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Journal : Compiler

SISTEM PENDUKUNG KEPUTUSANPEMILIHAN GURU TELADAN DENGAN SIMPLE ADDITIVE WEIGHTING METHOD (SAW) (STUDI KASUS DI SMA ANGKASA YOGYAKARTA) Agustian, Harliyus; Honggowibowo, Anton Setiawan; Indrianingsih, Yuliani
Compiler Vol 1, No 1 (2012): Mei
Publisher : Sekolah Tinggi Teknologi Adisutjipto Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (699.254 KB)

Abstract

Decision Support System or DSS is a system that helps managers solve problems in a semi-structured. Many of the techniques used to make the DSS, onewith Fuzzy Logic Multi-Attribute Decision Making (MADM). Fuzzy logic  is oneproblem on feelings. Where the degree  of membership is usually representedwith a value of 0 and 1, with Fuzzy Logic is the degree of membership can be represented with a value between 0 and 1, which can be more balanced. High School Angkasa Yogyakarta is a place to educate students thus the students can be useful for Nation.In realizing, the need for good quality teachers who can become role models for students, so that teaching and  learning process will be better. Thus the need assessment conducted by the student or the principal to determine the ability of ateacher, both in the process of teaching or outside the teaching process. In the process of assessment needs to consider several factors than affect teacher performance. These factor related to teaching and learning process outside the process of theaching  anyothers  on the Indonesian Government Regulation Number 74 Year 2008 about the master of pedagogical,competence, personality, social and professional.High School Angkasa in conducting an assessment to each teacher based on the result of the vote.  So , to help assist in making selection for decision support of teacher to be made SPK. DSS will use fuzzy logic techniques that apply MADM SAW method in its calculation. It is expected that DSS can be an alternativein the selection of exeplary teacher in High School Yogyakarta.
Introduction to Yogyakarta Icons in The Game of Running Challenge Bonai, Angga Adha Nugroho; Nugraheny, Dwi; Agustian, Harliyus
Compiler Vol 8, No 1 (2019): Mei
Publisher : Sekolah Tinggi Teknologi Adisutjipto Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (861.546 KB) | DOI: 10.28989/compiler.v8i1.432

Abstract

Yogyakarta's strong culture makes Yogyakarta one of the tourist areas frequented by tourists, both foreign tourists and local tourists. The Visitors come from various groups, for example visitors who come with family or individuals. A game model is needed that can facilitate the child in remembering the tourist icons in Yogyakarta through a Game Running Challenge that is made as attractive as possible and can run on the Windows operating system. The game running challenge application can provide convenience to users who are children aged 6-10 years to get to know and know the most famous icons in Yogyakarta through a game. So that it can be an educational medium that has a pattern of learning by doing learning. 
Uniform Resource Locator (URL) Detection Security System Based on Android Sajati, Haruno; Agustian, Harliyus; Murdiansyah, Eko
Compiler Vol 8, No 1 (2019): Mei
Publisher : Sekolah Tinggi Teknologi Adisutjipto Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (613.013 KB) | DOI: 10.28989/compiler.v8i1.343

Abstract

The use of the internet, which is currently increasing dramatically, certainly brings the convenience of finding information. The increase in internet usage also eventually gave rise to cybercrime crimes, one of which was by spreading a URL or fake site to steal someone's personal data. The research done is how to build an Android-based application that can detect the security of a URL. The goal is that internet users, especially social media, can avoid cybercrime crime that wants to steal personal data. Making an application uses the Regular Expression method to analyze each line of the Webpage Source Code in the URL based on 8 criteria taken from the World Wide Web Consortium (W3C). The application was then tested with 10 phishing-charged URLs and compared with Kaspersky, McAfee, and AdBlock applications. Based on the results of trials and comparisons, applications that have been made are able to detect 6 or 60% of the 10 URLs. Kaspersky and McAfee applications can detect 70%, while AdBlock only detects 3 or 30% of 10 URLs that contain phishing.