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Sisforma: Journal of Information Systems
Published by Universitas Katolik Soegijapranata
ISSN : 23558253     EISSN : 24427888     DOI : 10.24167
Core Subject : Science, Education, Engineering,
Computer Science & IT Education Engineering Library & Information Science
SISFORMA journal published by the Information Systems Studies Program Faculty of Computer Science Soegiapranata Semarang. to accommodate the scientific writings of the ideas or studies related to information systems. Scope journal Sisforma: Topics that will be published in the journal SISFORMA include (but not only in the limit in these topics only): Education and Curriculum, Game Theory and Game Technology, General topic in Information System, E-business, ERP, CMS, Artificial Intelligence and Enterprise System Information, Network and Computer Security, and Information Technology
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 6 Documents
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Search results for , issue "Vol 6, No 2: November 2019" : 6 Documents clear
Javanese Gender Speech Recognition Based on Machine Learning Using Random Forest and Neural Network Kristiawan Nugroho
SISFORMA Vol 6, No 2: November 2019
Publisher : Soegijapranata Catholic University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (543.547 KB) | DOI: 10.24167/sisforma.v6i2.2402

Abstract

Speech is a means of communication between people throughout the world. At present research in the field of speech recognition continues to develop in producing a robust method in various research variants. However decreasing the word error rate or reducing noise is still a problem that is still being investigated until now. The purpose of this study is to find the right method with high accuracy to classify the gender voices of Javanese. This research used a human voice dataset of both men and women from the Javanese tribe which was recorded and then processed using a noise reduction preprocessing technique with the MFCC extraction feature method and then classified using 2 machine learning methods, namely Random Forest and Neural Network. Evaluation results indicate that the classification of Javanese accent speech accents results in an accuracy rate of 91.3 % using Random Forest and 92.2% using Neural Network.
Recommendation System of Information Technology Jobs using Collaborative Filtering Method Based on LinkedIn Skills Endorsement Latifah Diah Kumalasari; Ajib Susanto
SISFORMA Vol 6, No 2: November 2019
Publisher : Soegijapranata Catholic University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (605.851 KB) | DOI: 10.24167/sisforma.v6i2.2240

Abstract

Students who are graduated from Informatics Engineering have wide employment opportunities in the information technology work field, such as database administrator, data scientist, UI designer, IT project manager, network engineer, system analyst, software engineer and UX designer. Each job in Information Technology field has different skill requirement for the interest of work field. Therefore, IT skill classification is needed to find out the suitable career recommendation for Informatics Engineering students. Data from IT professionals which are obtained from LinkedIn account of IT professionals will be processed as reference for students. Data are processed using K-Means Clustering algorithm to find out how is feasible IT professionals data are used as a reference. Then, Collaborative Filtering method by the K-NN algorithm is used to determine classification based on the proximity between student skills and information technology job field. The output is recommendation of information technology job field which are generated from calculate of IT student skills. Result has been tested by testing one of user that has been labeled software engineer produce a recommendation output as a software engineer.
Motion Recognition and Students’ Achievement Wen-Fu Pan; Anton Subarno; Mei-Ying Chien; Ching-Dar Lin
SISFORMA Vol 6, No 2: November 2019
Publisher : Soegijapranata Catholic University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (426.976 KB) | DOI: 10.24167/sisforma.v6i2.2468

Abstract

Human motion has multifarious meanings that can be recognized using a facial detection machine. This article aims to explore body motion recognition to explain the relationship between students’ motions and their achievement, as well as teachers’ responses to students’ motions, and especially to negative ones. Students’ motions can be identified according to three categories; facial expression, hand gestures, and body position and movement. Facial expression covers four categories, namely, contempt, fear, happiness, and sadness. Contempt is used to express conflicted feelings, fear to express unpleasantness, happiness to express satisfaction, and sadness to express that the environment is uncomfortable. Hand gestures can likewise be grouped into four categories: conversational gestures, controlling gestures, manipulative gestures, and communicative gestures. Conversational gestures refer to communicative gestures. Controlling gestures refer to vision-based interface communications, like the ones popular in current technology. Manipulative gestures refer to ones used in human interaction with virtual objects. Communicative gestures relate to human interaction, and therefore involve the field of psychology. Body position and movement also can be classified into four categories, namely: leaning forward, leaning backward, correct posture, and physical relocation. Leaning forward happens when a user is working with a high level of concentration. Leaning backward occurs when a user has been highly concentrated on work for several hours, and needs a break or change. Correct posture is the sign of an enjoyable working position which involves sitting in a free and relaxed manner. Movement refers to a change to the student’s sitting location, reflecting some inadequacy of the learning environment. Teachers can anticipate changes of students’ emotions by good learning design, teaching metacognitive skills, self-regulated performance, exploratory talks, mastery approach/avoidance, using hybrid learning environments, and controlling space within classrooms. Teachers’ responses to students’ motions will be explored in this article
An Application for Alumni of Soegijapranata Catholic University Hanna Mulianawati; Ridwan Sanjaya; FX Hendra Prasetya
SISFORMA Vol 6, No 2: November 2019
Publisher : Soegijapranata Catholic University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (553.516 KB) | DOI: 10.24167/sisforma.v6i2.1436

Abstract

Sometimes it’s hard for the university to get the information about their own alumni after the graduation ceremony. The situation of the alumni is also the same. They felt difficult to reach their university after they got a job. Some services and documents are still needed by the alumni for any reason. In fact, people nowadays live with their smartphone really closely. The smartphone could help people to get information and services while keeping them close to their community. The mobile application should be built to connect alumni and university through a smartphone via information sharing about job vacancy and providing some university’s services. Some methods are used in the process of mobile application development, such as designing the application, programming, testing, and launching. Interview and survey are done to know the responses in using the application. The conclusions of the research are the application could help the alumni to get information and services, the university is able to gain the updated data of their alumni, and make both of them closer.
Designing Web-Based DISC Psychology Personality Analysis Tests Daniel Aditama Somatdie; Erdhi Widyarto; Alb. Dwiyoga Widiantoro
SISFORMA Vol 6, No 2: November 2019
Publisher : Soegijapranata Catholic University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (904.968 KB) | DOI: 10.24167/sisforma.v6i2.2156

Abstract

Using a manual system in the companies or organizations today, has many disadvantages like inefficient, wasting time, require a lot of costs, and make work difficult. By integrating a DISC personality analytical psychological test with information system, the tests are carried out with computers initially using paper, so it more economical for using less paper. More than that, the test results are done automatically check by the computer, no need to manually check by the psychologist. In addition to being effective in examining, the validation of examinations is very high because it can recover human errors.
Analysis and Design of Waste Management System Using the Spiral Model Towards Smart Cities N. Tri Suswanto Saptadi; Phie Chyan; Andrew Christhoper Pratama
SISFORMA Vol 6, No 2: November 2019
Publisher : Soegijapranata Catholic University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (865.189 KB) | DOI: 10.24167/sisforma.v6i2.2313

Abstract

IT Governance has provided hope in human life, especially waste management and environmental cleanliness services. The role of IT becomes very important when people want services that are fast, accurate and relevant. Technology using Geographic Information Systems (GIS) has provided opportunities and made it possible to interact easily. The purpose of this research is to provide a GIS for the city environmental and sanitation services in order to provide good services in creating a clean environment. The research method uses the system analysis method with a spiral model approach in system design. The results of the design of GIS have been able to improve the performance of waste management in the city of Makassar.

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