Visualisasi Data Interaktif Data Terbuka Pemerintah Provinsi Dki Jakarta: Topik Ekonomi Dan Keuangan Daerah

Syaripul, Nadiar Ahmad; Bachtiar, Adam Mukharil

doi:10.21609/jsi.v12i2.481

Cited by 12 publications

(7 citation statements)

References 1 publication

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“…Visualisasi data dibutuhkan untuk menyajikan data atau informasi berupa trend. Cara efektif untuk menyajikan data agar lebih mudah dipahami adalah dengan mengubahnya menjadi data visual [3]. Visualisasi data merupakan suatu proses mengubah data agar lebih mudah dipahami dengan cara mengubah bentuk menjadi grafik.…”

Section: Pendahuluanunclassified

Implementation of K-Means Clustering Method for Trend Analysis of Thesis Topics (Case Study: Faculty of Computer Science, University of Jember)

2022

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The development of information technology causes a large number of digital documents, especially thesis documents, so that it can create opportunities for students to take the same and not varied topics. Thesis documents can be grouped by topic by identifying the abstract section. The results of the grouping can be seen with the trend with data visualization so that it can be analyzed to find out the trend of each topic. Retrieval of data in the repository of the University of Jember through a web scraping process as many as 490 thesis documents for students of the Faculty of Computer Science, University of Jember. The preprocessing stage is carried out by text mining methods which include cleaning, filtering, stemming, and tokenizing. Then calculate the weight of each word with the Term Frequency - Inverse Document Frequency algorithm, followed by the dimension reduction process using the Principal Component Analysis algorithm, which is normalized by Z-Score first. The outliers removal process is carried out before classifying documents. Furthermore, document grouping uses the K-Means Clustering method with Cosine Similarity as the distance calculation and the Silhouette Coefficient algorithm as a test. The test results were carried out with various k values and the optimal value was obtained at k = 2 with a Silhouette value of 0.80. Then the topic detection uses the Latent Dirichlet Allocation algorithm for each cluster that has been formed. Each cluster is visualized with a line chart and Trend Linear algorithm and analyzed to find out the trend. From the results of the analysis, it can be concluded that the topic of Decision Support System Development is trending down, and the topic of IT Performance Measurement and Forecasting is trending up. It can be concluded that the topic of Decision Support System Development needs to be reduced so that other topics can emerge.

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Section: Pendahuluanunclassified

Implementation of K-Means Clustering Method for Trend Analysis of Thesis Topics (Case Study: Faculty of Computer Science, University of Jember)

2022

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“…Panjaitan dan Hasugian menggunakan pendekatan Object Oriented Analysis and Design. Hasil penelitian ini adalah sistem informasi Gereja dengan fungsionalitas CRUDS tata acara, renungan, keuangan, jadwal kegiatan Gereja, informasi umum Gereja, dan data jemaat [9].…”

Section: Tinjauan Pustakaunclassified

Pembangunan Sistem Informasi dengan Visualisasi Data pada Gereja Santa Maria Dengan Tidak Bernoda Asal Tulungagung

Owen

Dwiandiyanta

Ch.

2022

Jurnal Informatika Atma Jogja

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Abstrak. Belum semua Gereja mengikuti perkembangan teknologi yang ada. Proses dokumentasi, pengolahan data, dan penyebaran informasi Gereja pada umumnya masih dilakukan secara konvensional. Pengambilan keputusan pengurus Gereja yang membutuhkan data masih dikelola dengan mencari data satu persatu. Berdasarkan permasalahan yang ada, maka ditemukan sebuah solusi yaitu membangun sebuah sistem informasi. Sistem informasi yang dibangun digunakan untuk melakukan proses dokumentasi secara digital, mengelola data serta menampilkannya pada grafik, dan menampilkan informasi Gereja secara online. Sistem dibangun dengan basis website. Penulisan kode menggunakan bahasa pemrograman PHP dan JavaScript. Bagian backend dibangun menggunakan framework Laravel, bagian frontend dibangun menggunakan library ReactJS, dan basis data yang digunakan adalah MySQL. Hasil penelitian menghasilkan sistem yang terdiri dari bagian admin dan bagian umat. Sistem yang dibangun dapat memudahkan pengguna dalam melakukan proses dokumentasi, pengolahan data, dan pengambilan keputusan. Selain itu sistem juga membantu umat dalam mencari informasi hasil distribusi Gereja.Kata Kunci: Dokumentasi, Pengolahan Data, Informasi, Website, Sistem Informasi

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“…Data visualization is concerned with the design, development, and implementation of computers [2]. Previously, research on the visualization of student satisfaction data against lecturers was conducted by Candra [3] who examined the Prediction of Student Satisfaction on Service Levels using the C4.5 Decision Tree Algorithm, Research on Application of Kmeans Algorithm for Clustering Lecturer Assessment Based on Student Satisfaction Index by khusniati [4] Research on Student Satisfaction on Lecturer Performance by Ruslan [5], Research on Analysis of Student Satisfaction on Lecturer Performance by Sulatri [6], Research on Student Satisfaction Levels on Performance of Lecturer Teaching and Learning Process by Paly [7], Research on Visualization of Patient Laboratory Examination Results by Ardy [8], Research on Interactive Data Visualization of Open Data by Syaripul [9], Research on Sales and Production Data Visualization by Aryanti [10], Research on Data Visualization in Library Management Systems by Saputra [11], and Research on Design and Development of Data Visualization on Internal Research Funds and Grants by Loka [12].…”

Section: Introductionmentioning

confidence: 99%

Data Clustering on Teaching and Learning Evaluation Application Over Pandemic Era

Vatresia

Fredianto

2022

J. Tek. Inform. (JUTIF)

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SIEPEL is an evaluation application for teaching and learning process in University of Bengkulu. It is mandatory for every student to fill the questionnaire before they can see the marking value for each subject each semester. This survey was designed to meet the requirements and expectations of students as educational service for customers. This data is very important to improve the quality of teaching and learning process for further policy and decision maker. However, the analysis of the data remains an open question as the size and the distribution of the data is become some issues to process the analysis. Here, we showed the new approach to analysis the data using K-Means Clustering to see the better distribution and understanding over the evaluation data. This paper used elbow method to find the best number of clusters to be implemented on the algorithm approach which results in four clusters of satisfaction values (unsatisfied, less satisfied, satisfied, and very satisfied). The result of this analysis was published based on website system to show the visualization of analysis. Furthermore, this research showed that the average value of evaluation result for 4 semester was very satisfied 6.50%; satisfied 43.89%; less satisfied 44.26%; and not satisfied 5.36%. The value of vary satisfied students was dropped from 20.47% to 0.12% by 2 years and the value for less satisfied was increased from 27.64% to 66.32%. This term was happened because of the pandemic era and the change on the process of learning and teaching on University of Bengkulu.

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Visualisasi Data Interaktif Data Terbuka Pemerintah Provinsi Dki Jakarta: Topik Ekonomi Dan Keuangan Daerah

Cited by 12 publications

References 1 publication

Implementation of K-Means Clustering Method for Trend Analysis of Thesis Topics (Case Study: Faculty of Computer Science, University of Jember)

Implementation of K-Means Clustering Method for Trend Analysis of Thesis Topics (Case Study: Faculty of Computer Science, University of Jember)

Pembangunan Sistem Informasi dengan Visualisasi Data pada Gereja Santa Maria Dengan Tidak Bernoda Asal Tulungagung

Data Clustering on Teaching and Learning Evaluation Application Over Pandemic Era

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