Articles
<![CDATA[Rancang Bangun Aplikasi Rentcar Now Pada Rental Mobil Sahabat Purwakarta Berbasis Mobile dengan Metode Prototype ]]>
<![CDATA[Muhammad Reza Mahendra]]>;
<![CDATA[Yudhi Raymond Ramadhan]]>;
<![CDATA[Dadi Iskandar]]>
<![CDATA[ Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 4, No 1 (2023): Edisi Januari ]]>
Publisher : <![CDATA[LPPM STIKOM Tunas Bangsa ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30645/kesatria.v4i1.115
<![CDATA[Sahabat Purwakarta Car Rental is a company engaged in services, especially for car rental services in Purwakarta. Ordering and presenting information on car availability is part of the business process activities carried out by Sahabat Purwakarta Car Rental. In the design of the best friend rental car application for mobile-based online ordering, the case study of the friend car rental in Purwakarta, the author uses a prototype software method using the Flutter programming language and uses firebase as the database. The features contained in the rentcar now application at Purwakarta best friend car rental are car availability, car ordering, managing car data, managing order data, and managing report data. The application that was built has been tested using blackbox testing and can run well. In implementing the rentcar now application, it is hoped that ordering and presenting information on car availability will make it easier for consumers and help employees at car rental friends in Purwakarta]]>
<![CDATA[PENERAPAN METODE UCD UNTUK PERANCANGAN UI DAN UX DALAM MEMBANGUN FITUR MENTOR ON DEMAND DAN LIVE CHAT PADA WEBSITE SKILVUL ]]>
<![CDATA[Youky Arie Sandi]]>;
<![CDATA[Imam Ma’ruf Nugroho]]>;
<![CDATA[Yudhi Raymond Ramadhan]]>
<![CDATA[ JURNAL ILMIAH BETRIK Vol. 13 No. 03 DESEMBER (2022): JURNAL ILMIAH BETRIK : Besemah Teknologi Informasi dan Komputer ]]>
Publisher : <![CDATA[P3M Institut Teknologi Pagar Alam ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.36050/betrik.v13i03 DESEMBER.34
<![CDATA[The user interface (UI) plays an important role in giving the user a good initial impression of the visuals of an application or website. Meanwhile, User Experience (UX) helps build interaction between users and the application system or website. UI and UX design is very influential for user comfort, so it needs an accurate analysis according to user needs. Skilvul is a technology education platform that currently wants to create Mentor on Demand and Live Chat features. This feature is needed because the number of students is not proportional to the number of existing mentors, therefore this feature was created which aims to help Skilvul students to be able to consult and discuss learning with mentors privately. By making these features, UI and UX design will be carried out first using the User Centered Design (UCD) method. The results of the design in this study were carried out using the Single Ease Questionnaire (SEQ) method. Through the SEQ questionnaire, the average value is 6.5 where the value is included in the easy category. Based on these results, it proves that the results of UI and UX design in building Mentor on Demand and Live Chat features can be categorized as easy and according to user needs.]]>
<![CDATA[Perancangan UI/UX Aplikasi Reservasi di Kitchenery Resto and Cafe Purwakarta Menggunakan Metode GDD ]]>
<![CDATA[Dewi, Shintia Kemala]]>;
<![CDATA[Nugroho, Imam Maruf]]>;
<![CDATA[Ramadhan, Yudhi Raymond]]>
<![CDATA[ Jurnal Sistem Informasi, Teknik Informatika dan Teknologi Pendidikan Vol. 3 No. 1 (2023): Jurnal Sistem Informasi dan Teknologi ]]>
Publisher : <![CDATA[Utiliti Project Solution ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.55338/justikpen.v3i1.55
