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INDONESIA
Indonesian Journal of Information System
Published by Universitas Atma Jaya Yogyakarta
ISSN : 26230119     EISSN : 26232308     DOI : -
Core Subject : Science,
Computer Science & IT
Arjuna Subject : -
Articles 9 Documents
 1 
Search results for , issue "Vol 2, No 1 (2019): Agustus 2019" : 9 Documents clear
Push Pull Mooring dan Pyschological Ownership terhadap Perilaku Beralih Pengguna Instant Messaging Djusmin, Vicky; Dirgahayu, Raden Teduh
Indonesian Journal of Information Systems Vol 2, No 1 (2019): Agustus 2019
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (800.521 KB) | DOI: 10.24002/ijis.v2i1.2013

Abstract

Hasil survei tentang perilaku pengguna Mobile Instant Messaging (MIM) di Indonesia menjelaskan bahwa terjadi arus migrasi pengguna MIM. Perilaku beralih mengakibatkan penurunan pengguna dan profitabilitas layanan pada MIM yang ditinggalkan. Untuk itu diperlukan sebuah pemahaman tentang faktor-faktor yang mempengaruhi individu yang beralih. Penelitian ini bertujuan untuk mengetahui efek pendorong, penarik, serta penambat terhadap niat dan perilaku beralih pengguna MIM. Kepemilikan psikologis sebagai anteseden yang mempengaruhi faktor penghambat. Dalam penelitian ini, Push Pull Mooring digunakan sebagai kerangka untuk mengevaluasi hubungan variabel. Pengujian menggunakan Structural Equation Modelling jenis PLS (SEM-PLS). Hasil penelitian menjelaskan bahwa Dissatisfaction terbukti mendorong individu untuk beralih MIM sedangkan Low System Quality bukan faktor pendorong beralih MIM. Alternative Attractiveness dan Subjective Norm terbukti sebagai penarik pada MIM alternatif. Commitment Affective yang sebelumnya diyakini sebagai faktor penambat beralih, tidak terbukti. Hasil evaluasi ini dapat menjadi acuan penyedia layanan MIM dalam mengembangkan fungsionalitas layanan sebagai upaya mempertahankan pengguna serta menarik pengguna baru.
Planning of Higher Education Information Technology Strategy Using TOGAF (A Case Study at AMN Cilacap) Prayitno, Oktavianus Teguh
Indonesian Journal of Information Systems Vol 2, No 1 (2019): Agustus 2019
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (572.73 KB) | DOI: 10.24002/ijis.v2i1.2349

Abstract

Information technology that develops along with the rapid role of communication through the Internet makes technology and information systems have a position that is vital for the business alignment of an institution including higher education institutions. The strategic planning of this sector has a goal to develop the basis / guidelines in developing and developing information technology and systems to support organizational goals and increase increasingly competitive competitive advantage. Thus, the integration between business and information technology becomes important to support the competitiveness of institutions. The responsibility of Enterprise Architecture (EA) is to provide an accurate and fast information system based on the business demands of the institution. Appropriate standards and models are needed by higher education institutions to improve the alignment of business strategies and information technology. This study will explore the problems faced by AMN Cilacap and provide the development of information technology and systems needed to use EA using the Open Group Architecture Framework (TOGAF) methodology. TOGAF provides methods and tools to assist in the receipt, production, use and maintenance of corporate architecture.
The Effect of Internet Slack on Learning Performance Hariwibowo, Ignatius Novianto
Indonesian Journal of Information Systems Vol 2, No 1 (2019): Agustus 2019
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (345.274 KB) | DOI: 10.24002/ijis.v2i1.2142

Abstract

In the midst of the widespread application of the internet in learning activities, this research was conducted to assess the impact of internet abuse on classroom learning outcomes. Published research shows the impact of diverse internet uses and this study aims to show the consequences of internet abuse on learning outcomes. This research was conducted on accounting class students with a hybrid learning system, where learning is done face-to-face in class but is supported by e-learning technology. The respondents of this study were 224 accounting students. Data were taken using questionnaires and 216 questionnaires were processed using SEM-PLS. The results of this study indicate that internet abuse does not moderate the influence of interaction and social presence on classroom learning performance. These findings indicate that internet abuse is not a factor that decreases student learning performance and can be an input for the design of e-learning concepts to use the internet as an interactive learning media where activities can still be controlled.
Back Matter Nastiti, Putri
Indonesian Journal of Information Systems Vol 2, No 1 (2019): Agustus 2019
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (682.417 KB) | DOI: 10.24002/ijis.v2i1.2491

Abstract

Medicine Inventory Grouping using Clustering Data Mining Nugraha, Joanna Ardhyanti Mita
Indonesian Journal of Information Systems Vol 2, No 1 (2019): Agustus 2019
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (616.71 KB) | DOI: 10.24002/ijis.v2i1.2340

