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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Dinamik Seminar Nasional Aplikasi Teknologi Informasi (SNATI) ELKHA : Jurnal Teknik Elektro Techno.Com: Jurnal Teknologi Informasi Jurnal Simetris Elkom: Jurnal Elektronika dan Komputer Bulletin of Electrical Engineering and Informatics Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Prosiding SNATIF Jurnal Transformatika Scientific Journal of Informatics Seminar Nasional Informatika (SEMNASIF) Sisforma: Journal of Information Systems JAIS (Journal of Applied Intelligent System) Proceeding SENDI_U Jurnal Ilmiah Dinamika Rekayasa (DINAREK) Journal of Information System Jurnal Informatika Upgris Jurnal Teknologi dan Sistem Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika SISFOTENIKA JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Wikrama Parahita : Jurnal Pengabdian Masyarakat Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Eksplora Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING J-SAKTI (Jurnal Sains Komputer dan Informatika) Building of Informatics, Technology and Science Jurnal Informatika dan Rekayasa Perangkat Lunak Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Teknik Informatika (JUTIF) JUDIMAS (Jurnal Inovasi Pengabdian Kepada Masyarakat) Jurnal Program Kemitraan dan Pengabdian Kepada Masyarakat Advance Sustainable Science, Engineering and Technology (ASSET) J-SAKTI (Jurnal Sains Komputer dan Informatika) Prosiding Seminar Nasional Hasil-hasil Penelitian dan Pengabdian Pada Masyarakat Jurnal Maklumatika Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Journal of Computing Theories and Applications Seminar Nasional Teknologi dan Multidisiplin Ilmu Scientific Journal of Informatics Journal of Future Artificial Intelligence and Technologies Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK) INOVTEK Polbeng - Seri Informatika
Ajib Susanto
Universitas Dian Nuswantoro
Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering 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 Health Professions Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Physics Public Health Social Sciences Other

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CHATBOT FEATURES ON WEBSITES USING DIALOGFLOW FRAMEWORK WITH RULE-BASED METHOD Nabiha Riandika, Muhammad Afiq; Susanto, Ajib; Respatria, Nabila Maharani
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 5 (2024): JUTIF Volume 5, Number 5, Oktober 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.5.2688

Abstract

A chatbot is an artificial intelligence (AI) technology that can mimic human conversation in the form of text or voice messages through a website, or mobile application. Chatbots are widely used to facilitate communication, such as finding information, or services. In this research, the difficulty of accessing information in obtaining answers to questions asked by the public, as well as taking too long for the admin to reply when providing information to people who ask questions related to information about the topic raised, is an initial problem that will be solved in this research. Chatbot is a solution that can overcome the above problems, chatbot itself is designed to help food license applicant services on the website of the Semarang City Health Office in the field of Pharmacy and Perbekes. By utilizing the Dialogflow framework, this chatbot will use the Rule-Based method because in this development, the Rule-Based method can adjust common questions and answers that are often asked by the public, and can also be changed and even expanded to manage conversations without experiencing much difficulty in changing them that follow questions that are often asked over time. The system consists of agents, intentions, and training phrases that will be trained to understand various questions and provide relevant responses. This chatbot development aims to improve the efficiency of food licensing services, reduce applicant waiting time, and provide accurate and easily accessible information. The test results in this development are on a chatbot system that can run well, and is able to understand various kinds of questions related to food licensing, and provide appropriate responses in accordance with the predetermined intent. In addition, an evaluation of the level of user satisfaction will be carried out to measure the success of this system. This chatbot can improve the quality of public services in the field of food licensing and provide convenience for the public in processing licenses.
Enhancing MPEG-1 Video Quality Using Discrete Wavelet Transform (DWT) with Coefficient Factor and Gamma Adjustment Krismawan, Andi Danang; Susanto, Ajib; Rachmawanto, Eko Hari; Muslih, Muslih; Sari, Christy Atika; Ali, Rabei Raad
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 2 (2025): JUTIF Volume 6, Number 2, April 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.2.4422

