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Analisis Sentimen Seputar UU ITE Menggunakan Algoritma Support Vector Machine Yoga Vikriansyah Wijaya; Adhitia Erfina; Cecep Warman
Progresif: Jurnal Ilmiah Komputer Vol 17, No 2: Agustus 2021
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (512.882 KB) | DOI: 10.35889/progresif.v17i2.644

Abstract

AbstractSentiment analysis of twitter tweets from the Indonesian people can be used as one of the parameters to be a support for the government in evaluating decision making and policies in the future. This study aims to find out the sentiments of Indonesian people's tweets on Twitter about the Information and Electronic Transaction Law. The data material used in this study uses a query on the Information and Electronic Transaction Law, Hate Speech, Defamation, Online Fraud, and Data Theft. The test is carried out by calculating accuracy, precision, recall and F1-score, using a variety of training data and test data. The highest accuracy results were obtained from the composition of 90% training data and 10% test data with an accuracy value of 84% with an average precision of 84%, recall 65%, f1-score 71% for each sentiment class.Keywords: Sentiment Analysis, Support Vector Machine Algorithm, Community TweetAbstrakAnalisis Sentimen cuitan twitter dari masyarakat Indonesia dapat dijadikan sebagai salah satu parameter untuk menjadi penunjang bagi pemerintah dalam mengevaluasi pengambilan keputusan dan kebijakan di masa yang akan datang. Penelitian ini bertujuan untuk mengetahui sentimen dari cuitan masyarakat Indonesia di twitter seputar Undang-Undang Informasi dan Transaksi Elektronik. Bahan data yang digunakan dalam penelitian ini menggunakan query Undang-Undang Informasi dan Transaksi Elektronik, Ujaran Kebencian, pencemaran nama baik, Penipuan Online, dan Pencurian data. Pengujian dilakukan dengan perhitungan akurasi, precision, recall dan F1-score, dengan menggunakan variatif data latih dan data uji. Hasil akurasi tertinggi didapatkan dari komposisi data latih 90% dan data uji 10% dengan nilai akurasi 84% dengan rata-rata precision 84%, recall 65%, f1-score 71% tiap kelas sentimen.Kata Kunci: Analisis Sentimen, Algoritma Support Vector Machine, Cuitan Masyarakat
Decision Support System For New Employee Recruitment In PT. Prosweal Indomax Using The Simple Additive Weighting Anti Aprianti; Yayatillah Rubiati; Muhamad Renaldi Aripin; Cecep Warman; Dudih Gustian
INTERNATIONAL JOURNAL ENGINEERING AND APPLIED TECHNOLOGY (IJEAT) Vol. 3 No. 1 (2020): International Journal of Engineering and Applied Technology (IJEAT)
Publisher : Nusa Putra University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (865.115 KB) | DOI: 10.52005/ijeat.v3i1.39

Abstract

The eligibility for hiring new employees based on certain criteria that the company expects is something that is very rarely obtained. The acceptance process may result in inaccurate and productive decisions due to inefficient admission processes. There are several criteria in making decisions about the recruitment of new employees at PT. Prosweal Indomax, which is based on latest education, expertise, age and work experience. Purpose made This system is able to help make decisions to determine the optimal recruitment process using the method Simple Additive Weighting (SAW). This method was chosen because this method determines the weight value for each attribute, then is followed by a ranking process that will select the best alternative. The research was conducted by finding the weighted value for each criterion, and then creating a ranking process that would determine which alternative was the best applicant.
Design and Build a Population Administration Data Collection Application System Using the Zachman Framework Anti Aprianti; Yayatillah Rubiati; Muhamad Renaldi Aripin; Cecep Warman
INTERNATIONAL JOURNAL ENGINEERING AND APPLIED TECHNOLOGY (IJEAT) Vol. 4 No. 1 (2021): International Journal of Engineering and Applied Technology (IJEAT)
Publisher : Nusa Putra University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1076.516 KB) | DOI: 10.52005/ijeat.v4i1.48