<![CDATA[User Interface (UI) dan User Experience (UX) memainkan peran integral dalam membantu aplikasi agar lebih menonjol. Oleh karena itu, memiliki UI yang terintegrasi dan harmonis atau UX dalam aplikasi seluler tidak hanya membantu bisnis untuk menarik lebih banyak pengguna tetapi juga meningkatkan kepuasan pelanggan. Kitchenery Resto and Cafe Purwakarta merupakan salah satu tempat makan yang memanfaatkan teknologi untuk memajukan bisnisnya dan membutuhkan desain aplikasi reservasi untuk membantu pelanggan dan karyawan dalam melakukan proses reservasi. Dengan pembuatan aplikasi tersebut akan dilakukan UI dan UX terlebih dahulu dengan menggunakan metode Goal Directed Design (GDD). Hasil perancangan akan dilakukan dengan menggunakan metode pengujian System Usability Scale (SUS). Berdasarkan metode perancangan dan metode pengujian pada penelitian ini, didapatkan nilai rata-rata 78 dengan grade B melalui kuesioner pada tahap support yang dilakukan oleh lima orang responden. Berdasarkan hasil tersebut membuktikan bahwa hasil perancangan UI dan UX aplikasi reservasi ini dapat diterima dan sesuai dengan kebutuhan pengguna.]]>
<![CDATA[ANALISIS SENTIMEN E-WALLET GOPAY, SHOPEEPAY, DAN OVO MENGGUNAKAN ALGORITMA NAIVE BAYES ]]>
<![CDATA[Widianto, Iqbar Sajidan]]>;
<![CDATA[Ramadhan, Yudhi Raymond]]>;
<![CDATA[Komara, Mutiara Andayani]]>
<![CDATA[ Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 3S1 (2024) ]]>
Publisher : <![CDATA[Universitas Lampung ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.23960/jitet.v12i3S1.5277
<![CDATA[Pembayaran secara non-tunai atau cashless yang dilakukan melalui aplikasi dompet digital atau e-wallet merupakan aktivitas digitalisasi yang terus digunakan dalam kehidupan sehari-hari, mulai dari pesan antar makanan, berbelanja online, hingga pembayaran asuransi semua dilakukan dengan mudah dan cepat melalui aplikasi dompet digital. Dari banyaknya pengguna aplikasi dompet digital tersebut tentu saja tidak semua pengguna merasa puas dengan aplikasi yang mereka gunakan dan biasanya para pengguna aplikasi dompet digital sering kali meninggalkan ulasan kepuasannya di salah satu platform distribusi aplikasi yaitu Google Play Store. Namun, jika para calon pengguna aplikasi membaca seluruh ulasan itu bisa menghabiskan banyak waktu, maka dalam hal ini perlu dilakukan analisis sentiment. Tujuan dari penelitian ini adalah untuk menganalisis sentimen ulasan aplikasi dompet digital Shopeepay, Gopay, dan OVO di Google Play Store. Metode penelitian yang digunakan adalah metode Knowledge Data Dictionary (KDD) dengan menggunakan algoritma Naïve Bayes Classifier. Tools yang digunakan untuk mendukung proses penelitian yaitu Jupiter Notebook dengan bahasa pemrograman Phyton. Objek penelitian berfokus pada tiga aplikasi dompet digital yaitu Gopay, Shopeepay dan OVO. Setelah dilakukan pengujian menggunakan algoritma Naïve Bayes Classifier hasil nilai akurasi aplikasi Shopeepay memiliki nilai paling besar yaitu sebesar 88%, disusul aplikasi OVO 86% sebesar dan aplikasi Gopay sebesar 82%. Dari hasil akurasi tersebut dapat disimpulkan bahwa algoritma Naïve Bayes Classifier bekerja dengan baik terhadap analisis aplikasi Shopeepay]]>
<![CDATA[Analisis Marketplace Shopee Untuk Memprediksi Penjualan dengan Algoritma Regresi Linier ]]>
<![CDATA[Syakir, Yusuf]]>;
<![CDATA[Hermanto, Teguh Iman]]>;
<![CDATA[Ramadhan, Yudhi Raymond]]>
<![CDATA[ J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER ]]>
Publisher : <![CDATA[STIKOM Tunas Bangsa Pematangsiantar ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30645/j-sakti.v6i2.501
<![CDATA[Many methods can be used to predict sales, one of which is the processing of sales data using the method of data mining with a linear regression algorithm. The data in this study used is data on sales of the Ariqa Collection Boutique in the Shopee marketplace starting from May 2020 to April 2022. By using a linear regression algorithm, the Ariqa Collection Boutique can predict sales estimates based on total visitors and total orders. The data mining method used is SEMMA (Sample, Explore, Modify, Model, Assess). With the Rapidminer Studio 9.10 tools the test results Mean Square Error (MSE) value is 5.172.628.212.404, Root Mean Square Error (RMSE) is 2.274.341, and Mean Absolute Percentage Error (MAPE) is 4.34%. Based on the MAPE value obtained, the accuracy of the linear regression algorithm in predicting sales of Ariqa Collection Boutique in the Shopee marketplace provides high accuracy]]>
