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All Journal E-Bisnis : Jurnal Ilmiah Ekonomi dan Bisnis Jurnal Teknologi Informasi dan Ilmu Komputer CESS (Journal of Computer Engineering, System and Science) Proceeding of the Electrical Engineering Computer Science and Informatics Sistemasi: Jurnal Sistem Informasi Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Informatika Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial IJCIT (Indonesian Journal on Computer and Information Technology) Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Jurnal Teknik Komputer AMIK BSI Paradigma JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Sains dan Informatika JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Informatika Universitas Pamulang Jurnal Teknoinfo Infoman's: Jurnal Ilmu-Ilmu Manajeman dan Informatika METIK JURNAL Jurnal Pengabdian Masyarakat Tekno

Windu Gata

STMIK Nusa Mandiri

Author-ID : 2438002

Aerospace Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Mathematics Social Sciences

Published : 35 Documents Claim Missing Document

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Articles

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Penggunaan Feature Selection di Algoritma Support Vector Machine untuk Sentimen Analisis Komisi Pemilihan Umum Imam Santoso; Windu Gata; Atik Budi Paryanti
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 3 No 3 (2019): Desember 2019
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

At this time sentiment analysis is very widely used by people to see the extent of people's sentiments towards an object. Objects that can be used in sentiment analysis can be various kinds, for example about the product regarding receipt by consumers, agencies or institutions regarding the performance of the agency. Whereas for this study taking sentiment analysis of the State Institution namely the General Election Commission (KPU) about the sentiments of the implementation of the ELECTION simultaneously and also the results of the implementation of the ELECTION which have become the subject of discussion by netizens on social media. So this research takes retweet data and retention comments from Twitter social media users. The algorithm used in this study is Support Vector Machine (SVM), with optimization of the use of Weight by Correlation Feature Selection (FS). The results of cross validation SVM without FS are 66.49% for accuracy and 0.716 for AUC. Whereas SVM with FS is 81.18% for accuracy and 0.943 for AUC. Very significant improvement with the use of Weight by Correlation Feature Selection (FS).

Analisis Sentimen Analisis Sentimen E-Wallet Pada Google Play Menggunakan Algoritma Naive Bayes Berbasis Particle Swarm Optimization Suwanda Aditya Aaputra; Didi Rosiyadi; Windu Gata; Syepry Maulana Husain
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 3 No 3 (2019): Desember 2019
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Increasingly sophisticated technology brings various conveniences both in transportation, information, education to the convenience of transactions in shopping, such as the development of E-wallet can now be easily done using a smartphone. From a number of e-wallet products, researchers took a case study, which is OVO product, which is currently being discussed by many groups, especially in the capital of Jakarta today. Customers or clients who are not satisfied with the services or products offered by a company will usually write their complaints on social media or reviews on Google play. However, monitoring and organizing opinions from the public is also not easy. For this reason, we need a special method or technique that is able to categorize these reviews automatically, whether positive or negative. The algorithm used in this study is Naive Bayes Classifier (NB), with the optimization of the use of Particle Swarm Optimization Feature Selection (FS). The results of cross validation NB without FS are 82.30% for accuracy and 0.780 for AUC. Whereas for NB with FS is 83.60% for accuracy and 0.801 for AUC. Very significant improvement with the use of Feature Selection (FS) Particle Swarm Optimization.

Integrasi N-gram, Information Gain, Particle Swarm Optimation di Naïve Bayes untuk Optimasi Sentimen Google Classroom Fajar Pramono; Didi Rosiyadi; Windu Gata
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 3 No 3 (2019): Desember 2019
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

The use of Learning Management System (LMS) applications made by Google with name Google Classroom since 2015 in junior and senior high schools in Bekasi City helps the learning process become easier. However, its use can have positive and negative effects on students. Google Class Sentiment by integrating N-grams, Information Gain, Particle Swarm Optimization, and Naïve Bayes Classifiers that have never been done by researchers before. From the experiments carried out, N-gram can increase the accuracy of 6.7% and AUC 4%, while using PSO can increase the Accuracy of 9.9% and AUC of 10.4%.