Abstract

Low-quality video caused by compression artifacts, noise, and loss of detail remains a significant challenge in video processing, affecting applications in streaming, surveillance, and medical imaging. Existing enhancement techniques often struggle with excessive noise amplification or high computational complexity, making them inefficient for real-time applications. This study proposes an improved video enhancement method using Discrete Wavelet Transform (DWT) with optimized coefficient factor and gamma adjustment. DWT is a mathematical approach that decomposes video frames into frequency subbands, enabling selective enhancement of important details. To analyze the impact of different wavelets, this study evaluates Coif5, db1, sym4, and sym8 wavelets. The sym8 wavelet, known for its high symmetry and ability to minimize artifacts, achieves the best results in preserving fine details and structural integrity. The coefficient factor is dynamically adjusted to sharpen details while preventing noise amplification, and gamma adjustment is applied to optimize brightness and contrast. The proposed method was evaluated using Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity Index (SSIM). Experimental results show that sym8 wavelet with gamma 0.7 and coefficient factor 0.3 provides the best balance, achieving an MSE of 0.062, a PSNR of 12.050 dB, and an SSIM of 0.674, outperforming Coif5, db1, and sym4 wavelets. The results indicate that wavelet selection significantly impacts video enhancement performance, with sym8 providing superior contrast enhancement and noise suppression. This study contributes to real-time video processing and AI-based applications, ensuring enhanced visual quality with minimal computational overhead.
Hiragana Character Classification Using Convolutional Neural Networks Methods based on Adam, SGD, and RMSProps Optimizer Mulyono, Ibnu Utomo Wahyu; Kusumawati, Yupie; Susanto, Ajib; Sari, Christy Atika; Islam, Hussain Md Mehedul; Doheir, Mohamed
Scientific Journal of Informatics Vol. 11 No. 2: May 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i2.2313

Abstract

Purpose: Hiragana image classification poses a significant challenge within the realms of image processing and machine learning. Despite advances, achieving high accuracy in Hiragana character recognition remains elusive. In response, this research attempts to enhance recognition precision through the utilization of a Convolutional Neural Network (CNN). Specifically, the study explores the efficacy of three distinct optimizers like Adam, Stochastic Gradient Descent with Momentum (SGDM), and RMSProp in improving Hiragana character recognition accuracy. Methods: This research adopts a systematic approach to evaluate the performance of a Convolutional Neural Network (CNN) in the context of Hiragana character recognition. A meticulously prepared dataset is utilized for in-depth testing, ensuring robustness and reliability in the analysis. The study focuses on assessing the effectiveness of three prominent optimization methods: Stochastic Gradient Descent (SGD), RMSProp, and Adam. Result: The results of the model performance evaluation show that the highest accuracy was obtained from the RMSP optimizer with an F1-Score reaching 99.70%, while the highest overall accuracy was 99.87% with the Adam optimizer. The analysis is carried out by considering important metrics such as precision, recall, and F1-Score for each optimizer. Novelty: The performance results of the developed model are compared with previous studies, confirming the effectiveness of the proposed approach. Overall, this research makes an important contribution to Hiragana character recognition, by emphasizing the importance of choosing the right optimizer in improving the performance of image classification models.
PSNR and SSIM Performance Analysis of Schur Decomposition for Imperceptible Steganography Susanto, Ajib; Sinaga, Daurat; Mulyono, Ibnu Utomo Wahyu
Scientific Journal of Informatics Vol. 11 No. 3: August 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i3.9561

