Article Per Year (5 Year)
p-Index From 2021 - 2026
11.119
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah Informatika Komputer Scientific Journal of Informatics Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL REKAYASA TEKNOLOGI INFORMASI Jurnal Technopreneur (JTech) Jurnal Teknologi INFOMATEK: Jurnal Informatika, Manajemen dan Teknologi Jurnal Review Pendidikan dan Pengajaran (JRPP) Jurnal Mantik Jurnal Sistem Informasi dan Informatika (SIMIKA) Buana Information Technology and Computer Sciences (BIT and CS) JATI (Jurnal Mahasiswa Teknik Informatika) Journal of Intelligent Decision Support System (IDSS) Pena : Jurnal Ilmu Pengetahuan dan Teknologi Jurnal Cahaya Mandalika Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Jurnal Mandiri IT Brilliance: Research of Artificial Intelligence Jurnal Minfo Polgan (JMP) Journal of Practical Computer Science (JPCS) PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer Biner : Jurnal Ilmiah Informatika dan Komputer IT-Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Jurnal Masyarakat Madani Indonesia Innovative: Journal Of Social Science Research Jurnal Teknik Indonesia Journal of Elektronik Sistem InformasI Jurnal Pengabdian Masyarakat Terapan Sustainable
Gunawan
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Transportation Other

Published : 95 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 95 Documents
Search

 1   2   3   4   5 
Systematic Literature Review Implementation of the Internet of Things (IoT) in Smart City Development Gunawan; Wilda Shabrina; Wresti Andriani
Buana Information Technology and Computer Sciences (BIT and CS) Vol 3 No 2 (2022): Buana Information Technology and Computer Sciences (BIT and CS)
Publisher : Information System; Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (167.454 KB) | DOI: 10.36805/bit-cs.v3i2.2762

Abstract

Internet of Things (IoT) "The smart city concept has become a dream that big cities in Indonesia want to achieve, basically the smart city concept focuses on developing the human element using technology. IoT opens up many opportunities for new services by connecting the physical world and the virtual world to various electronic devices. IoT aims to leverage cutting-edge technology to support sustainable services for governments and their citizens. Systematic Literature Review (SLR) is one method in conducting an overview of previous interrelated researchers. The purpose of the literature study in this research is to understand trending research topics, methods, and architecture in the development of smart cities with IoT. In this study, various interesting information was found in various research journals regarding the role of IoT in building a smart city that has a role to serve smart city infrastructure, identify and analyze trends, develop smart cities and become innovations for IoT. Based on the research, there are things that need to be done to improve the study to focus more on the role of IoT that can be more utilized. IoT is also one of the technologies that are widely used in several countries in the development of IoT in the future. IoT in smart cities will become an inseparable technology because humans will increasingly depend on IoT in their daily lives
PERENCANAAN PERSEDIAAN DARAH DENGAN METODE CONTIUOUS REVIEW SISTEM PADA PALANG MERAH INDONESIA Muh Ridwan; Gunawan; Wresti Andriani
Jurnal Minfo Polgan Vol. 11 No. 2 (2022): Article Research
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v11i2.11638

Abstract

UTD PMI Kabupaten Tegal merupakan Beberapa Bank Darah Rumah Sakit (BDRS) di Kabupaten Tegal dan sekitarnya mengandalkan sumber darah ini. Karena banyaknya permintaan darah, ada kalanya tidak tersedia cukup darah, dan di sisi lain, PMI sudah berusaha semaksimal mungkin agar masyarakat tergerak kesadaran untuk berdonor darah agar stok selalu ready. Stok aman dan tanggal pemesanan darah berikutnya agar dapat ditentukan untuk mengatasi masalah kekurangan stock. Jumlah permintaan produk darah sel darah merah dalam kurun waktu 2021 yang dikumpulkan dari database PMI dan digunakan dalam analisis ini. Dalam penelitian ini digunakan metode Continuous Review System untuk mengevaluasi dan menentukan stok yang ideal guna mencegah jumlah darah yang rusak dan dapat diketahui persediaan masing-masing golongan darah. Selain itu sekaligus menurunkan biaya persediaan. Analisa yang dipakai menggunakan service level 100% sehingga diketahui savety stok, nilai ROP, Persediaan PRC Optimal dan Persediaan Maksimum PRC dan dapat mengurangi biaya sebesar 64% atau meminimalkan aliran darah keluar biaya operasional Selain itu agar masyarakat juga tahu akan pentingnya kebutuhan darah bagi pasien yang membutuhkan untuk transfusi, Temuan studi mengarah pada pasokan terbaik stok darah.
Tinjauan Pustaka Sistematis: Penerapan Metode Machine Learning untuk Deteksi Bencana Banjir Intan Mayla Faiza; Gunawan; Wresti Andriani
Jurnal Minfo Polgan Vol. 11 No. 2 (2022): Article Research
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v11i2.11657

