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Journal : IJISTECH (International Journal Of Information System

Software Usability Measurement Inventory for Student Information Academic System at Politeknik Negeri Media Kreatif Yuyun Khairunisa; Sari Setyaning Tyas; Adnan Purwanto; Siti Aisyah
IJISTECH (International Journal of Information System and Technology) Vol 4, No 1 (2020): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1291.164 KB) | DOI: 10.30645/ijistech.v4i1.96

Abstract

Academic information system is a system that is urgently needed by universities to manage academic business processes. State Polytechnic of Creative Media implements SIAM as Student Information Academic System. SIAM being developed has the advantage of being able to convey more detailed information. In addition, SIAM has implemented the SSO (Single Sign On) system where this technology is in great demand, especially in very large and heterogeneous networks. In this research Software Usability Measurement Inventory (SUMI) methods used to conduct usability test. SUMI is a rigorously tested and proven method of measuring software quality from the end user's point of view. The analysis results from SUMI will be used to improve the development of the academic system life cycle.
The Mapping Model is in the form of Clustering of Workers' Hourly Wages by Region in Indonesia using the K-Means Method S Suhendra; Siti Aisyah
IJISTECH (International Journal of Information System and Technology) Vol 4, No 1 (2020): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (639.631 KB) | DOI: 10.30645/ijistech.v4i1.92

Abstract

Wages are a very important element in manpower activities because the main purpose of working people is to get wages or salaries which will be used to meet daily needs. The hourly wage system for workers in the Province affects the wages received by workers. The research objective is to create a cluster model of the hourly wages of workers in Indonesia by region. The data used in the mapping is data on workers' hourly wages for 2017-2018, which are managed by the Central Statistics Agency (abbreviated as BPS). The technique used is clustering with the k-means method, which is part of data mining. This process uses two cluster labels, namely the high wage cluster (C1) and the low wage cluster (C2), with a maximum Davies Bouldin value of 0.490. The research results were obtained from 34 regions in Indonesia, twenty-seven provinces were in the low category cluster (C2), and seven provinces were in the high category (C1). This can be used as input for the provincial government to make policies on hourly wages in Indonesia that have an impact on the welfare of the community.