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All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Information Technology and Telematics Dinamik Jurnal Ilmiah Dinamika Teknik Pixel : Jurnal Ilmiah Komputer Grafis Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Bulletin of Electrical Engineering and Informatics International Journal of Advances in Intelligent Informatics Seminar Nasional Informatika (SEMNASIF) Proceeding SENDI_U Bulletin of Electrical Engineering and Informatics Proceeding of the Electrical Engineering Computer Science and Informatics JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Jurnal Abdimas BSI: Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmiah Universitas Batanghari Jambi JURNAL ILMIAH INFORMATIKA Jurnal Teknoinfo Jurnal Teknik Informatika UNIKA Santo Thomas IKRA-ITH ABDIMAS Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Building of Informatics, Technology and Science Jurnal Mantik Progresif: Jurnal Ilmiah Komputer Jurnal Abdi Insani Indonesian Journal of Electrical Engineering and Computer Science Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) JINAV: Journal of Information and Visualization INTELEKTIVA Advance Sustainable Science, Engineering and Technology (ASSET) Journal of Applied Sciences, Management and Engineering Technology (JASMET) Bulletin of Information Technology (BIT) Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Pengabdian Masyarakat Waradin Jurnal INFOTEL Servis : Jurnal Pengabdian dan Layanan kepada Masyarakat
Edy Winarno
Universitas Stikubank Semarang
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Public Health Social Sciences Other

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Sistem Rekomendasi Tempat Parkir di Kota Lama Semarang Menggunakan Collaborative Filtering Ahmad Samsul Muarif; Edy Winarno
Jurnal Ilmiah Universitas Batanghari Jambi Vol 22, No 2 (2022): Juli
Publisher : Universitas Batanghari Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33087/jiubj.v22i2.2066

Abstract

Utilization of information and communication technology has become an inseparable part of people's lives today. In the last few years, there have been many studies that have used information technology to solve the problems of everyday life in society. Utilizes Collaborative Filtering and Location Based Filtering methods to build a tourism recommendation system in the special area of Yogyakarta. Based on previous research, the researcher will build a parking recommendation system in the old city of Semarang using the Collaborative Filtering method. Collaborative filtering has two processes, namely the similarity calculation process and the prediction calculation. A similar calculation process is carried out to find the value between parking lots which will continue the prediction calculation process. While the estimation process is carried out to find predictions of parking spaces for visitors. The calculation process that has been carried out on Andi users gets a recommendation on parking lot I2 with the highest score of 0.565, while the lowest score is obtained by parking lot I5 with a score of -0.696.
Analysis of Color Features Performance Using Support Vector Machine with Multi Kernel for Batik Classification Edy Winarno; Wiwien Hadikurniawati; Anindita Septirini; Hamdani Hamdani
International Journal of Advances in Intelligent Informatics Vol 8, No 2 (2022): July 2022
Publisher : Universitas Ahmad Dahlan

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

Abstract

Batik is a sort of cultural heritage fabric that originated in many areas of Indonesia. Each area, particularly Semarang in Central Java, has its own batik design. Unfortunately, due to a lack of knowledge, not all residents are able to recognize the types of Semarang batik.  Therefore, this study proposed an automated approach for classifying Semarang batik. Semarang batik was classified into five categories according to this method:  Asem Arang, Blekok Warak, Gamblang Semarangan, Kembang Sepatu, and Semarangan. Since color was able to distinguish batik patterns, it is necessary to analyze color features based on the color space in order to generate discriminative features.  Color features were produced based on the RGB, HSV, YIQ, and YCbCr color spaces. Four different kernels were used to feed these features into the Support Vector Machine (SVM) classifier. The experiment was conducted using a local dataset of 1000 batik images classified into five classes (each class contains 200 images).  In order to evaluate the method, cross-validation was performed using a k-fold value of 10. The results showed that the proposed method could reach an accuracy of 1 in all SVM Kernels when employing the YIQ color space, which was consistent across all tests.
Integrated Marketing Communication [IMC] Desa Wisata Wonolopo Dalam Upaya Publikasi Ikonik “Kampoeng Jamu” Imam Husni Al Amin; Edy Winarno; Budi Hartono; Dwi Budi Santoso
IKRA-ITH ABDIMAS Vol 6 No 1 (2023): IKRAITH-ABDIMAS Vol 6 No 1 Maret 2023
Publisher : Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikra-ithabdimas.v6i1.2397