Abstract

Banjir merupakan bencana alam yang sering terjadi di sejumlah wilayah Indonesia. Banjir menyebabkan kerusakan serta menggangu kegiatan perekonomian serta aktifitas masyarakat. Untuk meminimalisir dampak kerugian yang akan dialami dibutuhkan deteksi bencana banjir. Machine Learning dapat mempelajari pola data historis yang ada, sehingga dengan menggunakan metode machine learning dapat membantu dalam mengklasifikasikan ataupun mendeteksi apakah akan terjadi banjir atau tidak. Metode yang digunakan dalam penelitian ini yaitu Metode Systematic Literature Review. Metode SLR digunakan untuk mengevaluasi, mengkaji serta menafsirkan semua peneletian yang tersedia dengan topik yang menarik, dengan pertanyaan penelitian tertentu yang relevan. Dalam metode SLR dapat dilakukan review dan identifikasi jurnal secara sistematis yang setiap prosesnya mengikuti protokol yang telah dihasilkan. Hasil penelitian menunjukan bahwa Machine Learning merupakan metode yang dominan digunakan dalam mendeteksi bencana banjir.
Comparison of Grid Search and Evolutionary Parameter Optimization with Neural Networks on JCI Stock Price Movements during the Covid 19 Wresti; Gunawan; Purwanto; Catur Supriyanto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 6 (2022): Desember 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v6i6.4402

Abstract

This study aims to determine the effect of covid 19 on the movement of the JCI Stock Price by testing various combinations of the input variables of closed price stock data on the JCI. The analysis is carried out to find the best RMSE value from the combination of these input variables using the neural network method. The best RMSE results are compared using the optimization of grid search and evolutionary parameters. The data used in this study was taken from the Yahoo.finance.com page on the JCI Historical Data, during the covid pandemic, from 12/11/2019 to 12/30/2021. The data obtained are 509 records. The input variable used is the closing price data (closed price) as a target. The preprocessing data used are data cleansing, filtering, and windowing until seven days before. The results obtained an RMSE value of 0.104 five days before Close t (P=5), training cycle 9000. Momentum 0.9 and learning rate 0.2 is then optimized using the grid search parameter to produce RMSE 0.101, training cycle 100. Learning rate 1 and momentum 0.1 are then compared with evolutionary parameters, which make RMSE 0.103 at learning rate 0.029, momentum 0.68, and training cycle 86. Based on this research, optimizing grid search parameters produces better RMSE than evolutionary parameter optimization. This small RMSE result shows that investors are still safe to invest.
Coastal Batik Motifs Identification Using K-Nearest Neighbor Based on The Grey Level Co-occurrence Method Wresti Andriani; Gunawan; Sawaviyya Anandianskha
Buana Information Technology and Computer Sciences (BIT and CS) Vol 4 No 1 (2023): Buana Information Technology and Computer Sciences (BIT and CS)
Publisher : Information System; Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36805/bit-cs.v4i1.3342