Abstract

The purpose of this study is to determine how the application of the Zachman Framework in designing a population administration data collection system in Kadaleman village, because the current process is still carried out conventionally so that data storage is irregular. In analyzing the system using the Zachman Framework approach with a Planner, Owner, Designer, and Builder perspective and perspective issues, namely What, How, Where, Who, and When. For system modeling using UML. Data was collected by using observation, interview, literature study, and distributing questionnaires involving 35 respondents. Measurement of data using a Likert scale, with correlation test analysis using Spearman rho. The implementation of a web-based prototype system with the results of the usability value test on the system application shows that the system has met the aspects of learnability, efficiency, memorability, errors, and satisfaction. The results of the correlation analysis of the Zachman Framework model on the system built have a very strong correlation, which implies that the system built through the Zachman Framework approach can be realized and implemented
Perancangan Arsitektur Sistem Pemesanan Tiket Wisata Online Menggunakan Framework Zachman Sudin Saepudin; Egit Pudarwati; Cecep Warman; Sihabudin Sihabudin; Giri Giri
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 11, No 2 (2022): JULI
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v11i2.1415

Abstract

Penerapan sistem teknologi saat ini semakin berkembang dan mulai merambah ke berbagai sektor. Semua aktifitas yang dilakukan oleh sebuah bidang usaha semakin tidak terlepas dari pengaruh teknologi. Salah satu sektor yang berkembang dalam perkembangan teknologi adalah bidang pariwisata. Salah satunya yaitu wisata situ sukarame yang dalam menjalankan kegiatannya masih manual, seperti dalam pemesanan tiket masuk. Cara ini kurang efektif, karena mengakibatkan antrian yang sangat panjang dan membuat petugas loket kesulitan dalam menghitung jumlah wisata yang masuk per rombongan. Oleh karena itu, perancangan suatu sistem informasi penunjang kerja pada suatu objek wisata dirasa sangat dibutuhkan untuk kemajuan ke depannya. Dengan adanya perancangan enterprise architecture tiket wisata ini diharapkan bisa membantu dalam permasalahan yang ada khususnya dalam melakukan proses pemesanan tiket wisata yang lebih cepat, efektif, dan efisien. penelitian ini menggunakan metode pengumpulan data dengan melakukan observasi, wawancara dan studi pustaka. kemudian penelitian ini menggunakan framework zachman untuk melakukan klasifikasi pengorganisasian artifak enterprise. Zachman Framework terdiri dari 6 kolom dan 6 baris. Tiap kolom merepresentasikan fokus, abstraksi, atau topik arsitektur enterprise, yaitu: data, fungsi, jaringan, manusia, waktu, dan motivasi. Berdasarkan hasil penelitian yang telah dilakukan maka dapat diambil kesimpulan bahwa Penelitian ini menghasilkan analisis dan perancangan tiket wisata online yang dapat mengolah data pengunjung dan mengetahui jumlah pengunjung yang datang setiap hari nya dengan menggunakan framework zachman. Analisis dan perancangan ini dapat digunakan sebagai landasan pengembangan sistem informasi tiket wisata agar pengembangan sesuai dengan kebutuhan serta mempermudah wisatwan untuk membeli tiket dengan aplikasi ini
Peran Karakteristik Kepemimpinan dan Budaya Organisasi dalam Peningkatan Kinerja Karyawan di Mediasi oleh Variabel Motivasi Guli, Guli; Kahpi, Heri Sapari; Warman, Cecep; Fathurrohman, Fathurrohman
JIIP - Jurnal Ilmiah Ilmu Pendidikan Vol. 4 No. 4 (2021): JIIP (Jurnal Ilmiah Ilmu Pendidikan)
Publisher : STKIP Yapis Dompu

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (658.241 KB) | DOI: 10.54371/jiip.v4i4.262

