Academic Performance Measurement Model: Knowledge Management Perception Using Fuzzy-AHP Novі Yantі, Sarjon Defit, Okfalisa Okfalisa International Journal of Fuzzy Logic and Intelligent Systems, 2025 Assessment of academic performance in higher education begins with the establishment of knowledge management (KM) to produce explicit outcomes.The KM model is essential for the effective, objective, efficient, and integrated management of knowledge in higher education, encouraging continuous improvement in academic quality.This study proposed a model to measure KM success in assessing academic performance by considering the main principles of academic roles as constructs, including education and teaching, research and publication, community service, supporting elements, and work behavior.The constructs explored the KM process within knowledge creation, acquisition, storage, sharing, and application activities.Sixty-five subvariables were defined for the constructs.To obtain the preference values of each construct's variable and subvariable, a survey was conducted using a questionnaire distributed to academic experts from several Islamic public universities in Indonesia by applying the fuzzy analytical hierarchy process (fuzzy-AHP) method.The results of the analysis using fuzzy-AHP show that the highest priority weight value is found in the work behavior variable with subvariable KP WB1 (0.8365), followed by element supporting in subvariable KA ES1 (0.5923), education and teaching in subvariable KS ET1 (0.4798), community services in the subvariable KA CS1 (0.4522), and research and publications in the subvariable KP RP1 (0.4061).This difference shows the priority between the subvariables, which is the basis for decision-making according to the level of importance.With proper KM measurement, universities can improve their overall performance, drive innovation, and achieve an academic vision and mission more effectively and sustainably to support universities toward excellence.
Knowledge Management Trends for Measuring Academic Performance: A New Conceptual Framework Novi Yanti, Sarjon Defit, Okfalisa Proceedings of the International Conference on Electrical Engineering and Informatics, 2024 Research in the area of knowledge management for improving academic performance has been on the rise in recent years. The effectiveness of knowledge management in improving the quality of decision-making in higher education is a new challenge in the drive for university performance improvement. Therefore, this paper tries to propose one conceptual framework used to measure academic performance in universities. By applying knowledge management process integrated with Business Intelligence System with data-driven analysis concept. This can provide new insights into the theme of academic knowledge management processes for future research opportunities. The model developed is based on comprehensive research developments on research trends and mapping of knowledge management articles and academic performance as well as a systematic literature review. This literature review examines the current state, clusters, and main topics of research related to knowledge management based on authors, sources, cited articles, countries of article authors, and journals that are productive in producing articles. Herein, 429 articles are utilized as metadata taken from the Scopus database published in 2018-2024. Hence, the data analysis of scientific articles is then reviewed using a bibliometric approach and article mapping with using tool VOSviewers to get a network visualization image. The findings of bibliometric analysis point to a rise in publications and a strong level of interest among academics in the field of knowledge management for performance evaluation in higher education institutions.
Clustering the Academician Knowledge Qualification: K-Means for Performance Measurement Analysis Novi Yanti, Sarjon Defit, Okfalisa 2024 IEEE 22nd Student Conference on Research and Development Scored 2024, 2024 The assessment of an academic’s performance is not solely based on the tangible results achieved. Nonetheless, the formation aspect of the Knowledge Management (KM) process, which arises in the pursuit of outcomes, must be acknowledged. This emphasizes the significance of KM process development for academics in achieving their essential responsibilities including teaching and learning, research and publishing, and community service. Consequently, it is essential to develop a KM model for assessing the accomplishments of academics in higher education. An evaluation of academic performance in higher education was conducted to identify the success factors of knowledge management, by considering five key elements viz, knowledge creation, knowledge acquisition, knowledge storage, knowledge sharing, and knowledge application. Accordingly, sixty-five sub-variables were identified as success model factors for evaluating academic knowledge management performance. A K-Means clustering method was utilized to assess the KM qualifications of academics at an Islamic public institution in Indonesia (University X) as the primary study. Herein, a 5-point Likert scale questionnaire was administered to 500 academics and subsequently categorized into three performance levels such as low, medium, and high performance. As a result, 140 academicians were categorized as low KM performance, 139 were clustered as medium qualification, and 221 academicians were positioned in high performance. Furthermore, a recommendation analysis is presented to elucidate the accomplishments of academic credentials for each cluster and propose corrective actions for enhancement. Therefore, the scholars at University X might enhance their knowledge management practices to get a superior quality university.