Abstract

Indonesia is a country rich in natural, cultural, and tourism resources. One of the famous human cultural heritage in Indonesia is batik. Batik has unique motifs that are very diverse so it is difficult to recognize the in certain classes. This research was conducted to classify coastal batik, especially Tegal batik, Pekalongan batik, and Cirebon batik so that it can help facilitate the introduction and understanding of coastal batik when compared to another batik, such as Yogyakarta batik. The method used is Grey Level Co-occurrence Matrices to extract texture features, while, to determine the proximity of the test image to the training data using the K-Nearest Neighbor method, the calculation of the distance to be used is the Euclidean Distance and Manhattan Distance based on the texture characteristics of the batik image obtained. In this study, the highest score was obtained at 64% for Euclidean Distance and 66% for Manhattan Distance at k=15
Tinjauan Pustaka Sistematis: Penerapan Metode Naives Bayes untuk Klasifikasi dalam Dataset Cuaca Ahmad Zulfikri; Gunawan; Wresti Andriani
Journal of Practical Computer Science Vol. 2 No. 2 (2022): November 2022
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v2i2.2101

Abstract

This study aims to determine the application of the naive bays method for classification in Weather datasets using the systematic literature review method. Weather forecasting research is an interesting object to study because weather is one of the things that influences everyday life so good accuracy in weather forecasts is very much needed. This study uses the systematic literature review method, which is a process of identifying, assessing, and interpreting facts and evidence from available research with the aim of finding answers to a particular research question. Climate change and weather are problems faced by almost the whole world which classify and predict. The problem is that there are many influencing variables, so it is quite difficult and unpredictable. Climate and weather change is human-caused global warming which makes it more difficult to solve weather problems. The results of this study can be used to measure the level of accuracy and MSE of the weather. the dataset serves as a metric for determining precipitation groups and it is concluded that the system can make predictions with an accuracy probability of up to 92% on new data. for the precision class to get a result of 100% where the system can predict the suitability of the class that is relevant to the results of the selected class.
PREDIKSI NILAI EMAS MENGGUNAKAN ALGORITMA REGRESI LINEAR Wresti Andriani; Gunawan Gunawan; Alan Eka Prayoga
Jurnal Ilmiah Informatika Komputer Vol 28, No 1 (2023)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/ik.2023.v28i1.8096

Abstract

Harga emas yang fluktuatif menjadi salah satu tantangan dalam melakukan investasi. Oleh karenanya, prediksi harga emas menjadi penting untuk investor dalam mengambil keputusan investasi yang tepat. Penelitian ini bertujuan untuk melakukan prediksi harga emas menggunakan algoritma regresi linear. Harga emas diprediksi berdasarkan beberapa faktor, seperti suku bunga, inflasi, dan harga minyak. Data harga emas selama beberapa tahun diambil sebagai sampel untuk analisis. Model regresi linear dibangun berdasarkan faktor-faktor tersebut dan hasilnya dianalisis untuk menentukan akurasi prediksi.  Pengumpulan data dilakukan dengan mencari data histori harga emas melalui sumber website. Data yang dikumpulkan adalah harga emas, harga minyak bumi serta nilai dolar terhadap rupiah dari tahun 2019 hingga 2023, yang masing-masing sebesar 43 data.  Proses analisis data dilakukan menggunakan aplikasi RapidMiner. Hasil penelitian menunjukkan bahwa algoritma regresi linear  dapat digunakan untuk memprediksi harga emas di masa depan dengan perbandingan  metode evaluasi MAE sebesar 4341.140 lebih akurat dibanding menggunakan RMSE sebesar 4893.132. Variabel nilai mata uang dolar terhadap rupiah merupakan vaktor prnting yang bisa mempengaruhi pergerakan harga emas artinya menunjukkan model regresi linear dapat memberikan prediksi yang cukup akurat terhadap harga emas pada masa depan.
Comparison of three fuzzy logic algorithm methods for cellular selection Gunawan Gunawan; Wresti Andriani; Sawaviyya Anandianskha
Journal of Intelligent Decision Support System (IDSS) Vol 6 No 3 (2023): September : Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v6i3.154

