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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Techno Nusa Mandiri : Journal of Computing and Information Technology JURIKOM (Jurnal Riset Komputer) Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Jurnal Sistem Komputer dan Informatika (JSON)
Ultach Enri
Departemen Studi Teknik Informatika, Fakultas Ilmu Komputer, Universitas Singaperbangsa Karawang, Karawang, 41361
Humanities Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Analisis Sentimen Pada Isu Vaksin Covid-19 di Indonesia dengan Metode Naive Bayes Classifier Fitria Septianingrum; Jajam Haerul Jaman; Ultach Enri
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3260

Abstract

The Covid-19 pandemic that has occurred in Indonesia and even in the world has not yet ended. Various efforts have been made by the Indonesian government to minimize the spread of this virus, such as the implementation of a lockdown, Large-Scale Social Restrictions (PSBB), a ban on going home during the Eid al-Fitr holiday, and so on. One of the new policies issued by the government is the vaccination program, where the government has started implementing the program since early 2021 for the people of Indonesia, which aims to increase antibodies to avoid exposure to the Covid-19 virus. To find out opinions, comments, or feedback given by the public on this new policy, sentiment analysis can be done. The process of this sentiment analysis includes data collection, namely the crawled tweet data originating from the Twitter social media. The data is then selected for further pre-processing stage so that the data is clean and ready for classification. Furthermore, sentiment weighting is carried out for data labeling using a lexicon dictionary and negative words. Then after that, the terms or words are weighted with tf-idf and followed by the feature selection process using Information Gain. Furthermore, the classification process is carried out using the Naive Bayes Classifier algorithm to classify the data into 3 classes, namely positive, negative, and neutral sentiments. The results of this study are to produce a model accuracy rate of 78%, recall 80%, and an AUC score of 0.904.
PENERAPAN KNOWLEDGE MANAGEMENT SYSTEM BERBASIS INFORMASI DESA UNTUK MENINGKATKAN LAYANAN PUBLIK DESA DUKUH KARYA Purwantoro Purwantoro; Yuyun Umaidah; Ultach Enri
Techno Nusa Mandiri: Journal of Computing and Information Technology Vol 15 No 2 (2018): TECHNO Periode September 2018
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1405.382 KB) | DOI: 10.33480/techno.v15i2.21

Abstract

The rank of EGDI level (E-Government Development Index) in Indonesia has decreased and it reflects the development conditions of EGovernment in Indonesia are not maximally covering: the level of public services, there is a disparity in public services in the village, the support of information technology devices is still limited, the absence of village archive management, the absence of a system that can manage knowledge, there is no synergy between village apparatus. Dukuh Karya is a village that belongs to Karawang Regency, Rengasdengklok District. Dukuh Karya village has a population of around 6000 and mostly the residents has income from agricultural products. The need for knowledge managers in the village is to manage properly and implement a Knowledge Management System (KMS) based on village information systems can improve public services in the Dukuh Karya village. By applying the concept of KMS to be able to collect and manage all available knowledge. Building Knowledge, collect, store and use it so that the village government can be more transparent and accountable to improve public services. The implementation of KMS is a way for village apparatus to identify, create, represent, distribute, and enable the adaptation of insights and experiences consisting of knowledge, both owned by individuals and knowledge that is inherent in the process or standard of service procedures that have the main objective to maintain and effectively transfer knowledge that is important to improve the quality of service of village government apparatus to its citizens.
Analisis Sentimen Terhadap Bakal Calon Presiden 2024 Dengan Algoritme Naïve Bayes Muhammad Raihan Fais Sya' bani; Ultach Enri; Tesa Nur Padilah
JURIKOM (Jurnal Riset Komputer) Vol 9, No 2 (2022): April 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i2.3989

Abstract

Presiden Indonesia saat ini telah memegang jabatan yang sama selama 2 periode secara berturut – turut yang mana pada dasar peraturan untuk menjadi calon presiden sudah tidak bisa mencalonkan kembali menjadi presiden, dalam hal itu banyak lembaga survei yang telah mengeluarkan hasil survei terhadap beberapa tokoh yang memiliki elektabilitas untuk bisa menjadi calon presiden, berdasarkan hal tersebut juga banyak warganet yang menyampaikan pendapat, dari pendapat tersebut bisa dibuat kesimpulan mengenai sentimen warga masyarakat terhadap suatu tokoh bakal calon presiden tersebut dengan menggunakan metode Knowledge Discovery from Data dengan menggunakan algoritme naïve bayes dan perhitungan skor sentimen dengan harapan dari penelitian ini bisa memberikan bahan referensi kepada masyarakat dalam memilih presiden di pilpres yang akan datang. Hasil dari penelitian ini mendapatkan kesimpulan bahwa warganet memiliki sentimen positif terhadap setiap tokoh bakal calon presiden yang akan datang. Kemudian untuk hasil evaluasi dari algoritme naïve bayes yang didapatkan dari dataset pertama adalah 73,68 akurasi dan AUC 0,74 pada fold ke-7, dataset kedua adalah 71,43 untuk akurasi dan AUC 1,0 pada fold ke – 5, untuk dataset ketiga nilai akurasi yang didapat 60% dan AUC 0,92 pada fold ke-1, dan untuk dataset terakhir nilai akurasi yang didapatkan adalah 62,5% dan AUC 0,65 pada fold ke-3.
Designing animated videos as culinary tourism promotion in Tegal Sawah Village, Karawang City Ultach Enri; Yuyun Umaidah; Apriade Voutama; Chaerur Rozikin; Richard Julianno Soeganda; Ahmad Ridhoi Fajri; Muhammad Nur Yasin
Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Vol 7, No 2 (2022): May 2022
Publisher : University of Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/abdimas.v7i2.6683

