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All Journal Jurnal Informatika Jurnal Sarjana Teknik Informatika JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Insect (Informatics and Security) : Jurnal Teknik Informatika IJISTECH (International Journal Of Information System & Technology) Building of Informatics, Technology and Science Infotech: Journal of Technology Information Jurnal Teknik Informatika (JUTIF) IJISTECH JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Murien Nugraheni
Program Studi Teknik Informatika Universitas Ahmad Dahlan Yogyakarta Jl. Prof. Dr. Soepomo, S.H., Warungboto, Janturan, Yogyakarta 55164 Telp : (0274) 563515 ext. 3208
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Social Sciences

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MULTI-CRITERIA DECISION ANALYSIS USING COMPLEX PROPORTIONAL ASSESSMENTS AND RANK ORDER CENTROID METHODS IN THE SELECTION SYSTEM FOR TUTORING INSTITUTIONS Fatmayati, Fryda; Nuraini, Rini; Nugraheni, Murien; Soares, Teotino Gomes
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 5 (2023): JUTIF Volume 4, Number 5, October 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.5.1340

Abstract

Tutoring can help increase students' self-confidence, reduce anxiety about tests or assignments, and overcome learning barriers. The large number of tutoring institutions that offer various programs makes parents or students have to be observant when choosing them. To choose a tutoring institution, parents or students must know all the profiles and programs of the institution to be selected. This creates a difficult and long time to come up with a choice. The purpose of this study is to use the Multi Criteria Decision Analysis (MCDA) approach through the Complex Proportional Assessment (COPRAS) method and the Rank Order Centroid (ROC) method to create a Decision Support System (DSS) that will make it easier to choose a tutoring institution. The ROC approach serves to determine the weight based on the order of importance of the criteria. The COPRAS method is used because this method takes utility into account by assessing the usefulness of each alternative. This research produced a web-based tutoring institution selection DSS that can provide alternative recommendations based on criteria determined by decision-makers. The results of system calculations and manual calculations do not show a different value, which shows that the system produces a valid COPRAS approach value. Based on the results of usability testing, the built DSS scored 89.17%; in other words, the system is feasible to use.
K-anonymity Menggunakan Simple Distribution of Sensitive Values dan Aggregation of Sensitive Values Widodo, Widodo; Duskarnaen, Muhammad Ficky; Nugraheni, Murien
Jurnal Teknik Informatika dan Sistem Informasi Vol 10 No 2 (2024): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v10i2.8798

Abstract

Anonymizing microdata is a matter while the microdata is published or shared. The purpose of anonymization is sothat sensitive data will not be known by unauthorized parties either directly or indirectly. The technique that is widely used isgeneralization and suppression in the k-anonymity model, however, this technique has the disadvantage that the level of information loss is quite high. In addition, the generated microdata representation due to anonymization is too large, thus it needs to be simplified. In this research, an anonymity model is built using a sensitive attribute distribution technique, namely Simple Distribution of Sensitive Values (SDSV). The main purpose of this method is to reduce the probability of unauthorized parties guessing the owner of sensitive data. Meanwhile, to simplify the representation of the microdata, the aggregative of sensitive value (ASENVA) technique is applied. The result shows that the SDSV metho has less information loss compared to others, while the use of ASENVA simplifies the representation of anonymized tables to an average of 13.67% for aggregated quasi-identifier tables and 6.35% for sensitive tables.
Co-Authors Ajie, Hamidillah Ali Idrus Amannu, Ramadhan Duskarnaen, Muhammad Ficky Effendy, Vina Ardelia Fryda Fatmayati Hartono, Muhammad Adryan Ika Arfiani Mumtas, Fuad Praha, Tohpatti Crippa Rini Nuraini, Rini Rossi, Farli Siti Nurhayati Soares, Teotino Gomes Subhiyanto, S Sugiyanta, Lipur Sulistyono, Danang Tonggiroh, Mursalim Uning Lestari Widodo Widodo Yunanto, Prasetyo Wibowo