Abstract

Tujuan dari penelitian ini untuk mengujiperan motivasi dalam memediasi pengaruh karakteristik pemimpin dan budaya organisasi terhadap kinerja karyawan dengan menggunakan Structural Equation Modeling. Sampel yang diambil adalah 100 karyawan dengan menggunakan purposive sampling didasarkan pada judgment sampling. Hasil penelitian menunjukkan bahwa hasil efek tidak langsung karakteristik pemimpin terhadap kinerja melalui motivasi artinya positif dan signifikan signifikan. Budaya organisasi terhadap kinerja melalui motivasi berarti signifikan. Pengaruh total (total effect) karakteristik pemimpin terhadap kinerja melalui motivasi adalah 0,418 (0,204 + 0,214) dengan VAF sebesar 0,633 (0,418 + 0,214). Sedangkan pengaruh total (total effect) budaya organisasi terhadap kinerja melalui motivasia dalah 0,347 (0,226 + 0,121) dengan VAF sebesar 0,347 (0,347 + 0,121). Hasil VAF pengaruh karakteristik pemimpin terhadap kinerja melalui motivasi bernilai 0,633 atau 63,3% ini dikategorikan memediasi penuh, Hasil VAF pengaruh budaya orgnasisasi terhadap kinerja melalui motivasi bernilai 0,347atau 34,7% ini dikategorikan memediasi penuh.
ANALISIS PENGGUNAAN CHAT GPT (AI) DAN MODUL PEMROGRAMAN TERHADAP MOTIVASI BELAJAR DAN KREATIVITAS MAHASISWA DALAM MATA KULIAH PEMROGRAMAN PADA PROGRAM STUDI PENDIDIKAN TEKNOLOGI INFORMASI, UNIVERSITAS BINA BANGSA Mutaqin, Reihan; Desty Endrawati Subroto; Cecep Warman
Jurnal Saintifik (Multi Science Journal) Vol 22 No 1 (2024): JANUARI
Publisher : Fakultas Pertanian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58222/js.v22i1.214

Abstract

This research aims to analyze the use of CHAT GPT (AI) and Programming Module on students' understanding of programming in the Department of Information Technology Education at Bina Bangsa University. The research method used is a descriptive quantitative approach, with questionnaires distributed to 70 students as the population, and a sample of 35 students from two classes, namely 6A and 6B, was taken. The research subjects were given questionnaires, and the data were analyzed using the Likert scale as a measurement scale. The questionnaires were distributed through the Google Form platform. The results of the research show that the use of CHAT GPT (AI) is preferred by students in classes 6A and 6B in understanding programming concepts compared to the use of Programming Module. The utilization rate of CHAT GPT (AI) reaches 93.33% in class 6A and 75.24% in class 6B, while the utilization rate of Programming Module is only 75.91% in class 6A and 88.91% in class 6B. Therefore, CHAT GPT (AI) has good potential as a learning tool to help students understand programming concepts. The research results also indicate that the use of CHAT GPT (AI) and Programming Module has a positive impact on students' understanding in the programming course.
GAME DEVELOPMENT PROJECT MANAGEMENT USING SCRUM FRAMEWORK: HYPERCASUAL GAME CASE STUDY 'RUSH RUNNER' Nurjaman, Moh.; Baturohmah, Habi; Warman, Cecep
Jurnal Pilar Nusa Mandiri Vol. 20 No. 2 (2024): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v20i2.5555

Abstract

The research aims to explore and implement an effective Project Management approach in Game Development using the Scrum Framework. A case study was conducted on the development of a hypercasual game titled "Rush Runner." With a focus on rapid iterations, continuous feedback, and adaptation to changes, the Scrum methodology was used to manage the game development workflow from planning to publication. Concrete steps were taken to adapt to user needs and evolving demands as an integral part of the development process. The research findings indicate that the implementation of Scrum had a positive impact on productivity, quality, and user satisfaction in hypercasual game development. Furthermore, the integration of Project Management and the Scrum approach optimized overall time, cost, and quality. These findings provide valuable insights for practitioners and researchers in the field of game development to understand the importance of an adaptive and responsive Project Management approach to market changes and user needs.
Pemberian Imunisasi Pada Bulan Imunisasi Anak Nasional (BIAN) di Kelurahan Gerogol, Kecamatan Gerogol – Kota Cilegon Desty Endrawati Subroto; Yuliawati; Cecep Warman; Fidziah
Journal of International Multidisciplinary Research Vol. 2 No. 1 (2024): Januari 2024
Publisher : PT. Banjarese Pacific Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62504/kmwm0064

