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All Journal JURIKOM (Jurnal Riset Komputer) Jurnal Sistem Komputer dan Informatika (JSON)
Muhammad Affandes
Universitas Islam Negeri Sultan Syarif Kasim, Pekanbaru
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Design Rancangan User Interface Aplikasi My Pets Dengan Menggunakan Metode Design Thinking Roni Setyawan; Reski Mai Candra; Eka Pandu Cynthia; Febi Yanto; Muhammad Affandes
JURIKOM (Jurnal Riset Komputer) Vol 9, No 6 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i6.5305

Abstract

The research was made to produce an application design using the design thinking’s method. The system made on the basis of user interface and user experience. The user interface is used to meet user needs, while the user experience is used as an assessment of the system designed. The target of My Pets application is for pet parents. It  has several stages; empathize, define, ideate, prototype, and testing. At the empathize stage it produces the main problems which are used as material for researchers to find a solution, problems obtained from the results of interviews and observations of 25 respondents. In the define stage, it begins to determine the problem as main focus to be solved. The ideate stage, it generates a solution to an existing problem. The prototype stage develops designs based on the previous stages. At the testing stage using the system usability scale to 25 respondents and getting a result of 87.7 or excellent. Based on the test results, My Pets application has been completed and assessed as effective based on the design thinking’s method. It is expected the design made can be used and the system developed better in the future
Klasifikasi Sentimen Transformasi dan Reformasi Sepak Bola Indonesia Pada Twitter Menggunakan Algoritma Bernoulli Naïve Bayes Destri Putri Yani; Siska Kurnia Gusti; Febi Yanto; Muhammad Affandes
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 3 (2023): Maret 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i3.5829

Abstract

Federation Internationale de Football Association (FIFA) carried out Transformations and Reformations to Indonesian Football with one of them Indonesia was chosen as the Host of the U-20 World Cup in 2023. The transformations and reformations carried out cause people to often provide opinions through social media Twitter. Opinions given by the public can be positive or negative. The research uses Text Mining to classify sentiment in 2 categories with the Bernoulli Naïve Bayes algorithm. This research aims to classify positive and negative sentiments and determine the level of accuracy value of the sentiment classification results of Indonesian Football Transformation and Reformation. The research stages carried out are data collection, text preprocessing, data labeling, TF-IDF weighting, Bernoulli Naïve Bayes classification, and evaluation. Based on the research results from 4907 data there is duplicate data and only uses 2125 data which is divided into 90% training data and 10% testing data, so as to get accuracy with a high category value of 88%. The classification results show that many tweets are positive sentiments.
Klasifikasi Sentimen Tragedi Kanjuruhan Pada Twitter Menggunakan Algoritma Naïve Bayes Iqbal Salim Thalib; Siska Kurnia Gusti; Febi Yanto; Muhammad Affandes
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 3 (2023): Maret 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i3.5852

Abstract

The Kanjuruhan Malang incident occurred on October 1 and resulted in 132 deaths, 96 serious injuries and 484 minor injuries. The cause of the riot occurred due to provocation between Arema Malang supporters and Persebaya Surabaya supporters who mentioned harsh words and other provocative actions that caused anger on both sides. Sentiment analysis of the Kanjuruhan tragedy using the Naive Bayes method was conducted through tweets taken through Twitter to understand the public's perception of the incident. The Naïve Bayes algorithm is performed for the sentiment classification of tweet data which is applied by processing the tweet text and classifying it into positive, negative, and neutral. In this study using data as much as 4843 data and carried out with tweet data that has been crawled resulting in 2,042 data. This research aims to classify sentiment and determine the level of accuracy in the Multinomial Naïve Bayes algorithm in the Kanjuruhan tragedy using a dataset in the form of tweets from twitter social media. The processed tweet data is divided into two types, namely 90% training data and 10% test data.  The results of this classification get a Naïve Bayes accuracy of 75% with a precission of 73%, recall of 75%, and f1-score value of 74%. The results of the tweet data used in this study can be concluded that the Naïve Bayes algorithm has a fairly good accuracy value.
Co-Authors Destri Putri Yani Eka Pandu Cynthia Febi Yanto Iqbal Salim Thalib Reski Mai Candra Roni Setyawan Siska Kurnia Gusti