Abstract

One of the main factors in health services is adequate medicine supplies. Puskesmas is one of the health services that is managed under the district and city health offices to serve patients every day. However, there are obstacles in the process of medicine supply at the Puskesmas. Puskesmas still uses medicine supply techniques manually by looking at the minimum medicine stock. In this way, many medicines are unused and even lacking. The application of data mining can be used as an analysis to determine the medicine supply according to the patient's needs. In the data mining method, the clustering algorithm is one of the most popular to use where the data belonging to the same cluster will be close to each other and will be far from the data about another cluster. For this reason, this study used clustering to classify types of medicines based on the number of medicine uses and requests. The results are obtained in the form of information on the type of medicine with rapid use and model of m with extended usage every month taken from three years of data. Also, information on the types of medicines from the clustering process can be used to improve better patient service.
Front Matter Nastiti, Putri
Indonesian Journal of Information Systems Vol 2, No 1 (2019): Agustus 2019
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1974.543 KB) | DOI: 10.24002/ijis.v2i1.2493

Abstract

Central Actor Identification of Crime Group using Semantic Social Network Analysis Tahalea, Sylvert Prian; SN, Azhari
Indonesian Journal of Information Systems Vol 2, No 1 (2019): Agustus 2019
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (703.262 KB) | DOI: 10.24002/ijis.v2i1.2354

Abstract

The Police as law enforcers who authorize in terms of social protection are expected to do both the prevention and investigation efforts also the settlement of criminal cases that occurred in the society. This research can help police to identify the main actor faster and leads to solving crime-cases. The use of overall centrality is very helpful in determining the main actors from other centrality measures. The purpose of this research is to identify the central actor of crimes done by several people. Semantic Social Network Analysis is used to perform central actor identification using five centrality measurements, such as degree centrality, betweenness centrality, closeness centrality, eigenvector centrality, and overall centrality. As for the relationship between actors, this research used social relation such as friendship, colleague, family, date or lover, and acquaintances. The relationship between actors is measured by first four centrality measures then accumulated by overall centrality to determine the main actor. The result showed 80.39% accuracy from 102 criminal cases collected with at least 3 actors involved in each case.
Parents’ Sum of Salaries Analyses towards School Tuition Fee Arrears Potential with Decision Tree Method Iskandar, Iqbal Dzulfiqar
Indonesian Journal of Information Systems Vol 2, No 1 (2019): Agustus 2019
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (736.538 KB) | DOI: 10.24002/ijis.v2i1.2168

Abstract

School tuition fee is typically used for funding school operational, i.e. paying honorary teachers in public and private schools, purchasing practical instruments, printing examination worksheets, and other net-operational costs. According to the discovered data in the research environment, the funding is unable to be acquired properly due to students’ school tuition fees arrears for months even years until they graduate. Considering the condition, this research is conducted to identify the potential of students’ school tuition arrears, based on the sum of their parents’ salaries centered on the business intelligence approach, using the decision tree method. The analysis results show that, students whose parents’ income is less than Rp 672.500,00 will be potentially in arrears with school tuition more than  Rp 900.000,00 each month, while students whose parents’ income is above Rp 672.500,00 are potentially in arrears of less than Rp 900.000,00 or not in arrears. To evaluate the effectiveness of the decision tree algorithm for data processing, it has an accuracy value of 95.97%, with a precision of 94.96% that means the algorithm has a good correlation based on attributes and the data that have been processed by the algorithm.
Application of K-Nearest Neighbor Algorithm on Classification of Disk Hernia and Spondylolisthesis in Vertebral Column Handayani, Irma
Indonesian Journal of Information Systems Vol 2, No 1 (2019): Agustus 2019
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (544.168 KB) | DOI: 10.24002/ijis.v2i1.2352

Abstract

Vertebral column as a part of backbone has important role in human body. Trauma in vertebral column can affect spinal cord capability to send and receive messages from brain to the body system that controls sensory and motoric movement. Disk hernia and spondylolisthesis are examples of pathologies on the vertebral column. Research about pathology or damage bones and joints of skeletal system classification is rare whereas the classification system can be used by radiologists as a second opinion so that can improve productivity and diagnosis consistency of the radiologists. This research used dataset Vertebral Column that has three classes (Disk Hernia, Spondylolisthesis and Normal) and instances in UCI Machine Learning. This research applied the K-NN algorithm for classification of disk hernia and spondylolisthesis in vertebral column. The data were then classified into two different but related classification tasks: “normal” and “abnormal”. K-NN algorithm adopts the approach of data classification by optimizing sample data that can be used as a reference for training data to produce vertebral column data classification based on the learning process. The results showed that the accuracy of K-NN classifier was 83%. The average length of time needed to classify the K-NN classifier was 0.000212303 seconds.

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