Optimizing placement of field experience program: An integration of moora and rule-based decision making Okfalisa Okfalisa, Rizka Hafsari, Gusman Nawanir, Saktioto Toto, Novi Yanti Pertanika Journal of Science and Technology, 2021 The lack of optimality in the Field Experience Program (FEP) placement has affected universities’ educational services to the stakeholders. Bringing together the stakeholders’ needs, university capacities, and participants’ willingness to quality and quantity is not easy. This study tries to optimize the placement of FEP by considering the interests of multiple perspectives through the application of Multi-Objective Optimization on the Basic of Ratio Analysis (MOORA) and Rule-Based methods in the form of a decision-making model. MOORA ranked the students based on the FEP committee’s perspective and other criteria, such as micro-teaching grades, final GPAs, study programs, number of credits, and student addresses. Meanwhile, the school perspective was ordered based on its accreditations, levels, types, facilities, and performances. To achieve the optimal recommendation of FEP placement, the integration of MOORA and Rule-based intertwined the requirement of such perspectives. A prototype of the system recommendation is then acquired to simplify the decision-making model. As adjudications, a survey from twenty stakeholders evidenced around 86.92% of system user acceptances. The confusion matrix testing defines the accuracy of this method reaches 78.33%. This paper reveals that the recommendation model has been successfully increasing the effectiveness of decision making in FEP placement under the needs and expectations of the entire stakeholders.
Bioinformatic analysis in designing mega-primer in overlap extension PCR cloning (OEPC) technique - Mardalisa, Sony Suhandono, Novi Yanti, Fazrol Rozi, Fitri Nova, - Primawati International Journal on Informatics Visualization, 2021 Bioinformatics has developed into an application tool for basic and applied research in the biomedical and biotechnology field. Polymerase Chain Reaction (PCR) is a common technique in the molecular area that has always involved bioinformatics science. PCR cloning techniques such as TA cloning and PCR-mediated cloning exhibit complex processes with low success rates. One easy, effective, and practical solution is to use a mega-primer with the Overlap Extension PCR Cloning (OEPC) technique. The success of PCR cloning using the mega-primer design in the OEPC technique is strongly influenced by the characteristics of the mega-primer used. Knowledge of mega-primer characteristics is one of the important factors in the success of PCR cloning. The design process for the mega-primer str promoter was characterized based on the principle of a genetic algorithm using the web-based bioinformatics tools such as ClustalW, NetPrimer, and BLAST. The success of the mega-primer construction in producing recombinant pSB1C3 vector has been confirmed by the sequencing method and the function of the reporting protein (AmilCP). DNA analysis shows a 100 % homologous sequence on the str promoter, while E. coli colonies successfully express the purplish-blue color. Mega-primer characters can save costs and time of the research by maintaining the primer parameters that provide optimal values and increase the success value of PCR cloning via bioinformatics software. Hence, implications on biological problems, especially using DNA and amino acid sequences, could solve rapidly.
Application of Novel Ergonomic Postural Assessment Method in Indonesia Creative Industry Centers Merry Siska, Reski Mai Candra, Eki Saputra, Masud Zein, Alex Wenda, Novi Yanti 2019 International Conference on Engineering Science and Industrial Applications Icesi 2019, 2019 An operator's productivity should be affected by the conditions of the work station where the operators are carrying out their activities. The conditions of the work station or good work environment for an operator are effective, comfortable, safe, healthy and efficient. This paper analyze the Novel Ergonomic Postural Assessment Method application in the Indonesia creative industry centers in Bandung. Bad operator work postures carried out every day cause a high risk of musculoskeletal disorders for the operators in the creative industry centers in Indonesia. Thus, the research problems can be formulated as: How is the application of the Novel Ergonomic Postural Assessment Method (NERPA) in the center of creative industries in Indonesia. Based on the constraints of the problem, each new design in four creative centers in Bandung was conducted. In the doll making, the first posture is designing doll pattern station which is a priority for improvement by designing a table to reduce the level of musculoskeletal risk for its workers. The fourth body posture in shoe-making is a priority to be improved by making a design tool to cut the footwear to reduce the level of musculoskeletal risk. Knitted clothing center having level of musculoskeletal risk are priority improvements, namely in the first posture because the operator works in long standing state. Tofu making center also has high level of musculoskeletal risk, namely in the molding tofu station in posture 5.
