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All Journal Jurnal ICT : Information Communication & Technology Jurnal Sistim Informasi dan Teknologi Journal of Management Accounting Business and International Research
Dadang Sudrajat
STMIK IKMI Cirebon
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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E-Learning Usability Evaluation Menggunakan Fuzzy Logic dan Usulan Alternatif Desain Interaktif Learning Management System (LMS) Chamilo Arif Rinaldi Dikananda; Harry Budi Santoso; Raditya Danar Dana; Dadang Sudrajat
Jurnal ICT : Information Communication & Technology Vol 18, No 1 (2019): JICT-IKMI, Juli 2019
Publisher : STMIK IKMI Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36054/jict-ikmi.v18i1.56

Abstract

E-Learning as well as learning media in general needs to be evaluated to find out and measure how much effectiveness, efficiency and user satisfaction is for the quality of the overall learning process. One effort that can be done to find out and evaluate the quality of learning is to use usability evaluation. Usability measurements require data derived from questionnaires presented using a Likert scale. The data illustrates the perceptions of users who have uncertainties because they are very subjective so they have the potential to cause misinterpretations. Fuzzy logic can be used to evaluate e-Learning reusability because fuzzy logic has the advantage of resolving a problem that contains uncertainty / ambiguity, which in this case is in accordance with the context of usability problems that are often presented in natural languages that have uncertainties, such as "how effective? "," How efficient? "And" how much user satisfaction. By using the Mamdani model Fuzzy Inference an increase in system usability with a score of 3.06 with a membership level of 0.9961 in the Moderate Usability stack. With the application of fuzzy variables and fuzzy rules, the process of evaluating system usability can be done with natural language that is easier to understand.
AnalisaTingkat Kepuasan Mahasiswa Terhadap Layanan Pembelajaran Menggunakan K-Means dan Algoritma Genetika Ade Rizki Rinaldi; Lana Surlanto; Dadang Sudrajat; Dian Ade Kurnia
Jurnal ICT : Information Communication & Technology Vol 18, No 1 (2019): JICT-IKMI, Juli 2019
Publisher : STMIK IKMI Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36054/jict-ikmi.v18i1.55

Abstract

The level of student satisfaction with learning services in higher education is one factor in the quality of college learning. To determine the level of student satisfaction with learning services in higher education, it is necessary to analyze the level of student satisfaction with learning services. K-Means method is a technique of grouping data based on the level of similarity of each member. K-Means can be used to classify the student satisfaction index on learning services. The K-Means method can also be optimized with genetic algorithms to determine the best centroid value. K-means optimization with Genetic Algorithms can be used as a technique to determine the level of student satisfaction with learning services. Obtained by Davies Bouldien Index from the K-Means and Genetics method is 1.593 with cluster number 5
Enhancing Workforce Agility of National Insurance Firm’s Employees by Effective E-Learning Management and Growth Mindset Hendy Tannady; Aditya Wardhana; Dadang Sudrajat
Jambu Air : Journal Of Accounting Management Business And International Research Vol 1, No 1 (2022): September 2022
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (246.064 KB) | DOI: 10.57235/jambu air.v1i1.10

Abstract

This study aims to determine the effect of e-learning and growth mindset to workforce agility at Insurance Company XYZ. This study using qualitative approach as well as observation and interview to collect data and information about the problems that might be happen. This study conducted interviews with 5 persons who are the employees of Insurance Company XYZ.In this study it was found that there were various positive and negative impacts. Even tho, the results of this study show that e-learning and growth mindset have an effect on workforce agility at Insurance Company XYZ. Therefore, the researcher give the suggestion for Insurance Company XYZ is to always empower, motivate and provide moral support for the employees to be able to provide the best for the company and not give up easily at work. 
Analisis Segmentasi Pelanggan Menggunakan Metode K-Means Clustering Khaerul Anam; Dadang Sudrajat; Dian Ade Kurnia
Jurnal ICT: Information Communication & Technology Vol. 22 No. 2 (2022): JICT-IKMI, December 2022
Publisher : LPPM STMIK IKMI Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Teknologi berbasis computerized dewasa ini dapat diaplikasikan sebagai instrumen pendukung kegiatan pada berbagai bidang usaha dalam rangka mencapai tujuan pekerjaan dengan efektif dan efisien. Teknologi computerized data mining dibutuhkan untuk membantu kegiatan promosi dengan membuat segmentasi pelanggan berdasarkan data transaksi sebelumnya. Segmentasi pelanggan dapat dimanfaatkan sebagai indikator nilai pelanggan (customer value), dalam hal ini perusahaan akan dapat menilai kelompok pelanggan mana yang memberikan keuntungan besar bagi perusahaan. Penelitian ini bertujuan untuk membuat segmentasi pelanggan dari sebuah supermarket dengan K-Means clustering. Hasil eksperimen clustering didapatkan nilai k = 2 sebagai cluster terbaik dengan nilai DBI 0,527 dan nilai centroid distance 1,4821. Kelompok data pada Cluster 0 berjumlah 109 data sedangkan pada cluster 1 berjumlah 231 data dan total semua data adalah 340. Segmen data dari hasil clustering dideskripsikan menjadi segmen konsumen prioritas dan dan konsumen biasa yang dapat menjadi informasi pendukung untuk divisi marketing dalam menentukan strategi pemasaran yang relevan dengan konsumen untuk meningkatkan Customer Lifetime Value.
The Implementation of Data Mining Method Using K-Means Algorithm to Analyze Study Interest of High School Students Dadang Sudrajat; Arif Rinaldi Dikananda; Abrar Hiswara; Rinovian Rais; Amat Suroso
Jurnal Sistim Informasi dan Teknologi 2023, Vol. 5, No. 1
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jsisfotek.v5i1.209

Abstract

At present, the school is experiencing difficulties processing the results of student academic achievement for the specialization process for high school students. The currently running student interest process still uses a manual system by calculating the subject value of each student and then grouping the results of the calculation of each student's value into science or social studies interest groups in accordance with the requirements imposed by the school. For that, we need a solution that can overcome these difficulties. The author develops the application using the Rapid Application Development (RAD) method, which consists of the requirements planning phase, the design phase, the construction phase, and the implementation phase. At the construction stage, the K-Means algorithm is implemented in data mining technology to classify student academic achievement results into science and social studies interest groups. The results of making this application are intended for the school, especially the homeroom teacher, so that it can be an alternative solution or advice in making decisions for student specialization.
Co-Authors Abrar Hiswara Ade Rizki Rinaldi Aditya Wardhana Arif Rinaldi Dikananda Dian Ade Kurnia Harry Budi Santoso Hendy Tannady Khaerul Anam Lana Surlanto Raditya Danar Dana Rinovian Rais suroso, amat