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Deciphering the Visibility of Higher Education Institutions: A Statistical Analysis of Google Search Console Data Arief, Ikhwan
International Journal of Advanced Science Computing and Engineering Vol. 5 No. 1 (2023)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/ijasce.5.1.131

Abstract

The research presented here delves into the connection between data from Google Search Console (GSC) and the Webometrics visibility score of a specific public university's web presence. The study scrutinized GSC parameters such as clicks, impressions, click-through-rate (CTR), and average position to assess their impact on the university's digital visibility. The results indicate that impressions and average position play a critical role in determining the Webometrics visibility score, underscoring the significance of search engine optimization for learning establishments. The research also pinpointed the most effective search queries that drive substantial visitor traffic to the university's website, underlining the need for precise content targeting to optimize search performance. In this study, a predictive model was developed using multiple linear regression analysis to accurately predict the Webometrics visibility score based on GSC metrics, suggesting that strategic efforts to enhance these parameters could boost a university's online prominence. Additionally, a theoretical model was proposed to clarify the dynamic relationship between impressions, positions, and clicks in shaping the overall web visibility. Although this study provides valuable insights, it is based on data from a single university, which calls for further investigation using more varied datasets. Ultimately, the study emphasizes the immense potential of leveraging GSC data to bolster a university's online footprint, suggesting that strategic enhancements of vital parameters can greatly improve a university's online visibility according to Webometrics. As the academic world becomes increasingly digital, implementing these findings to guide search engine optimization strategies is a crucial element of institutional administration.
Implementation of The Balanced Scorecard In Improving The Performance of University Business Incubator (Case Study : Inkubator Bisnis Teknologi Universitas Andalas) Fithri, Prima; Hasan, Alizar; Triawan, Fandy; Arief, Ikhwan; Muluk, Asmuliardi
AMAR (Andalas Management Review) Vol. 7 No. 2 (2023)
Publisher : Management Institute Faculty of Economics Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/amar.7.2.1-17.2023

Abstract

Andalas University has a business incubator unit called the Technology Business Incubator (InBisTek) Andalas University. This study aims to formulate Key Performance Indicators and measure the performance of Inbistek Andalas University in assisting tenants. Performance measurement is carried out using the Balanced Scorecard method which consists of: on four perspectives namely internal business process perspective, growth and learning perspective, financial perspective, and tenants perspective. Performance measurement is carried out using data obtained from direct observation, questionnaires, and interview directly with the Andalas University Inbistek. KPI formulation is followed by a validation step,so that 31 selected KPIs were obtained. Furthermore, the selected KPIs are continued with weighting to determine the level interest in each KPI through a pairwise comparison questionnaire with the Analytical Hierarchy Process method. Then the performance measurement is carried out according to the perspective on the Balanced Scorecard. Obtained results of performance measurement Andalas University Institute of Technology as a whole is 3.4 which is included in the good category. Based on the results performance measurement, there are 5 KPIs with poor performance category, 5 KPIs with fairly good performance category, 12 KPIs withgood performance category, and 9 KPIs with very good performance category.
Balanced Scorecard dan Pengukuran Kinerja Pemerintahan Daerah: Tinjauan Sistematis terhadap Implementasi dan Isu Penelitian Satria, Trinda Farhan; Hadiguna, Rika Ampuh; Henmaidi; Arief, Ikhwan
Jurnal Sains dan Teknologi: Jurnal Keilmuan dan Aplikasi Teknologi Industri Vol. 24 No. 1 (2024): Regular Issue
Publisher : SEKOLAH TINGGI TEKNOLOGI INDUSTRI PADANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36275/j611ac61

Abstract

Tinjauan literatur sistematis ini mengkaji secara kritis penerapan Balanced Scorecard (BSC) dalam pengukuran kinerja pemerintah daerah. Di tengah meningkatnya pengawasan terhadap efisiensi sektor publik, tinjauan ini menyintesis literatur terkini untuk menilai adaptasi, hasil, tantangan, dan manfaat penerapan BSC dalam pemerintahan daerah. Berdasarkan kumpulan data 1.891 studi, yang sebagian besar bersumber dari Scopus dan Web of Science milik Clarivate, tinjauan ini menggunakan metodologi kuantitatif dan kualitatif, termasuk analisis tematik dan eksplorasi tren. Temuan utama mengungkapkan peningkatan fokus akademis pada BSC, pendekatan metodologis yang beragam mulai dari studi kasus hingga analisis empiris, dan wawasan tematik dalam pelaksanaan praktis BSC. Tinjauan ini menyoroti kemampuan beradaptasi dan efektivitas BSC dalam berbagai konteks pemerintah daerah, sekaligus mengidentifikasi tantangan dalam implementasi dan kontekstualisasi. Secara teoritis, hal ini berkontribusi terhadap literatur pengukuran kinerja dengan memberikan gambaran komprehensif tentang penerapan BSC di sektor publik. Secara praktis, laporan ini memberikan wawasan berharga bagi pembuat kebijakan dan administrator dalam mengoptimalkan strategi pengukuran kinerja. Studi ini menggarisbawahi pentingnya BSC dalam meningkatkan pengukuran kinerja pemerintah daerah dan memberikan arahan untuk penelitian di masa depan, dengan menekankan perlunya studi longitudinal dan integrasi teknologi.
Feature Selection and Performance Evaluation of Buzzer Classification Model Dian Isnaeni Nurul Afra; Radhiyatul Fajri; Harnum Annisa Prafitia; Ikhwan Arief; Aprinaldi Jasa Mantau
Jurnal Optimasi Sistem Industri Vol. 23 No. 1 (2024): Published in July 2024
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (318.919 KB) | DOI: 10.25077/josi.v23.n1.p1-14.2024

