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Journal of Computer and Information Systems Ampera
Published by Asosiasi Perguruan Tinggi Informatika dan Ilmu Komputer
ISSN : -     EISSN : 27752496     DOI : https://doi.org/10.51519
Core Subject : Science,
Computer Science & IT
Journal of Computer and Information Systems Ampera (Journal-CISA) is an online journal that organized and managed independently by the consortium of informatics lecturers. Journal-SEA is an open-access journal that is provided for researchers, lecturers, and students who will publish research results in the field of all of thing about software engineering and its process.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 1 No. 3 (2020): Journal of Computer and Information Systems Ampera" : 5 Documents clear
Perencanaan Stategis Sistem Informasi Administrasi di SLBN Nunumeu SoE Menggunakan Metode Ward and Peppard Anjarwanti S. R. Suseno; Agustinus Fritz Wijaya
Journal of Computer and Information Systems Ampera Vol. 1 No. 3 (2020): Journal of Computer and Information Systems Ampera
Publisher : APTIKOM SUMSEL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalcisa.v1i3.40

Abstract

Special education school is a school established by the government with a special concept for Children with Special Needs. In carrying out activities, there is an Administration section which is an important part of the process of activities at school, but there are obstacles, namely not being well systemed so that it creates difficulties in operating. In building a good system, it is necessary to have a Strategic Information System planning in advance, therefore this research was conducted. This research was conducted using the Ward and Peppard method and using the SWOT, Value Chain, and MCFarland Strategy analysis methods, with qualitative research methods, then providing output in the form of proposed applications to be considered in future application development in order to facilitate all activities in the administrative section of SLBN Nunumeu.
Visualisasi Data Kependudukan Pada Dinas Kependudukan Dan Pencatatan Sipil Kabupaten Musi Banyuasin Rica Damayanti Putri; Alex Wijaya
Journal of Computer and Information Systems Ampera Vol. 1 No. 3 (2020): Journal of Computer and Information Systems Ampera
Publisher : APTIKOM SUMSEL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalcisa.v1i3.42

Abstract

Population data from the Department of Population and Civil Registration can be used by other agencies according to the needs of that agency. The Department of Population and Civil Registration uses SIAK (Sistem Informasi Administrasi Kependudukan /Population Administration Information System) for its service processes, the SIAK application is an application made by the Director General of Department of Population and Civil Registration of the Ministry of Home Affairs. The SIAK application still has limited features for operators in the District, for this reason the SIDAK application was created for the utilization of population data in Musi Banyuasin Regency. In this SIDAK application, there is no feature available for visualizing graphical data so that the desired data can be easily analyzed in aggregate data. For the data visualization, the authors took the data from the SIAK database conversion to the SIDAK application. The data taken is the aggregate data on the number of populations, mandatory ID card, birth, death, move, arrival, occupation, religion, education, blood group, marital status, persons with disabilities, age groups. Therefore, we need a tool that capable of visualizing population data using a website in the form of a dashboard system at the Department of Population and Civil Registration. This population data visualization system development uses the Extreme Programming method
Pemanfaatan Analisis Jaringan Sosial Dalam Penentuan Centrality Dalam Pengembangan Web Berita Online Fitra Ramadhan
Journal of Computer and Information Systems Ampera Vol. 1 No. 3 (2020): Journal of Computer and Information Systems Ampera
Publisher : APTIKOM SUMSEL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalcisa.v1i3.43