Abstract

Many cell phone types are on the market today, increasingly making users feel confused and confused about choosing the cell that suits their needs. As one of the most essential needs at this time, users must be able to match their cellular needs with their income. Many smartphone products are offered. To help users in this study using three methods from the Fuzzy Logic algorithm for Decision Support Systems in choosing cellular according to their needs and desires; from the research that has been done, it is found that using the Fuzzy Tsukamoto method the accuracy is better than Mamdani which is equal to 0.02135, Mamdani is as large as 0.0643, while Sugeno is 0.1007. The cellular chosen is the Samsung A73 brand.
Application of the Naïve Bayes and K-Nearest Neighbor Methods for Classifying Roses Gunawan Gunawan; Wresti Andriani; Aisyach Aminarti Santoso
Jurnal Mantik Vol. 7 No. 2 (2023): Agustus: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v7i2.3911

Abstract

They are faced with the rapid development of plant science, especially the science of rose flora. The rose has a sweet-smelling charm; beautiful color. Many people, like roses, are deliberately cultivated by the beauty industry as the main ingredient in making cosmetics. Roses have various varieties, and the types have similarities, so it is difficult to distinguish, know and determine the varieties of roses; in plain view, it requires a long time and precision. In this study, the Naïve Bayes and K-Nearest Neighbor applications were used. Algorithms will be carried out for the classification of roses in addition to proving the identification and classification of rose varieties based on morphological characteristics using K-NN and Naïve Bayes to understand the diversity of roses. The Naive Bayes method produced maximum accuracy with little training data. Meanwhile, K-Nearest Neighbor was chosen because it is robust against noise data. The performance of the two methods will be compared to determine which method is better for classifying roses. The results show that the Naive Bayes method performs better, with an accuracy rate of 75%, while the K-Nearest Neighbor method has an accuracy rate of 62.5%.
TINJAUAN PUSTAKA SISTEMATIS : PENERAPAN SMART CITY DALAM SISTEM INFORMASI DESA Yan Kurniawan; Gunawan Gunawan; Wresti Andriani
Biner : Jurnal Ilmiah Informatika dan Komputer Vol 2 No 2 (2023): Juli
Publisher : Program Studi Teknik Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Sains Al-Qur'an