Abstract

Awareness for the community in the tourism that the area is one of the tourist destinationsthat has the potential to improve the people's economy, so the pioneers and movers of the touristvillage must be able to synergize all existing components to move together to build their villageand participate in every activity that exists during tourist visits. Management that is conditionedand managed by the community itself, so that young people who will later become pioneers andmovers are equipped with the ability to publish and promote their tourist villages by utilizinginformation technology, especially digital marketing. Optimizing the use of information technology in the form of digital marketing as a meansto promote and publicize Kampoeng Jamu, Wonolopo sub-district for young people driving theWonolopo tourist village to be very strategic in relation to the acceleration to be able to lift thepotential that exists in the area so that the tourism potential in the Wonolopo tourist village oneof them which is an icon of the Wolopo tourist village is "kampoeng Jamu" with traditionalherbal products carried so that it is more widely known. Integration of MarketingCommunication is provided in digital marketing materials with digital content in the form ofphotos of products and services as well as story telling so that they are very familiar toconsumers, followed by material on optimal use of social media that can be made viral byeveryone involved in digital marketing for tourist villages. Wonolopo, specifically forcommodities from Kampoeng Jamu
Pelestarian Budaya Batik Tulis Melalui Penggalian Potensi Kriya Batik Pewarna Alami Bagi Penggerak Deswita Wonolopo Imam Husni Al Amin; Edy Winarno; Dewi Handayani U. N.; Veronica Lusiana
IKRA-ITH ABDIMAS Vol 6 No 2 (2023): IKRAITH-ABDIMAS Vol 6 No 2 Juli 2023
Publisher : Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikra-ithabdimas.v6i2.2411

Abstract

The Wonolopo tourist village was designated by the mayor of Semarang as one of theleading tourist villages in the city of Semarang, which is located in Mijen sub-district, WestSemarang, Central Java. Wonolopo tourist village has a lot of local potential with natural wealthand uniqueness that can be proud of as one of the cultural and educational tour packages fortourists. With the uniqueness of Kampoeng Jamunya which can be juxtaposed with theexploration of natural dyed batik, it becomes the main attraction to be presented for tourists whowant to see the uniqueness of the Wonolopo tourist village area.Most of those who are driving tourist villages and tourism awareness groups (pokdarwis)do not understand the process of writing batik, let alone the use of natural dyes that can beobtained from around. One of the efforts to optimize the existing potential needs to be carriedout on an ongoing basis, training and technical guidance mainly for the community that drivesthe Tourism village in the form of written batik / stamp using the natural dye Blue Indigo. The training was given in stages starting from handling the fabric with mordanting, blazing the motifonto a piece of white cloth, painting according to the pattern drawn, the next process dyeing thefabric with natural Indigo blue dye, and finally slapping it off to remove the wax from the stick.The last process, the cloth is rinsed until it is clean from the lime that is present with the Indigopaste
Forecasting Analysis of Fishermen’s Productivity Data Using Single Exponential Smoothing Taufiq Dwi Cahyono; Heri Purwanto; Iwan Adhicandra; Kraugusteeliana Kraugusteeliana; Edy Winarno
JINAV: Journal of Information and Visualization Vol. 3 No. 2 (2022)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav1487

Abstract

One of the reasons why it is vital to forecast fisher production data in coastal regions is to increase fish resource management efficiency. By calculating the number of fishing boats, the amount of fish that must be caught, and the amount of raw materials required for fish processing based on the anticipated amount of fishermen's production in the following period, decision-makers can determine the amount of fish that must be caught and the amount of raw materials required for fish processing. So that the objective of the research is to forecast fishermen's production data using the Single Exponential Smoothing method, this method is effectively used to perform forecasting of time series data with short period data intervals to produce forecasts for the next period, and it can measure the rate of change of fishermen's production data each period. The results of forecasting data on fishermen's production utilizing time series data intervals from October 2022 to January 2023 to make forecasts for February 2023, namely a MAPE error rate of 2.85%, indicate that the forecasting results are within the "good" category.
Data clustering study of information and communication technology abilities among adolescents and adults in indonesia Muchamad Sobri Sungkar; Warkianto Widjaja; Edy Winarno; Hamid Wijaya; Firman Aziz
Jurnal Mantik Vol. 7 No. 1 (2023): May: 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.v7i1.3719

