Tengku Khairil Ahsyar
Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru

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Analisa Manajemen Risiko Sistem Informasi Perpustakaan Menggunakan Metode Failure Mode Effect and Analysis (FMEA) Maisarah Assa'diyah; Tengku Khairil Ahsyar; M Afdal
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 3 No. 6 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v3i6.867

Abstract

Public libraries that have implemented information technology in their business processes have a great responsibility in service and management because the visiting users are the general public. In implementing information technology, maintaining the security of user data, members, resources, and library information is very important. Digital libraries must have consideration of the risks and threats that may occur. The risks and threats that can occur are as follows server damage, hardware damage, staff negligence, loss, and natural disasters. The purpose of this research is to analyze risk management by identifying risks and measuring the level of risk from one of the Riau Province Library and Archives Services which already uses a library automation system, namely INLISLite. The method used to identify and assess risk is the Failure Mode Effect and Analysis (FMEA) method. Risk assessment is based on calculating the value of the Risk Priority Number (RPN) resulting from multiplying the level parameters severity, occurrence, and detection. Risk assessment is carried out based on the category list of asset components that support the running of the system, namely, hardware, software, data, people, and network. From the calculations that have been carried out, there are six categories of RPN levels, namely 1 score at a very high level, 3 scores at a high level, 2 scores at a medium level, 16 scores at a low level, and 1 score at a very low level. From the results of the RPN value that needs to be given recommendations for action, namely the RPN value which is at very high and high levels
Evaluasi Usability Pada Sistem Informasi Beasiswa Menggunakan Metode Heuristic Evaluation dan Think Aloud Riska Ayuni; Tengku Khairil Ahsyar; Muhammad Luthfi Hamzah
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 3 No. 6 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v3i6.873

Abstract

The scholarship information system needs to cover several aspects so that it can always maintain the superior quality of use and existing information, one of which is the usability aspect. Based on initial observations that have been made on the information system, there is user dissatisfaction such as sometimes errors when inputting data by staff, inconsistencies in some displays, no menu for forgotten password, no contact information, no help menu, parts of the site interface are difficult to understand. . The problem is related to usability. Usability evaluation is carried out to evaluate the system based on the level of effectiveness, efficiency and satisfaction. The purpose of this research was to evaluate the ease of use of the UIN Suska Riau Scholarship information system. The purpose of this evaluation is to see how easy the system is to use and to make recommendations about possible improvements. Data collection through observation, interviews, and questionnaires. in the heuristic evaluation method the data analysis method used is usability testing, and the data processing tool used is Statistical Product Solution (SPSS) Statistics 23 software from IMB Software. and 8 to 10 respondents for Think Aloud. For the evaluation of this study, two approaches were used, Heuristic Evaluation and Think Aloud. Heuristic Evaluation is used to evaluate the interface using a heuristic questionnaire, while Think Aloud is used to evaluate the use of the information system based on what the user says. At the Think Aloud data collection stage, each participant will carry out a task scenario to provide criticism or reveal the problems they are experiencing. The results of the data analysis succeeded in identifying identified gaps in the information system assessed in this study and providing recommendations for improvement. The results of the Heuristic Evaluation Analysis show that this system obtains a percentage score of 75%, which indicates a sufficient level of goodness for its users. However, there is a total of 25% where deficiencies are found in the system, it shows that this system is not good for its users. Then, through Think Aloud analysis, found up to 23 suggestions for improvement for the system being evaluated. Future research can further evaluate the implementation of these improvement recommendations
Evaluasi Usability Sistem Informasi Penelitian dan Pengabdian Masyarakat Menggunakan Heuristic Evaluation dan Human-Centered Design Efilda; Tengku Khairil Ahsyar; Muhammad Lutfhi Hamzah
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 3 No. 6 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v3i6.874

Abstract

Education is an asset for successfully building human resources in competition in the digital age. The world of education must increase the effectiveness of building education in this country in accordance with increasingly sophisticated technological advances such as the Information System for Research and Community Service (SIP). SIP is used to assist organizations in reporting work processes as operational achievements of external organizations as well as enabling task completion. The main problem with the SIP website is that it has never been evaluated in terms of usability since the system was used. This study aims to evaluate the usability of SIP websites using Heuristic Evaluation and Human-Centered Design. Usability is a very important factor for website acceptance. The Heuristic Evaluation uses 3 evaluators to assess the SIP website and uses 10 Heuristic Evaluation principles. The Human Centered Design method is used as a tool for developing designs and interactive systems that focus on user needs. From the results of the initial Heuristic Evaluation carried out by 3 evaluators by producing 21 problems as a basis for improving solution designs using prototypes. Furthermore, the second heuristic evaluation resulted in a decrease in problems, namely 3 problems located in the Heuristic code H1 Visibility Of System Status. This problem is a new problem found by evaluator 1. After doing a comparison, it can be concluded that the evaluation of the solution design resulted in a reduction of 18 problems from the 21 problems found to 3 problem findings found in the solution design evaluation
Perbandingan Algoritma Naïve Bayes Classifier Dan K-Nearest Neighbor Pada Sentimen Review Aplikasi Mobile JKN Citra Annisa; M. Afdal; Tengku Khairil Ahsyar
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6242

Abstract

BPJS Health must provide health services for the people of Indonesia. With the availability of the Mobile JKN application, it is useful to facilitate services for participants of the National Health Insurance-Indonesian Health Card (JKN-KIS). Mobile JKN is an innovation in electronic government health insurance services, making it easier for the public to access services and information quickly in the palm of their hand. With this innovation, many pros and cons flowed from the community, various comments appeared in the Play Store review column, sentiment analysis could be used to assess and rate applications. Therefore, these sentiments can be analyzed into information that can be used as material for evaluation and consideration by BPJS Kesehatan regarding Mobile JKN. This study aims to look at the results of the accuracy comparison between the Naïve Bayes Classifier (NBC) and K-Nearest Neighbor (KNN) algorithms on the sentiment review of the Mobile JKN application on the Play Store. This study used the Naïve Bayes Classifier (NBC) and K-Nearest Neighbor (KNN) methods with data scrapping techniques to collect Play Store data for the past year, namely 2,847 data and divided into 3 classes, namely positive, neutral and negative. Distribution of data using 10 K-Fold Cross Validation so that a comparison of the accuracy level of the Naïve Bayes Classifier (NBC) is 61.15%, while the accuracy level of K-Nearest Neighbor (KNN) is 87.59%.