Petra Christian University

About: Petra Christian University is a education organization based out in Surabaya, Indonesia. It is known for research contribution in the topics: Population & Customer satisfaction. The organization has 2412 authors who have published 2893 publications receiving 10429 citations.

Reassessing Chinese Indonesian stereotypes: two decades after Reformasi

Abstract: Historically, the Chinese community in Indonesia has been stereotyped as exclusive of the ‘indigenous’ social group; hardworking and industrious but frugal; and apolitical or lacking nationalistic ...

The Analysis of E-service Quality, Customer Trust, Perceived Value, and Behavioral Intention on Online Transportation in Surabaya

Abstract: The current number of motor vehicles in Indonesia increased very rapidly and impacted the traffic jam. Therefore, it was expected that with the increasing use of public transportation can reduce congestionproblems. Competition in the transportation industry is gotten competitive, so there is an innovation withmobile applications. But to make consumers want to use online transportation applications, companies mustunderstand about consumer behavior. Measurement of behavioral intention is the best way to predictconsumer buying behavior in the future. In this study, we wanted to know the factors that affect thebehavioral intention of online transportation consumers in Surabaya. This research used causal quantitativeresearch method. Based on the results of research conducted on 240 respondents found that e-service quality,trust and perceived value correlated significantly and positively to behavior intention. E-service quality is themost influential factor in building behavior intention compared to the other two factors.

Resampling imbalanced data to detect fake reviews using machine learning classifiers and textual-based features

Abstract: Fraudulent online sellers often collude with reviewers to garner fake reviews for their products. This act undermines the trust of buyers in product reviews, and potentially reduces the effectiveness of online markets. Being able to accurately detect fake reviews is, therefore, critical. In this study, we investigate several preprocessing and textual-based featuring methods along with machine learning classifiers, including single and ensemble models, to build a fake review detection system. Given the nature of product review data, where the number of fake reviews is far less than that of genuine reviews, we look into the results of each class in detail in addition to the overall results. We recognise from our preliminary analysis that, owing to imbalanced data, there is a high imbalance between the accuracies for different classes (e.g., 1.3% for the fake review class and 99.7% for the genuine review class), despite the overall accuracy looking promising (around 89.7%). We propose two dynamic random sampling techniques that are possible for textual-based featuring methods to solve this class imbalance problem. Our results indicate that both sampling techniques can improve the accuracy of the fake review class—for balanced datasets, the accuracies can be improved to a maximum of 84.5% and 75.6% for random under and over-sampling, respectively. However, the accuracies for genuine reviews decrease to 75% and 58.8% for random under and over-sampling, respectively. We also discover that, for smaller datasets, the Adaptive Boosting ensemble model outperforms other single classifiers; whereas, for larger datasets, the performance improvement from ensemble models is insignificant compared to the best results obtained by single classifiers.

Pembuatan aplikasi sistem pendukung keputusan untuk proses kenaikan jabatan dan perencanaan karir pada pt. x

Abstract: Fulfilling empty position on company often become complicated process because the candidate who can be placed in that position by matching between employee-profile and position-profile sometimes not well define. To minimize that problem, there should be a method such as decision support system which can analize employees who suitable with the available position. This decision support system for profile matching process and gap analization is made based on company's data and rules which locate on PT.X. Profile Matching process is taken to recommend employees in Positioning and Carrier Planning based on three stages, which are Intelectual Capacity, Working Area and Attitude. The result of this process is represented ini rank of employees as recommendation for decision maker in deciding which employee is suitable for the position.This Software is using Microsoft Access 2000 for database and Borland Delphi 5.0 as compiller. Form the result of this implementation system can be seen that this software can be very helpfull on decision support to profile matching in positioning and career planning on PT. X. Abstract in Bahasa Indonesia : Pengisian jabatan yang kosong pada proses kenaikan jabatan sering mengalami kesulitan karena pengajuan calon kandidat yang bisa menempati jabatan tersebut dengan cara pencocokan profil karyawan dan profil jabatan kurang terdefinisi dengan baik. Untuk meminimumkan kendala tersebut diperlukan suatu sistem pendukung keputusan yang dapat menganalisa beberapa karyawan yang sesuai dengan profil jabatan yang ada. Sistem pendukung keputusan untuk proses profile matching dan analisis gap ini dibuat berdasarkan data dan norma-norma SDM yang terdapat di PT. X. Proses Profile Matching dilakukan untuk menentukan rekomendasi karyawan dalam Sistem Kenaikan Jabatan dan Perencanaan Karir berdasar pada 3 aspek yaitu Kapasitas Intelektual, Sikap Kerja dan Perilaku. Hasil dari proses ini berupa ranking karyawan sebagai rekomendasi bagi pengambil keputusan untuk memilih karyawan yang cocok pada jabatan yang kosong tersebut. Software ini dibuat dengan menggunakan Microsoft Access 2000 untuk database dan Borland Delphi 5 sebagai compiller-nya. Dari hasil implementasi sistem, disimpulkan bahwa dengan penggunaan software ini dapat membantu proses pengambilan keputusan terhadap profile matching proses kenaikan jabatan dan perencanaan karir di PT. X. Kata kunci: Sistem Pendukung Keputusan, Profile Matching, Kenaikan Jabatan, Perencanaan Karir, Analisis Gap, Sistem Informasi