Implementation of Advanced Encryption Standard (AES) and QR Code Algorithm on Digital Legalization System Okfalisa, Novi Yanti, Wahyu Aidil Dita Surya, Amany Akhyar, A Ambarwati Frica E3s Web of Conferences, 2018 A certificate is an important document that its validity must be ascertained. Fraud over the originality of this document demands a high level of security to ensure that this document is genuine. The Digital Certificate Legalization system (DCL) can regulate and guarantee the mechanism of document validity procedure. By implementing AES and QR Code algorithm, the information contained in the photo-scan of the certificate can be authenticated. The results of the scan are encrypted by using the legalized code in AES Algorithm. The code will be translated using the QR Code and matched to the data contained in the server system. The system will confirm whether the certificate is original or not. In order to test the system, black box testing is applied for functionality check; capacity testing in terms of execution time and memory load of benchmark testing are also examined for system performance measurement. Finally, user response testing is conducted to identify the user acceptance towards the system. As the result, the implementation of AES and QR Code algorithm provides good performance, efficient, light, and fast execution responses (less than one second and less than one megabyte) in a legalized certification checking system.
Tropical diseases web-based expert system using certainty factor Novi Yanti, Rahmad Kurniawan, Siti Norul Huda Sheikh Abdullah, Mohd Zakree Ahmad Nazri, Wilda Hunafa, Mardhiyah Kharismayanda Proceedings 2018 2nd International Conference on Electrical Engineering and Informatics Toward the Most Efficient Way of Making and Dealing with Future Electrical Power System and Big Data Analysis Icon Eei 2018, 2018 Indonesia is in the area of equatorial latitude which is known as a tropical climate country. On the other hand, many Indonesian people are prone to suffering typical tropical disease such as typhoid, dengue and malaria. With the motivation to curb disease, they should be informed about awareness, treatment and knowledge regarding to tropical diseases such as the symptoms, causes and early prevention. Web-based expert system is one well-known solution, which can access online via internet. Usually, traditional inference engine is possible to make misdiagnosis in medical domain. In addition, modern inference e.g. Bayes theory are complicated plus insufficient to substitute complete human brain reasoning activities. Therefore, this study aims to hybridize Forward Chaining and Certainty Factor method for diagnosing common tropical diseases suffered by Indonesian people. We have used ten types of tropical disease namely typhoid, dengue, chingkungunya fever, malaria, chicken pox, tuberculosis, diphtheria, pertussis, SARS and elephantiasis along with 38 symptoms for representing every disease into a knowledge base. We compare the results between expert’s diagnosis and our proposed web-based expert system after running ten times consecutively. We can conclude that hybridization of Forward Chaining and Certainty Factor methods during developing the web-based expert system, can significantly diagnose tropical diseases properly.
Dominant Criteria and Its Factor Affecting Student Achievement Based on Rough-Regression Model Riswan Efendi, Novi Yanti, Alex Wenda, Susnaningsih Mu'at, Noor Azah Samsudin, Mustafa Mat Deris 2018 2nd International Conference on Informatics and Computational Sciences Icicos 2018, 2018 the ordinary least square model has been widely considered to estimate the significant factors which influence the student achievement. Some factor is qualitative type and measured using criteria or categories. However, the decisive criteria for each factor which affect to the cumulative grade point average of student cannot be determined by this model. In this paper, we are interested to build a new procedure using rough-regression model in determining the dominant criteria from each factor based on generalization of dependency attribute. Based on result, the proposed procedure is capable to investigate the dominant criteria and factors affecting student achievement, such as, language spoken with dominant criteria is “many-many”, FB friend with dominant criteria is “many” and fast food with dominant criteria is “never”. This proposed procedure is very appropriate to implement for handling categorical data.
Supply chain configuration using hybrid SCOR model and discrete event simulation Lecture Notes in Engineering and Computer Science, 2014
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