Abstract

Tegal Sawah Village is also famous for its culinary cuisine, namely processed Tutut. By utilizing the scenery of vast rice expanses and various kinds of culinary processing, it makes Karang Taruna Tegal Sawah Village and residents want to make rice field culinary tourism villages to increase the income of residents and also MSMEs in particular. As support for planning, it takes an animated video of rice field tourism planning. The purpose of making animated videos is to help provide the understanding and a design for developing rice field culinary tourism village’s implementation methods by conducting live surveys, place measurements, and animation creation using SketchUp applications. The results of the measure are planned to be 440 m2 road, irrigation canal 243 m2 and rice fields 5307 m2 which will be built more than 15 huts or saung, hydroponic area, parking area, photo booth seats, trash cans, arches, sinks, and various decorations. After the animation is completed then socialization in the village apparatus and the community. Socialization was carried out in front of the Tegal Sawah village apparatus, and the community got a good response and hoped that the video could be realized.
Analisis Sentimen Ulasan Pengguna Aplikasi Myim3 Pada Situs Google Play Menggunakan Support Vector Machine Piqih Aditiya; Ultach Enri; Iqbal Maulana
JURIKOM (Jurnal Riset Komputer) Vol 9, No 4 (2022): Agustus 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i4.4673

Abstract

Technological developments are increasingly rapid, this makes it easier to communicate information and shopping transactions, one of the innovations that are being adopted is digital services, such as self-service. One of the self-services is myim3 which is a product of PT Indosat Ooredoo Hutchison as an internet network service provider company, with the increasing number of users of the application, many opinions or public sentiments are shared in the comments or reviews column, therefore it is necessary to analyze this MyIM3 application review to find out public opinion about the application. The review data is obtained from the Google Play website which is retrieved using the scraping method with the help of 3rd party libraries in python. The amount of data obtained in this study was 3484 data. Experts assist in data labeling to determine positive and negative. In the preprocessing stage, the data is cleaned to reduce the less influential attributes. In the next stage, perform the transformation process with TF-IDF. The classification process is divided into several scenarios with the algorithm used as a support vector machine with 2 kernels, linear and RBF. The best results are in the scenario (70:30) for the linear kernel with 87% accuracy and the scenario (90:10) with 87% accuracy in the RBF kernel. The classification process produces the most frequently occurring words in each sentiment class which is visualized with a word cloud. The word "good" is the most dominant in the positive review data, while the word "network" is the most dominant in the harmful review data of the MyIM3 application
Penerapan Algoritma K-Means dan Decision Tree Dalam Analisis Prestasi Siswa Sekolah Menengah Kejuruan Muhammad Bari Abdul Majid; Yusup Mad Cani; Ultach Enri
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 2 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i2.5299

Abstract

This study aims to determine how much influence parents' income and the distance from a student's home to school have on student achievement at SMK Tarbiyatul Ulum. Because if you know the factors that influence student achievement, steps or actions can be taken to improve student achievement. The method used in this study includes the use of clustering using K-Means and then classifying it using the Decision Tree method with a total of 157 datasets used as research material. After conducting the classification modeling using the decision tree algorithm, it was found that parents' income did not affect student achievement, but the distance from home to school did affect student achievement. Then at the evaluation stage, the decision tree algorithm is not suitable for use in predicting student achievement, because the accuracy and AUC values of this algorithm are 68% and 0.561, where these values fall into the failure category.
Co-Authors Ahmad Ridhoi Fajri Apriade Voutama Chaerur Rozikin Fitria Septianingrum Iqbal Maulana Jaman, Jajam Haerul Muhammad Bari Abdul Majid Muhammad Nur Yasin Muhammad Raihan Fais Sya' bani Piqih Aditiya Purwantoro Purwantoro Richard Julianno Soeganda Tesa Nur Padilah Yusup Mad Cani Yuyun Umaidah