Abstract

In the rapidly evolving digital age, social media platforms have transformed into battleground for shaping public opinion. Among these platforms, X has been particularly susceptible to the phenomenon of 'buzzers', paid or coordinated actors who manipulate online discussions and influence public sentiment. This manipulation poses significant challenges for users, researchers, and policymakers alike, necessitating robust detection measures and strategic feature selection for accurate classification models. This research explores the utilization of various feature selection techniques to identify the most influential features among the 24 features employed in the classification modeling using Support Vector Machine. This study found that selecting 11 key features yields a remarkably effective classification model, achieving an impressive F1-score of 87.54 in distinguishing between buzzer and non-buzzer accounts. These results suggest that focusing on the relevant features can improve the accuracy and efficiency of buzzer detection models. By providing a more robust and adaptable solution to buzzer detection, our research has the potential to advance social media research and policy. This enabling researchers and policymakers to devise strategies aimed at mitigating misinformation dissemination and cultivating an environment of trust and integrity within social media platforms, thus fostering healthier online interactions and discourse.
Innovative Multi-Criteria Decision-Making Approach for Supplier Evaluation: Combining TLF, Fuzzy BWM, and VIKOR Ikhwan Arief; Dicky Fatrias; Ferry Jie; Armijal
Jurnal Optimasi Sistem Industri Vol. 22 No. 2 (2023): Published in December 2023
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (497.052 KB) | DOI: 10.25077/josi.v22.n2.p179-196.2023

Abstract

When confronted with underperforming suppliers, the need to evaluate and improve supplier performance becomes apparent. However, the inherent inaccuracies in information introduce complexity, especially when subjective human judgment is involved in the supplier evaluation process. Associated with such problem, this study presents a novel methodology for supplier performance evaluation in the crumb rubber industry, integrating the Taguchi Loss Function (TLF), fuzzy Best-Worst Method (BWM), and VIKOR technique in group decision-making environment. Aimed at addressing the challenges in industries with variable supplier quality and performance, such as the crumb rubber industry in Indonesia, the methodology was empirically tested to demonstrate its practical utility. The process involved identifying evaluation criteria through literature review tailored to the needs of decision makers (DMs), applying TLF to quantify losses from supplier performance deviations, using fuzzy BWM to determine criteria weights based on the DMs judgment, and employing the VIKOR technique for comprehensive supplier ranking. The findings underscore the methodology's effectiveness in enhancing decision-making, offering a unified metric that accommodates diverse criteria and balances precise data with subjective assessments. This approach simplifies the evaluation process, particularly in situations with conflicting interests among decision-makers. Demonstrating its practical application in the crumb rubber industry, the study highlights the methodology's potential for broader industrial applicability. Future research could explore comparative analyses with other analytical methods, further establishing the methodology's robustness and adaptability in different management contexts.
Identification of Internal Academic Factors Affecting Academic Entrepreneurship: A Case Study Prima Fithri; Rida Rahim; Donard Games; Alizar Hasan; Ikhwan Arief
Jurnal Optimasi Sistem Industri Vol. 20 No. 2 (2021): Published in October 2021
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (142.464 KB) | DOI: 10.25077/josi.v20.n2.p72-82.2021