Abstract

Information and communication technology (ICT) has become an integral part of daily existence in the digital age. Internet penetration, smartphone usage, and the adoption of technology-based applications have all accelerated the growth of ICT usage in Indonesia. Nonetheless, not everyone has the same level of proficiency with ICT. In order to comprehend the characteristics of ICT users in Indonesia, the research seeks to classify ICT proficiency among adolescents and adults in Indonesia. This study classifies ICT proficiency data among adolescents and adults in Indonesia using data mining techniques, specifically the K-Means clustering algorithm. The classification of ICT proficiency data among adolescents and adults in Indonesia based on predetermined characteristics is the outcome of this study. The results indicate that provinces close to the capital city center tend to have a high proportion of 15- to 24-year-olds with ICT skills. The region of Papua that is farthest from the capital city has the lowest percentage of ICT proficiency. Rural areas typically possess fewer ICT skills than urban ones.
Real-Time Detection of Face Mask Using Convolutional Neural Network Imam Husni Al Amin; Deva Ega Marinda; Edy Winarno; Dewi Handayani U.N; Veronica Lusiana
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 3 (2023): Juni 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i3.5036

Abstract

Masks are a simple barrier that can help us prevent transmission and spread of disease from other people who enter the body, avoid exposure to air pollution, and protect the face from the adverse effects of sunlight. However, many people are still ignorant about the importance of wearing masks for health. This study aims to detect whether or not to use masks in real-time by proposing a deep learning model to reduce illness and death caused by air pollution. The convolutional Neural Network (CNN) method was used in this research to detect facial recognition using a mask and not using a mask. The public dataset used in this research consists of 1300 images with 650 data using masks and 650 data without masks. The results of this study show that the proposed CNN method works well in detecting masked and non-masked faces in real time. The proposed method obtains an accuracy value of 97.5% at epoch 50. Previous research on mask detection using the Eigenface method yielded an accuracy of 88.89%, and another study using the Viola-Jones method yielded an accuracy of 95.5%. It can be concluded that this research can increase the accuracy value of previous studies. So, this research is feasible to be applied to the detection of mask use in real time.
Sistem Pengenalan Wajah Bermasker dengan Metode Convolutional Neural Network Ibnu Halim Mustofa; Edy Winarno
Pixel :Jurnal Ilmiah Komputer Grafis Vol 16 No 1 (2023): Vol 16 No 1 (2023): Jurnal Ilmiah Komputer Grafis
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/pixel.v16i1.1062

Abstract

Face is one of the unique parts of the human body and can be used for identification purposes. Research on the application of facial recognition biometric technology has been carried out since 1960 and continues to be refined to this day. Humans can easily recognize an object or image, but not for a computer. This is the background behind the creation of a scientific discipline called Computer Vision. One deep learning algorithm that has been extensively researched and used for classifying various images is Convolutional Neural Network (CNN). The COVID-19 requires us to comply with health protocols, one of which is by wearing a mask when doing activities outside the home. The biometric presence system that is commonly used today can pose a risk of transmission because they have to touch the surface of an object that may have been contaminated from someone infected with the COVID-19 virus. Seeing the risks posed and the relevance to the times when people are accustomed to wearing masks, a study was conducted to create a masked face recognition system using the Convolutional Neural Network (CNN) method with VGG16 architecture. The dataset used was in the form of people's faces who were willing to be the object of research. This study produced highest accuracy rate of 85,71% with the application of various types of masks, namely surgical, cloth, and KF94 masks.
Multi-Accent Speaker Detection Using Normalize Feature MFCC Neural Network Method Kristiawan Nugroho; Edy Winarno; Eri Zuliarso; Sunardi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 4 (2023): August 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i4.4652

