani, Yuri Rahayu, Andi Riyanto, and Renny Oktapiani
IOP Publishing
Autistic Spectrum Disorder (ASD) can faze brain development, growth, and social behaviour. Teens with ASD tend to become bullying object. Autism can be recognized and diagnosis using a test with a questionnaire. The answers from the questionnaire usually converted into an integer value using the Linkers scale, whereas this answer still contains biased and this bias cannot be captured using this scale. Through our initial test results shows that if a user uses an answer choice slightly agree or slightly disagree, the results value is low enough it's about 6% to 20%. Autistic according to the CDC, it has eight symptoms, and we apply it to form fuzzy memberships. Previous Researchers had been shared autism screening dataset to the UCI machine learning repository, this dataset we filtered for "Who is completing the test" attribute with "self "value. We used the classification algorithms in WEKA to find a model, then this model we applied in fuzzification. This system is still a simulation study and has not been clinically tested. This system is assigned to diagnose autism based on the recognized symptoms, where the number of asked questions can vary according to needs but still refers to the symptoms. This paper proposed an autism screening test diagnosis using the fuzzy logic with a better interpellation and precision.
Bambang Pilu Hartato, Tri Astuti, Irnawati Pratika, Rizki Wahyudi, Irfan Santiko, and Andi Dwi Riyanto
IEEE
Intelligent systems currently have been proven to provide more benefits on various aspects of human life. One of them is sentiment analysis (SA) approach. SA is a mathematical approach that allows machines to analyze the opinion polarity of the statements or documents. Generally, SA is utilized to observe the tendency of public opinion on an issue. SA can also be used on e-commerce to analyze the trend of customer statements toward a product based on the reviews given by them. Thus, SA will help e-commerce business owners to know the level of acceptance toward offered products. In this paper, we try to evaluate the artificial neural network (ANN) algorithm in conducting a SA of electronic products reviews. In this study, the ANN was designed using 1 input layer, 1 hidden layer consisting of 10 neurons, and 1 output layer consisting of 2 neurons. Our experimental results showed that the ANN had a fairly high accuracy and precision while conducting SA toward electronic products reviews that have been carried out, i.e. 70.80% and 71.07% respectively. Hence, ANN is very possible to be applied to intelligent systems that are tasked to assist e-commerce business owners in conducting SA toward feedback provided by the customers.
Agung Wibowo, Yuri Rahayu, Andi Riyanto, and Taufik Hidayatulloh
IEEE
Indonesia has 13% species of mushroom in the world but there is a very limited study on determining edible or poisonous mushroom. Classification process of poisonous mushroom or not will be easily conducted by learning machine using mining data as one of the ways to extract computer assisted knowledge. Currently, there are three comparisons of the best classification algorithms in data mining, namely: Decision Tree (C4.5), NaïveBayes and Support Vector Machine (SVM). The study method used is experiment with assisted tool of WEKA that has been testing in the comparison of the three algorithms. To conduct the testing, it is used the mushroom data of Agaricus and Lepiota family. The mushroom data were taken from The Audubon Society Field Guide to North American Mushrooms, in UCI machine learning repository. Results of the testing indicate that the C4.5 algorithm has the same accuracy level to the SVM by 100% however, from the speed aspect, process of the C4.5 algorithm is faster than the SVM.
Andi Dwi Riyanto, Hendra Marcos, Zulia Karini, and Kamal Miftahul Amin
IEEE
Micro Small Medium Enterprises an important part of a country's economy. Various strategies are created through technology one of them is to determine the amount of production and inventory of goods in order to meet market needs. Fuzzy logic is a logic that is easy to understand and very flexible, it means able to adapt to the changes and certainty that accompanied the problem, so it can be implemented into an application that can optimize the inventory. The purpose of this research is to optimize the supply of goods in Pekanita by using fuzzy mamdani method on sales system, so there is no shortage of inventory and no excess goods. Pekanita is a distributor of sanitary napkin which is engaged in Micro Small Medium Enterprises.