<![CDATA[Analisis Sentimen Terhadap Aplikasi Chatgpt Pada Twitter Menggunakan Algoritma Naïve Bayes ]]>
<![CDATA[Rifaldi, Muhamad Ilmar]]>;
<![CDATA[Ramadhan, Yudhi Raymond]]>;
<![CDATA[Jaelani, Irsan]]>
<![CDATA[ J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 2 (2023): EDISI SEPTEMBER ]]>
Publisher : <![CDATA[STIKOM Tunas Bangsa Pematangsiantar ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30645/j-sakti.v7i2.687
<![CDATA[Sentiment analysis or opinion mining is the detection of attitudes, opinions and emotions towards an object. The value of sentiment analysis can be divided into 2 types of sentiment, namely positive and negative sentiment. One of the topics that is currently being discussed by the public on Twitter social media is an AI-based chatbot application, ChatGPT. This research makes public tweets on Twitter as sentiment analysis material. Data retrieval is done using the Twitter API with data processing on Rapidminer and visualization using Power BI. The sentiment analysis process uses the Naïve Bayes algorithm by dividing the data of 301 tweets into training data and test data. Then testing using Confusion matrix to calculate the performance of the classification results. From the test results, 80% accuracy was obtained, then the Precission value was 80.95% and the Recall value 89.47%. It can be concluded that public sentiment on Twitter for the ChatGPT application tends to be positive seen from the number of positive tweet data as much as 74%.]]>
<![CDATA[Perancangan User Interface/User Experience Aplikasi Mobile Menggunakan Metode Design Thinking Pada Only One Cloth Di Purwakarta ]]>
<![CDATA[Budiharto, Sigit]]>;
<![CDATA[Ramadhan, Yudhi Raymond]]>;
<![CDATA[T, Moch. Hafid]]>
<![CDATA[ J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 1 (2023): EDISI MARET ]]>
Publisher : <![CDATA[STIKOM Tunas Bangsa Pematangsiantar ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30645/j-sakti.v7i1.579
<![CDATA[The most important stage in making a mobile application is designing an attractive display design. The Only One Cloth store still uses social media to sell products, besides that the factors that are still limited to the Only One Cloth Store are the lack of payment system organization and descriptions, therefore an application display that is needed by the store and potential users is made. The user interface (UI) is a form of graphical display that relates to potential users. User Interface works to connect users with the operating system on the computer so that prospective users can use it easily. Making the application display uses the iterative Design Thinking method where we try to understand the user, challenge assumptions, and redefine the problem in an effort to find alternative strategies and solutions. The Design Thinking method consists of five stages, namely Emphatize, Define, Ideate, Prototype, Test. At the Test stage, a test will be carried out on the value given to the task from the application display that has been made. The values that have been collected will be tested using the Single Ease Question (SEQ) method and get a value of 6.4 from the total tasks that have been assessed, if one task has a value of 5.5 then it must be iterated again. Judging from the SEQ results from the appearance of the application that is made feasible 6.4 then the appearance of the application is already easy to use by potential users]]>
<![CDATA[Analisis Marketplace Shopee Untuk Memprediksi Penjualan dengan Algoritma Regresi Linier ]]>
<![CDATA[Syakir, Yusuf]]>;
<![CDATA[Hermanto, Teguh Iman]]>;
<![CDATA[Ramadhan, Yudhi Raymond]]>
<![CDATA[ J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER ]]>
Publisher : <![CDATA[STIKOM Tunas Bangsa Pematangsiantar ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30645/j-sakti.v6i2.501