Abstract

Revolusi digital selama berapa tahun terakhir ini meningkat pesat dan membuat perkembangan pada basis data. Perkembangan data tersebut sering terjadi beredar secara global. Data yang tersebar secara global dapat dikonsumsikan sebagai informasi terutama dalam media sosial. Media sosial Twitter merupakan salah satu media sosial yang sudah banyak digunakan di indonesia, dengan Data percakapan pada Twitter tersebut dapat dimanfaatkan sebagai sarana Informasi atau berita dan dapat juga dianalisis. Dengan penelitian ini memanfaatkan Basis Data pada media sosial twitter pada tweets yang diperoleh melalui API (Application Programming Interface). Dengan basis data tersebut merupakan untuk mewakili jaringan sosial antara pengguna, dan dengan menggunakan metode Social Network Analisys (SNA) karena untuk mencari tahu siapa saja pengguna yang menunjukkan pengaruh paling besar dalam penyebaran berita atau informasi dengan menggunakan suatu kata kunci dengan kata lain kedekatan dan hubungan dalam tweet. Software basis data dan Visualisasi menggunakan Gephi. Dalam menentukan aktor yang paling berpengaruh dalam Hastag #Indonesia dihitung menggunakan Centrality yang terdiri dari degree Centrality, Betweeness Centrality, dan Closeness Centrality. Sampel yang digunakan dalam penelitian ini merupakan sebuah tweet yang didalam mention, retweet, maupun reply interaksi akun tersebut menggunakan #Indonesia. Hasil penelitian ini yaitu terdapat 1064 node (akun) dan terdapat 1261 edges merupakan aktor yang terlibat dalam interaksi. Dalam tersebut ditemukan aktor atau akun yang paling berengaruh dalam jaringan #Indonesia secara keseluruhan adalah akun bernama bob_bay.
Implementasi Business Intelligence Pada Analisis Perkembangan Hasil Pertanian Provinsi Sumatera Selatan Muhammad Danu Riyanda; Suyanto Suyanto
Journal of Computer and Information Systems Ampera Vol. 1 No. 3 (2020): Journal of Computer and Information Systems Ampera
Publisher : APTIKOM SUMSEL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalcisa.v1i3.44

Abstract

In the process of data collection of agricultural food products and horticulture consists of several data covering the time, area, area of land, crop yields, and types of plants stored in the form of files with large amounts of data. The large amount of data can cause errors in compiling information for the process of analysis and evaluation for the agriculture department. The analysis process can be faster and more precise by implementing Business intelligence. Business intelligence is a concept and method for managing and analyzing data and facts into more effective information to improve the quality of organizational evaluation and decision-making processes. One form of information that can be provided from the application of business intelligence is a visual dashboard that can help display information that makes it easier to analyze the development of agricultural products efficiently and interactively. Processing data for analysis in this study using the Pentaho application. By implementing Business Intelligence, it is expected to be able to assist the Department of Food Agriculture and Horticulture in South Sumatra Province in analyzing the development of agricultural products
Analisis Sentimen Masyarakat Terhadap Pilpres 2019 Berdasarkan Opini Dari Twitter Menggunakan Metode Naive Bayes Classifier Khoirul Zuhri; Nurul Adha Oktarini Saputri
Journal of Computer and Information Systems Ampera Vol. 1 No. 3 (2020): Journal of Computer and Information Systems Ampera
Publisher : APTIKOM SUMSEL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalcisa.v1i3.45

Abstract

Twitter is a social media that is currently popular, where the public is free to comment and write anything. It is not uncommon for the public to comment with harsh words and even hate speech. The 2019 presidential election drew many comments, some praised, criticized and insulted. To be able to dig up information and classify a text, sentiment analysis is needed. In this study, sentiment analysis is a process of classifying textual documents into two classes, namely negative and positive sentiment classes. Opinion data were obtained from the Twitter social network in the form of tweets. The data used was 3337 tweets consisting of 80% training data and 20% training data. Training data is data with known sentiment. This study aims to determine whether a tweet is a positive or negative tweet conveyed on Twitter in Indonesian. The classification of tweet data uses the naïve Bayes classifier algorithm. The classification results of the test data show that the Naïve Bayes Classifier algorithm provides an accuracy value of 71%. The accuracy value for each sentiment is 71% for positive sentiment and 70% for negative sentiment

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