Pemanfaatan Sensor Suhu DHT-22, Ultrasonik HC-SR04 Untuk Mengendalikan Kolam Dengan Notifikasi Email Siswanto; Ikin Rojikin; Windu Gata
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 3 No 3 (2019): Desember 2019
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

In the case of handling rainwater reservoirs, officers are currently overwhelmed, because they have to continue to monitor changes in water level manually. This is ineffective and inefficient because officers must always be present at the location of the water reservoir. While HR is very limited. The purpose of this study is to make an application to monitor and control water levels in rainwater reservoirs with temperature & humidity sensors DHT-22, ultrasonic sensors HC-SR04 and Arduino Uno R3 microcontrollers, so that they can report quickly to staff through email notifications making it easier for staff monitor changes in water level in a rainwater reservoir remotely. This application interface is made using the Arduino programming language, for its web display using the PHP programming language and MySQL database. The results of the trial were obtained as much as 90% of users said the system created was very helpful in controlling the water level of the water reservoir and working in realtime, and as many as 10% of users said the system created was less helpful in controlling the water level of the water reservoir.

Co-Authors Abdul Hamid Abdul Latif Abdul Latif Abdussomad Abdussomad Achmad Maezar Bayu Aji Achmad Rifai Ade Irma Rizmayanti Agustiani, Sarifah Ahmad Fachrurozi Akrom, Akrom Ali Mustopa, Ali Andi Saryoko Angelina Puput Giovani Ardiansyah Ardiansyah Ardiansyah Arifin Nugroho Atik Budi Paryanti Basri Basri Chintamia Bunga Sari Dewi Cucu Ika Agustyaningrum Dedi Priansyah Deni Anugrah Sahputra Deni Gunawan Didi Rosiyadi Didi Rosiyadi Dwi Andriyanto Erni Erni Fadillah Said Fajar Pramono Fakihotun Titiani Fariszal Nova Arviantino Grace Gata, Grace Hafez Aditya Hiya Nalatissifa Ikin Rojikin Imam Santoso Ipin Sugiyarto Irwan Herliawan Istiqal Hadi Jajang jaya Purnama Jordy Lasmana Putra Kartika Handayani Khoirun Nisa Laela Kurniawati Lilyani Asri Utami, Lilyani Asri M. Anif M. Rangga Ramadhan Saelan Mawadatul Maulidah Mufid Junaedi Muhammad Fahmi Julianto Muhammad Fahmi Julianto Muhammad Iqbal Muhammad Iqbal Muhammad Rifqi Firdaus Muhammad Rifqi Firdaus Nadiyah Hidayati Nia Kusuma Wardhani Nuraeni Herlinawati Nurlaelatul Maulidah Prasetyo, Basuki Hari Rangga Pebrianto Ranu Agastya Nugraha Rendi Septian Retno Sari Rhini Fatmasari Ridan Nurfalah Ridwansyah Ridwansyah Riefky Sungkar Riki Supriyadi Risnandar, Risnandar Rizki Aulianita Safitri Linawati Saifurrachman Chohan Samudi Samudi Saputro, Ari Setiaji Setiaji Sidik Sidik Siswanto Siswanto Siswanto, Siswanto Siti Faizah Siti Khotimatul Wildah Siti Nurhasanah Nugraha Sofian Wira Hadi Sri Diantika Sri Rahayu Subandi Sukmawati Anggraeni Putri Sukri Syafrudin Suwanda Aditya Aaputra Syaifur Rahmatullah Syepry Maulana Husain Tri Rivanie Tuti Haryanti Wawan Kurniawan Widiastuti Widiastuti Yudhistira Yudhistira Yuliani, Yuri Yuliazmi Yusuf Arif Setiawan

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