Library Binus

The Inﬂuence of Perceived Risk and Trust in Adoption of FinTech Services in Indonesia

Meyliana

The service level in community must be consideredifitwantstocontinuetobeusedbytheusers.This research studies the adoption of Financial Technology (FinTech) services in the terms of trust and risk. The work employs the Technology Acceptance Model (TAM) theory as the theoretical basis combined with trust and perceived risk. The research method is quantitative. The data are analyzed by the Structural Equation Model (SEM) using Smart PLS V2.0. The researchers use a questionnaire in Google Form to collect the data. It is distributed online with the snowball data collection technique. As a result, 548 respondents are successfully gathered. The results indicate that the factor of users trusts inﬂuences perceived usefulness in the adoption to use FinTech services. However, the risk factor does not affect the use of FinTech services, which further does not inﬂuence the users’ attitude. The work contributes to the study of the adoption of FinTech services, which provides a view determining the users’ intention to use FinTech services in Indonesia.

A Survey on Mixed-Attribute Outlier Detection Methods

Nur Rokhman

In the data era, outlier detection methods play an important role. The existence of outliers can providecluestothediscoveryofnewthings,irregularities in a system, or illegal intruders. Based on the data, outlierdetectionmethodscanbeclassiﬁedintonumerical, categorical, or mixed-attribute data. However, the study of the outlier detection methods is generally conducted for numerical data. Meanwhile, many real-life facts are presented in mixed-attribute data. In this paper, the researcher presents a survey of outlier detection methods for mixed-attribute data. The methods are classiﬁed into four types, namely, categorized, enumerated, combined, and mixed outlier detection methods for mixed-attribute data. Through this classiﬁcation, the methods can be easily analyzed and improved by applying appropriate functions.

Javanese Document Image Recognition Using Multiclass Support Vector Machine

Yuna Sugianela

Some ancient documents in Indonesia are written in the Javanese script. Those documents contain the knowledge of history and culture of Indonesia, especially about Java. However, only a few people understand the Javanese script. Thus, the automation system is needed to translate the document written in the Javanese script. In this study, the researchers use the classiﬁcation method to recognize the Javanese script written in the document. The method used is the Multiclass Support Vector Machine (SVM) using One Against One (OAO) strategy. The researchers use seven variations of Javanese script from the different document for this study. There are 31 classes and 182 data for training and testing data. The result shows good performance in the evaluation. The recognition system successfully resolves the problem of color variation from the dataset. The accuracy of the study is 81.3%.

A Comparison of Machine Learning Algorithms in Manufacturing Production Process

Rosalina

This research aims to improve the productivity and reliability of incoming orders in the manufacturing process. The unclassiﬁed data attributes of the incoming order can affect the order plan which will impact to the low productivity and reliability in the manufacturing process. In order to overcome the problem, machine learning algorithms are implemented to analyze the data and expected to help the manufacturing process in deciding the incoming order arrangement process. Four machine learning algorithms are implemented (DecisionTree,NaveBayes,SupportVectorMachine,and Neural Network). These machine learning algorithms are compared by their algorithm performance to the manufacturing process problem. The result of the research shows that machine learning algorithms can improve the productivity and reliability rate in production area up to 41.09% compared to the previous rate without any dataset arrangement before. The accuracy of this prediction test achieves 97%.

A Comparison of Machine Learning Algorithms in Manufacturing Production Process

Rosalina

Segmentation of Tuberculosis Bacilli Using Watershed Transformation and Fuzzy C-Means

Rahadian Kurniawan

The easily transmitted Tuberculosis (TB) disease is attributed to the fact that Mycobacterium Tuberculosis (MTB) bacteria/viruses can be transmitted through the air. One of the methods to screen the TB disease is by reading sputum slides. Sputum slides are colored sputum samples of TB patients placed on microscopic slides. However, TB disease microscopic analysis has some limitations since it requires high accuracy reading and well-trained health personnel to avoid errors intheprocessofinterpretation.Furthermore,thenumber of TB patients in the Primary Health Care (PHC) and the process of manual calculation of bacteria in a ﬁeld of view often complicate the decision-making in the screening process conducted by the medical staffs. In this paper, the researchers propose the use of Watershed Transformation and Fuzzy C-Means combination to help solve the problem. The researchers collect the photo shooting of three PHC in Indonesia with 55 images of sputum from different TB patients. The assessed results of the proposed method are compared with the opinions of three Microbiology doctors. The comparison shows Cohen’s Kappa Coefﬁcient value of 0.838. It suggests that the proposed method can detect Acid Resistant Bacteria (ARB) although it needs some improvement to achieve higher accuracy.

Mapping Irrigation Networks with Geographical Information Systems Using Satelite Imagery Data: A Case of Brebes Regency, Indonesia

Aulia Azhar Abdurachman

Water resources are important factors in food production. Those are very vital and strategic to meet food needs and food security. As water is scarce both in terms of volume and distribution throughout the year, reliable water management is needed. To support this water management, the accurate data is needed. However, the complete tabular data is not enough. It is because the existing tabular data does not provide the various activities and events based on time and place spatially and detail enough for planning purposes at the sub-district level. The researchers use high-resolution satellite imagery data that have been pre-processed with the geometric and radiometric corrections. They are used as one of the layers in the working map, so it is easier to provide the depiction of irrigation network objects, to ﬁnd out the location of rice ﬁelds that have not been irrigated and the location of damaged irrigation networks. The depiction of the working map can also be used to map irrigation networks and their network conditions. Through this work, it has been shown that the researchers can map irrigation networks in detail for operational planning at a sub-district level with the help of technology, in particular for developing countries that is difﬁcult or even impossible to do in the past

Analisis IRIO dalam Pengembangan Industri pada Era Otonomi Daerah

Putri Kartika

Analisis Dampak Kebijakan Harga Energi terhadap Perekonomian dan Distribusi Pendapatan di DKI Jakarta Aplikasi Model Komputasi Keseimbangan Umum

Djoni Hartono

Rekayasa Kebutuhan Perangkat Lunak E-Marketplace Gerobak Kopi