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penerapan konsep Smart City dalam sistem informasi desa telah menjadi fokus utama dalam upaya meningkatkan efisiensi, partisipasi masyarakat, dan keberlanjutan di wilayah pedesaan. Artikel ini menyajikan sebuah tinjauan pustaka sistematis yang bertujuan untuk menggali informasi mengenai penerapan Smart City dalam sistem informasi desa. Tinjauan pustaka ini dilakukan dengan melakukan pencarian dan analisis literatur yang relevan yang telah diterbitkan dalam jurnal-jurnal ilmiah dan konferensi yang sesuai. Melalui pendekatan ini, kami berhasil mengidentifikasi artikel-artikel yang membahas konsep Smart City, infrastruktur teknologi, aplikasi cerdas, partisipasi masyarakat, keberlanjutan, dan tantangan yang terkait. Meskipun banyak penelitian telah dilakukan tentang implementasi Teknologi Informasi dan Komunikasi (TIK) di desa, namun fungsi TIK masih sebatas sebagai pendorong. Oleh karena itu, penelitian ini memiliki tujuan penting untuk mengisi kekosongan tersebut dengan mengembangkan sebuah model konseptual Smart City dalam Sistem Informasi Desa. Model konseptual ini dibangun berdasarkan tinjauan pustaka yang dilakukan pada jurnal-jurnal yang terpercaya seperti Google Scholar, Emerald Insight, Elsevier, dan IEEE Explore dengan menggunakan kata kunci "smart village", "smart rural", dan "sustainable village". Hasil tinjauan pustaka ini menunjukkan bahwa penerapan Smart City dalam sistem informasi desa memiliki potensi besar untuk meningkatkan efisiensi pelayanan publik, pengelolaan sumber daya, dan kualitas hidup masyarakat desa. Namun, terdapat tantangan seperti kebutuhan akan infrastruktur teknologi yang memadai, ketersediaan akses internet, pemastian privasi dan keamanan data, serta partisipasi masyarakat yang aktif. Artikel ini memberikan gambaran komprehensif tentang penerapan Smart City dalam sistem informasi desa. Diharapkan tinjauan pustaka ini dapat menjadi sumber referensi bagi pembaca dalam memahami manfaat, tantangan, dan peluang yang terkait dengan implementasi Smart City dalam konteks desa. Selain itu, tinjauan pustaka ini juga memberikan dasar yang kuat untuk penelitian dan pengembangan lebih lanjut dalam bidang ini.
Co-Authors Aang Alim Murtopo Aditdya, Maulana Ahmad Zulfikri Aimar Akbar, Aminnur Aisyach Aminarti Santoso Al Fattah, Muhammad Raikhan Alan Eka Prayoga Albana, Muhammad Syifa Ali Murtopo, Aang Amalani, Mukhamad Zulfa Bakhtiar Ananda, Pingky Septiana Anandaianskha, Sawaviyya Anandianshka, Sawaviyya Anandianska, Sawaviyya Anandianskha, Sawaviyya Andriani, Wresti Andriani, Wresty Anshori, Abu Hasan Al Arif, Zaenul Arifiyah, Nur Latifatul Arrohman, Zidni Dlia Aslam, Muhammad Nur Aziz, Taufiq Azmi, Isni Azmi, Muchamad Nauval Bangkit Indarmawan Nugroho Budiono, Wahyu Cahyo, Septian Dwi Catur Supriyanto Dari, Mayang Melan Dewi, Errika Mutiara Didiek Trisatya Dodi Setiawan Dodi Setiawan Dwi Fina Fahirah Dwi Kurniawan, Rifki Fadila, Nurul Fahirah, Dwi Fina Fanti, Azizah Permata Farkhan, Muhammad Fatkhurrohman Fatkhurrohman, Fatkhurrohman Firmansyah, Akhmad Lutfi Firmansyah, Hasbi Firmansyah, Muchamad Aries Gunawan Gunawan Hafid Subechi, Fadlan Handayani, Sri Harefa, Reyvan Sinatria Haris Fadillah Hassan, Muhamad Nur Hidayatullah, Bryan Adam Intan Mayla Faiza Intan Mayla Faiza Januarto, Sigit Khadziqul Humam Munfi Khasanah, Apriliani Maulidya Khusni, Muhammad Wazid Kurniawan, Rifki Dwi Limaknun, Lulu Lutfayza, Rezi Maulana, M Taufik Fajar Miftakhuddin, Ahmad Miftakhudin, Muhammad Mohamad Rifki Septiadi Mohammad Amin Triwinanto Triwinanto Moonap, Dinar Auranisa Muchamad Nauval Azmi Muh Ridwan Muhammad Sulthon Mutaqin, Ahadan Fauzan Muttaqin, Anik Naja, Naella Nabila Putri Wahyuning Ningrum, Isna Lidia Nughroho, Bangkit Indarmawan Nugroho Adhi Santoso Nur Tulus Ujianto Nurokhman, Akhmad Nursahid, Wahyu Nursidik, Maulia Nurul Fadhilah Nurul Fadilah, Nurul Prayoga, Alan Eka Priyo Haryoko Purwanto Purwanto Putra, Alif Sya’Bani Qurrotu Aini, Atikah Rafhina, Ana Ramadhan, Ilham Gema Rifki Dwi Kurniawan Rivaldiansyah, Rafik Riyadi, Fajar Sugeng Santoso, Aisyach Aminarti Santoso, Bayu Aji Santoso, Nughroho Adhi Santoso, Nugroho Adh Santoso, Nugroho Adhi Santoso, Nugroho Adi Saputra, Aryan Dandi Sarif Surorejo Sawaviyya Anandianskha Sawaviyya Anandianskha Sawaviyya Anandianskha Sawavyya Anandianskha Septian Ari Wibowo Septiana Ananda, Pingky Septiana, Pingky Surur, Misbahu Sya’bani, Adhita Zulfa Syefudin, Syefudin Ubaidillah, Muhamad Rizal Ujianto, Nur Tulus W.N, Naella Nabila Putri Wahyu Pratama, Raka Wahyuning Naja, Naella Nabila Putri Wilda Shabrina Windi Setiawati Wresti Andriani Wresti Andriani Wresti Andriani Yan Kurniawan Yan Kurniawan, Yan Yulison Herry Chrisnanto Zaenul Arif Zain Hidayatullah, Fikri Zain, Ahmad Muzakky