Abstract

Academic Entrepreneurship is an entrepreneurial activity conducted by scientists/academics who market their research results commercially to achieve specific economic benefits or rewards. This research focuses on academic entrepreneurship that occurs at Andalas University. There is still a lack of academics whose research products for commercialization are about 22.73%. It is because there are factors that influence academic entrepreneurship activities at Andalas University. One of them is the internal academic factor. The internal factors are Control System, Organizational Culture, Human Resource Management System, Organizational Structure, and Academic Leadership Behavior. The purpose of this study is to analyze the university's internal factors on academic entrepreneurship. This research uses a quantitative approach derived from 106 Andalas University academics with Structural Equation Modelling (SEM) methods with SmartPLS Software. The result obtained in this study is that the control system exerts a positive and negative influence on academic entrepreneurship. In contrast, other factors have a significant positive influence on academic entrepreneurship. The research results show that the university's control system, organizational structure, and human resources had no significant positive effect on academics at Andalas University. Meanwhile, entrepreneurial behavior and organizational culture have a significant positive effect on academic entrepreneurship at Andalas University. Further research should be analyzed for all universities with innovative products and are ready for commercialization throughout Indonesia. This research is still a case study and needs to be developed.
Pembuatan Knowledge Management pada External Cylindrical Grinding Ikhwan Arief; Muhammad Arieaman Fikri
Jurnal Optimasi Sistem Industri Vol. 15 No. 1 (2016): Published in March 2016
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (822.421 KB) | DOI: 10.25077/josi.v15.n1.p47-61.2016

Abstract

Knowledge management is a process that helps an organization or company in identifying, selecting, preparing, distributing and sending important information and expertise part of an organization or a company to change the behavior or attitude that is not in place. Grinding processes are usually based on the experiences of people who have are experts in their work (tacit knowledge) that will be collected and converted into explicit knowledge so that the information can be maintained and easily accessible.The design began by analyzing the external cylindrical grinding systems and translate them into Unified Modelling Language (UML) which was followed by the design of database and computer software, and test the software. The application software is web-based and can be accessed by multiple users. The application will help the operator in determining parameters with given option of parameter recommendation. The system gives recommendations based on the tacit knowledge that has been gathered into explicit knowledge. The output of the application is a list of selected parameters and report cases. Report data in the case will be used to set up the machine.
Perancangan Purwarupa Sistem Pengendalian Kualitas Pengukuran Dimensi Produk Terotomasi Ikhwan Arief; Rahmat Fajri Fajri
Jurnal Optimasi Sistem Industri Vol. 14 No. 2 (2015): Published in October 2015
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/josi.v14.n2.p217-226.2015

Abstract

The production process is one of the several main activities in industries. The process followed by quality control to achieve expected final products. Products' conformities to design specification can be achieved through direct measurement. However, not all measurements can be done directly while the process is running. Inconformities to product's design specification could result in unfunctional or rejected products. This will render producers into losing their profits. Technology plays a major role in simplifying products' measurement processes. Advancement in technology made it possible to automate measurement processes and will also make it possible to do during the production process in achieving expected quality control as early as possible. The quality control yield measurements in products'lengths, widths and depths/ heights which will control products' dimension and generate quality control chart. The proposed prototype will allow measurements of product dimension and data acquisition directly during the process without disrupting on going processes.
Indikator Proses Utama pada Proses Grinding dengan Pendekatan Manajemen Pengetahuan Ikhwan Arief; Alfajri Nalda
Jurnal Optimasi Sistem Industri Vol. 13 No. 2 (2014): Published in October 2014
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/josi.v13.n2.p743-759.2014

Abstract

This study discusses about key process indicators in grinding with the knowledge management approach. Common/key indicators used in the machine are workpiece, grinding wheel, dressing tool and coolant. The resulting key processeswill benefit firms and their operators especially new ones in managing scienceson grinding process that will allow knowledge transferred to new operators quickly. Process indicators are described with IDEF0 diagrams which will define the inputs, outputs, mechanisms and controls.
Beyond the Metropolis: Drivers of Online Food Delivery Adoption Ikhwan Arief; Armijal Armijal; Ridhamelia Ridhamelia
Andalasian International Journal of Agriculture and Natural Sciences (AIJANS) Vol. 6 No. 2 (2025)
Publisher : Lembaga Penelitian dan Pengabdian, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/aijans.v6.i2.101-109.2025

Abstract

This study investigates the determinants of purchase intention for Online Food Delivery (OFD) services among Generation Z and Millennial consumers in a non-metropolitan city within an emerging market, using ShopeeFood in Padang, Indonesia, as a case study. The rapid saturation of OFD services necessitates a re-evaluation of classical technology adoption models. This research employs an extended Technology Acceptance Model (TAM) framework, integrating digital marketing as a key antecedent. Utilizing a quantitative survey methodology with a sample of 102 consumers, the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that Perceived Usefulness (B=0.584, p<0.001) and Digital Marketing (B=0.262, p<0.05) are significant positive predictors of Purchase Intention. Critically, Perceived Ease of Use (B=0.046, p<0.05) was found to have no significant effect. The model collectively explains 56.1% of the variance (R2) in purchase intention, demonstrating substantial predictive power. This study's principal contribution lies in providing empirical evidence that in a maturing digital service market, ease of use may transition from a direct driver of intention to a baseline 'hygiene factor'. Consequently, the core utility of the service and the effectiveness of strategic marketing efforts significantly influence consumer choice. These findings offer crucial implications for OFD platforms seeking to capture market share in the next frontier of digital growth: the emerging economies' secondary and tertiary cities.