Abstract

Imunisasi merupakan Langkah untuk mencegah penyakit menular dengan cara memberikan vaksin pada seseorang sehingga tubuhnya resisten terhadap penyakit tertentu. Dalam prosesnya imunisasi dilakukan dengan cara pemberian vaksin yang akan diberikan melalui suntik ataupun minum. Adapun, tujuan imunisasi adalah  untuk membentuk imun tubuh yang kuat, meningkatkan sistem kekebalan tubuh pada anak, dan melindungi tubuh dari berbagai penyakit yang beresiko kematian. Dalam rangka Imunisasi Nasional (BIAN), pada bulan Mei Tahun 2023 dilakukan kegiatan PKM Pemberian Imunisasi Campak Rubela di Posyandu Seroja 1 Link, Ciora Tengah, Kelurahan Gerogol – Kota Cilegon. Kegiatan ini melibatkan UPTD Gerogol, segenap Bidan Desa dan Kader Posyandu. Dalam melaksanakan kegiatan pengabdian masyarakat tentang pemberian  Imunisasi di Kelurahan Gerogol. Metode yang diterapkan pada kegiatan ini : A. Perencanaan, B. Pelaksanaan, C. Evaluasi. Adapun, tujuan  diadakannya Kegiatan Pengabdian Masyarakat ini yakni menciptakan kegiatan yang mampu untuk mengurangi tingkat penyebaran penyakit menular seperti campak dan rubella sehingga hal ini bisa dicegah dengan melakukan imunisasi secara berlangsung.
Sentimen Analisis Kegiatan Trading Pada Ap-likasi Twitter dengan Algoritma SVM, KNN Dan Random Forrest Wardani, Neng Resti; Saepudin, Sudin; Warman, Cecep
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.497

Abstract

This study aims to find out how people comment on trading activities that are currently busy. As we know that lately there have been cases of trading involving affiliates, many people feel that they have been deceived by these activities. From this case, we conducted research using data collection methods regarding trading, which were taken from the Twitter social media platform using the Orange application. The data obtained through the scraping process will then be filtered to separate positive and negative sentiments, so that the data ready for sentiment analysis is 1,400 tweets. Data were analyzed using three methods, namely Random Forest, KNN, and SVM (Support Vector Machines). The results obtained from the research conducted which has 3 variables, namely positive sentiment has a value of 29%, negative is 10%, and neutral has a value of 62%. To analyze sentiment data from Twitter the author uses 3 classification methods and produces an accuracy value of KnN of 0.999, Random forest 0.994 and Naïve SVM 0.992. Based on the results of the analysis that has been carried out regarding trading activities, people think that not all trading is illegal and fraudulent because many sites are still legal
Sentimen Analisis Kegiatan Trading Pada Ap-likasi Twitter dengan Algoritma SVM, KNN Dan Random Forrest Wardani, Neng Resti; Saepudin, Sudin; Warman, Cecep
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.497

Abstract

This study aims to find out how people comment on trading activities that are currently busy. As we know that lately there have been cases of trading involving affiliates, many people feel that they have been deceived by these activities. From this case, we conducted research using data collection methods regarding trading, which were taken from the Twitter social media platform using the Orange application. The data obtained through the scraping process will then be filtered to separate positive and negative sentiments, so that the data ready for sentiment analysis is 1,400 tweets. Data were analyzed using three methods, namely Random Forest, KNN, and SVM (Support Vector Machines). The results obtained from the research conducted which has 3 variables, namely positive sentiment has a value of 29%, negative is 10%, and neutral has a value of 62%. To analyze sentiment data from Twitter the author uses 3 classification methods and produces an accuracy value of KnN of 0.999, Random forest 0.994 and Naïve SVM 0.992. Based on the results of the analysis that has been carried out regarding trading activities, people think that not all trading is illegal and fraudulent because many sites are still legal