IMPLEMENTASI METODE AHP PADA SISTEM PENDUKUNG KEPUTUSAN PARIWISATA JAWA TIMUR

Perubahan perilaku wisatawan dalam berwisata dengan bantuan perangkat digital salah satunya adalah perencanaan wisata, contohnya yaitu menentukan destinasi wisata. Pemilihan destinasi wisata yang bervariasi di Provinsi Jawa Timur oleh para calon wisatawan dapat dipermudah guna meningkatkan strategi manajemen pariwisata. Penelitian ini bertujuan untuk menghasilkan Sistem Pendukung Keputusan atau Decision Support System (DSS) berbasis website yang dapat mempermudah wisatawan dalam menentukan pilihan destinasi pariwisata di wilayah Jawa Timur. Sebagai metode pengambilan keputusan, Analytical Hierarchy Process (AHP) diterapkan. Metode System Development Life Cycle (SDLC) yang meliputi tahap perencanaan, analisis, desain, dan produksi serta pengujian dan implementasi, digunakan dalam mengembangkan Sistem Pendukung Keputusan. Pengujian khusus sistem dan user-testing menunjukkan bahwa seluruh fungsionalitas yang diuji bekerja dengan baik dengan black box testing, sedangkan user-testing menunjukkan bahwa 87,13% pengguna setuju bahwa sistem ramah pengguna.

Investigation of Widely Used SLAM Sensors Using Analytical Hierarchy Process

Applications of mobile robots are continuously capturing the importance in numerous areas such as agriculture, surveillance, defense, and planetary exploration to name a few. Accurate navigation of a mobile robot is highly significant for its uninterrupted operation. Simultaneous localization and mapping (SLAM) is one of the widely used techniques in mobile robots for localization and navigation. SLAM consists of front- and back-end processes, wherein the front-end includes SLAM sensors. These sensors play a significant role in acquiring accurate environmental information for further processing and mapping. Therefore, understanding the operational limits of the available SLAM sensors and data collection techniques from a single sensor or multisensors is noteworthy. In this article, a detailed literature review of widely used SLAM sensors such as acoustic sensor, RADAR, camera, Light Detection and Ranging (LiDAR), and RGB-D is provided. The performance of SLAM sensors is compared using an analytical hierarchy process (AHP) based on various key indicators such as accuracy, range, cost, working environment, and computational cost.

Multiple ratiometric nanothermometry using semiconductor BiFeO3 nanowires and quantitative validation of thermal sensitivity

Here, we report a very sensitive, non-contact, ratio-metric, and robust luminescence-based temperature sensing using a combination of conventional photoluminescence (PL) and negative thermal quenching (NTQ) mechanisms of semiconductor BiFeO3 (BFO) nanowires. Using this approach, we have demonstrated the absolute thermal sensitivity of ~ 10 mK−1 over the 300–438 K temperature range and the relative sensitivity of 0.75% K−1 at 300 K. Further, we have validated thermal sensitivity of BFO nanowires quantitatively using linear regression and analytical hierarchy process (AHP) and found close match with the experimental results. These results indicated that BFO nanowires are excellent candidates for developing high‐performance luminescence-based temperature sensors. Graphical abstract

Knowledge Management Model for Smart Campus in Indonesia

The application of smart campuses (SC), especially at higher education institutions (HEI) in Indonesia, is very diverse, and does not yet have standards. As a result, SC practice is spread across various areas in an unstructured and uneven manner. KM is one of the critical components of SC. However, the use of KM to support SC is less clearly discussed. Most implementations and assumptions still consider the latest IT application as the SC component. As such, this study aims to identify the components of the KM model for SC. This study used a systematic literature review (SLR) technique with PRISMA procedures, an analytical hierarchy process, and expert interviews. SLR is used to identify the components of the conceptual model, and AHP is used for model priority component analysis. Interviews were used for validation and model development. The results show that KM, IoT, and big data have the highest trends. Governance, people, and smart education have the highest trends. IT is the highest priority component. The KM model for SC has five main layers grouped in phases of the system cycle. This cycle describes the organization’s intellectual ability to adapt in achieving SC indicators. The knowledge cycle at HEIs focuses on education, research, and community service.

SISTEM PENDUKUNG KEPUTUSAN Implementasi Metode Analytical Hierarchy Process (AHP) Untuk Proses Kenaikan Jabatan Karyawan

Kajian dalam buku ini bertujuan untuk mengetahui Sistem pendukung keputusan kenaikan jabatan yang dirancang telah memiliki nilai ketetapan dalam penentuan promosi jabatannya. Bagi karyawan yang memiliki nilai lebih kecil dari enam (6) maka karyawan dinyatakan tidak layak untuk dipromosikan kenaikkan jabatannya dan sebaliknya jika karyawan memiliki nilai lebih besar dari 6 maka karyawan dinyatakan layak untuk dipromosikan kenaikkan jabatannya. Dan untuk karyawan yang memiliki nilai paling tinggi yang akan mendapatkan promosi kenaikkan jabatannya. Dengan system pendukung keputusan kenaikan jabatan karyawan Yang akan diterapkan secara komputerisasi nantinya memungkinkan efisiensi waktu dan biaya-biaya, khususnya dalam percepatan pembuatan laporan kepada pimpinan dan juga meminimalisirkan kesalahan dalam penempatan karyawan yang akan terpilih nantinya. Dan diharapkan dapat membantu mengatasi permasalahanpermasalahan menghambat dalam melakukan pengambilan keputusan untuk kenaikkan jabatan karyawan.

Establishing the Relative Importance of Specific Sustainability Themes That Influence Women’s Choice of Engineering as a Career Using the Analytical Hierarchy Process

Understanding the importance of salient factors associated with sustainability challenges that engineers are known to solve in influencing women’s choice of engineering is particularly important in this present world where a combination of these sustainability issues, the underrepresentation of women and the need for more engineers remain a challenge to the profession. However, little is known about the degree of importance of more detailed themes within the social, environmental and economic sustainability pillars in such career decisions. Consequently, the aim of this paper is to understand the relative importance of specific sustainability-themed factors influencing women’s choice of engineering, using the Analytical Hierarchy Process (AHP). An AHP structurally designed online survey was used to gather and analyze data from a sample of 414 UK and Nigeria respondents. The results showed that of all the ten sustainability-themed factors examined in this study, water quality/quantity, climate change, waste management, biodiversity, and material consumption/energy use, had a greater influence on the respondents’ choice of engineering relative to other factors. The data revealed specific rather than general sustainability themes that appeal to women’s choice of engineering. This could offer valuable insight from a recruitment strategy perspective to help engineering stakeholders to focus their attention and recruitment efforts on the most salient areas of influence.