<![CDATA[Many methods can be used to predict sales, one of which is the processing of sales data using the method of data mining with a linear regression algorithm. The data in this study used is data on sales of the Ariqa Collection Boutique in the Shopee marketplace starting from May 2020 to April 2022. By using a linear regression algorithm, the Ariqa Collection Boutique can predict sales estimates based on total visitors and total orders. The data mining method used is SEMMA (Sample, Explore, Modify, Model, Assess). With the Rapidminer Studio 9.10 tools the test results Mean Square Error (MSE) value is 5.172.628.212.404, Root Mean Square Error (RMSE) is 2.274.341, and Mean Absolute Percentage Error (MAPE) is 4.34%. Based on the MAPE value obtained, the accuracy of the linear regression algorithm in predicting sales of Ariqa Collection Boutique in the Shopee marketplace provides high accuracy]]>
<![CDATA[Analisis Sentimen Terhadap Aplikasi Chatgpt Pada Twitter Menggunakan Algoritma Naïve Bayes ]]>
<![CDATA[Rifaldi, Muhamad Ilmar]]>;
<![CDATA[Ramadhan, Yudhi Raymond]]>;
<![CDATA[Jaelani, Irsan]]>
<![CDATA[ J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 2 (2023): EDISI SEPTEMBER ]]>
Publisher : <![CDATA[STIKOM Tunas Bangsa Pematangsiantar ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30645/j-sakti.v7i2.687
<![CDATA[Sentiment analysis or opinion mining is the detection of attitudes, opinions and emotions towards an object. The value of sentiment analysis can be divided into 2 types of sentiment, namely positive and negative sentiment. One of the topics that is currently being discussed by the public on Twitter social media is an AI-based chatbot application, ChatGPT. This research makes public tweets on Twitter as sentiment analysis material. Data retrieval is done using the Twitter API with data processing on Rapidminer and visualization using Power BI. The sentiment analysis process uses the Naïve Bayes algorithm by dividing the data of 301 tweets into training data and test data. Then testing using Confusion matrix to calculate the performance of the classification results. From the test results, 80% accuracy was obtained, then the Precission value was 80.95% and the Recall value 89.47%. It can be concluded that public sentiment on Twitter for the ChatGPT application tends to be positive seen from the number of positive tweet data as much as 74%.]]>
<![CDATA[Perancangan User Interface/User Experience Aplikasi Mobile Menggunakan Metode Design Thinking Pada Only One Cloth Di Purwakarta ]]>
<![CDATA[Budiharto, Sigit]]>;
<![CDATA[Ramadhan, Yudhi Raymond]]>;
<![CDATA[T, Moch. Hafid]]>
<![CDATA[ J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 1 (2023): EDISI MARET ]]>
Publisher : <![CDATA[STIKOM Tunas Bangsa Pematangsiantar ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30645/j-sakti.v7i1.579
<![CDATA[The most important stage in making a mobile application is designing an attractive display design. The Only One Cloth store still uses social media to sell products, besides that the factors that are still limited to the Only One Cloth Store are the lack of payment system organization and descriptions, therefore an application display that is needed by the store and potential users is made. The user interface (UI) is a form of graphical display that relates to potential users. User Interface works to connect users with the operating system on the computer so that prospective users can use it easily. Making the application display uses the iterative Design Thinking method where we try to understand the user, challenge assumptions, and redefine the problem in an effort to find alternative strategies and solutions. The Design Thinking method consists of five stages, namely Emphatize, Define, Ideate, Prototype, Test. At the Test stage, a test will be carried out on the value given to the task from the application display that has been made. The values that have been collected will be tested using the Single Ease Question (SEQ) method and get a value of 6.4 from the total tasks that have been assessed, if one task has a value of 5.5 then it must be iterated again. Judging from the SEQ results from the appearance of the application that is made feasible 6.4 then the appearance of the application is already easy to use by potential users]]>