Abstract

Speaker recognition is a field of research that continues to this day. Various methods have been developed to detect the human voice with greater precision and accuracy. Research on human speech recognition that is quite challenging is accent recognition. Detecting various types of human accents with different accents and ethnicities with high accuracy is a research that is quite difficult to do. According to the results of the research on the data preprocessing stage, feature extraction and selection of the right classification method play a very important role in determining the accuracy results. This study uses a preprocessing approach with normalizing features combined with MFCC as a method to perform feature extraction and the neural network (NN), which is a classification method that works based on the workings of the human brain. Research results obtained using the normalize feature with MFCC and neural network for multiaccent speaker recognition, the accuracy performance reaches 82.68%, precision is 83% and recall is 82.88%.
The combination of color-texture features and machine learning for detecting Dayak beads Anindita Septiarini; Hamdani Hamdani; Edy Winarno
JURNAL INFOTEL Vol 15 No 1 (2023): February 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i1.856

Abstract

Dayak is one of the tribes in East Kalimantan, Indonesia, which has a lot of cultural wealth. Beads craft is one of the Dayak traditional cultures made using various materials with distinctive motifs. The Dayak beads have many different motifs and color combinations. Hence not everyone can distinguish between the bead motif of Dayak and non-Dayak easily. This study aims to develop a bead detection method to differentiate between the bead types of Dayak and non-Dayak. The main processes required include preprocessing, feature extraction, and classification. The features were extracted based on color and texture. Experiments were carried out using several machine learning approaches. The highest results were achieved using the combination of color and texture features with the implementation of K-Nearest Neighbor (KNN) methods as indicated by the parameters precision, recall, and accuracy achieved of 92%, 92%, and 92.2% using Cross-Validation with a K-Fold value of 10.
Co-Authors Achmad Solichan Aditya Putra Ramdani Agus Harjanto Agus Harjoko Agus Harjoko Agus Prasetyo Ahmad Samsul Muarif Ainun Nirwanto, Ahmad Aji Supriyanto Al Amin, Muhammad Zainudin Alam, Sitti Nur Aniati Murni Arymurthy Anindita Septiarini, Anindita Anindita Septirini Anwar, Muchamad Taufiq Arief Jananto Basirudin Ansor Bernadus Gunawan Sudarsono budi hartono Budi Hartono De Rosal Ignatius Moses Setiadi Deva Ega Marinda Devie, Erviana Dewi Handayani Untari Ningsih DEWI RAHMAWATI DHINI AMINATI NURHASANAH Dian Kristiawan Nugroho DIAS AYU LISTYORINI Diaz Aditya Dwi Budi Santoso Dwi Cahyono, Taufiq Eddy Nurraharjo Edwin Febriansyah Eka Ardhianto Eko Adi Sarwoko EngMarkiano Solissa, Everhard Eri Zuliarso Erviana Devie Fadli, Bimo Akbar Fahri Fahri Fajri, Muhamad Mushfa Hikmatal Farah Zakiyah Rahmanti Farooq, Omar Fatchurohman, Dedi Fatkhul Amin Fatkhul Amin Febyliana, Eva Ferda Ernawan Firman Aziz Gilang Fadhillah Ramadhan Hamdani Hamdani Hamdani Hamdani Hamdani Hamdani Hamid Wijaya Heri Purwanto Herny Februariyanti Hersatoto Listiyono Heru Sigit Purwanto Ibnu Halim Mustofa Imam Husni Al Amin Iwan Adhicandra Karima Elsami KHUSNUL WIBI PRASETYO Kraugusteeliana Kraugusteeliana Kurniawan, Oki Liew, Siau-Chuin Maratun Nafiah Masa, Amin Padmo Azam Muchamad Sobri Sungkar Muji Sukur Naimatul Husna Nova Christina Sari NURDIYANTO, ARIF Nurdiyanto, Arif Prajanto Wahyu Adi Prajanto Wahyu Adi, Prajanto Wahyu Pratomo, Septyo Uji Purwatiningtyas Purwatiningtyas Putra Ramdani, Aditya Rahardika, Anindyta Fernanda Safitri, Unna Ria Sari, Artini Ratna Setyawan Wibisono Setyawan Wibisono Siti Aisyah Sri Hartati Sulaksono, Aryo Windu Rahman Sulaksono, Aryo Windu Rahman Sunardi Sunardi Suryani Suryani Taufiq Dwi Cahyono Veronica Lusiana Warkianto Widjaja Wijayanti, Tri Cicik Winarko, Edi WINDU RAHMAN SULAKSONO, ARYO Wiwien Hadikurniawati Zen, Agustian Zuly Budiarso