Abstract

Purpose: This research examines how well Schur decomposition-based steganography can hide data in digital images without being noticed, while also keeping the image quality high and keeping the hidden information safe. Methods: The study starts by choosing regular test images (Lena, Plane, Peppers, Cameraman, Baboon) to use for hiding messages in. The Schur decomposition is used to hide information within images in a subtle way. To test how well the new method works, we added Gaussian noise and Salt & Pepper noise after embedding. The quality of the image is determined by looking at the Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index (SSIM) metrics. Result: The research shows that Schur decomposition results in very good SSIM values (greater than 0.92) and high PSNR scores (as high as 90.27 dB) for various image sizes (64x64, 128x128, 256x256). This means that the quality of the images is not greatly reduced even after steganography is applied. Novelty: This research introduces a unique use of Schur decomposition for hiding data in images without affecting their quality. The study highlights how this method can securely hide information in digital media, which could be really useful for improving steganography techniques in the future. Future studies should concentrate on making improvements to Schur decomposition-based steganography, especially for bigger images. One possibility is to create adaptive methods that can change how images are hidden based on their content. This could make it harder for others to detect and analyze hidden information in the images.
SISTEM MONITORING SUHU DAN KELEMBABAN KANDANG AYAM BERBASIS INTERNET OF THINGS (IOT) Novita Kurnia Ningrum; Kusuma, Tiara Widya; Wahyu Mulyono, Ibnu Utomo; Susanto, Ajib; Kusumawati, Yupie
Elkom: Jurnal Elektronika dan Komputer Vol. 16 No. 2 (2023): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i2.1153

Abstract

Broiler chickens are livestock whose growth is influenced by environmental temperature. The temperature of the chicken coop that is not suitable can affect the decrease in productivity and cause death in broiler chickens, so that the temperature setting of the cage must be considered. The design of this temperature and humidity monitoring system uses a nodemcu ESP8266 microcontroller and an arduino uno. If the measured temperature exceeds the set temperature limit, the system will send an SMS to the smartphone so that the cage officer can take appropriate action.
A Comparative Study of Javanese Script Classification with GoogleNet, DenseNet, ResNet, VGG16 and VGG19 Susanto, Ajib; Sari, Christy Atika; Rachmawanto, Eko Hari; Mulyono, Ibnu Utomo Wahyu; Mohd Yaacob, Noorayisahbe
Scientific Journal of Informatics Vol 11, No 1 (2024): February 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i1.47305

Abstract

Purpose: Javanese script is a legacy of heritage or heritage in Indonesia originating from the island of Java needs to be preserved. Therefore, in this study, the classification and identification process of Javanese script letters will be carried out using the CNN method. The purpose of this research is to be able to build a model which can properly classify Javanese script, it can help in the process of recognizing letters in Javanese script easily.Methods: In this study, the Javanese script classification process has been used the transfer learning process of Convolutional Neural Network, namely GoogleNet, DenseNet, ResNet, VGG16 and VGG19. The purpose of using transfer learning is to improve the sequential CNN model, processing can be better and optimal because it utilizes a previously trained model.Result: The results obtained after testing in this study are using the transfer learning method, the GoogleNet model gets an accuracy of 88.75%, the DenseNet model gets an accuracy of 92%, the ResNet model gets an accuracy of 82.75%, the VGG16 model gets an accuracy of 99.25% and the VGG19 model gets an accuracy of 99.50%.Novelty: In previous studies, it is still very rare to discuss the Javanese script classification process using the CNN transfer learning method and which method is the most optimal for performing the Javanese script classification process. In this study, it had been resulted find an effective method to be able to carry out the Javanese script classification process properly and optimally.
Implementasi dan Evaluasi Model Machine Learning untuk Optimalisasi Prediksi Penjualan Produk Kue Kering Hilmi, Muhammad Abror Auliya; Susanto, Ajib
Building of Informatics, Technology and Science (BITS) Vol 7 No 3 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i3.8657

Abstract

The modern retail sector, such as Transmart, faces difficulties in maintaining stable sales performance due to changes in consumer behavior, variations in product types, and differing store characteristics. To address this issue, this study proposes the use of the Extreme Gradient Boosting (XGBoost) machine learning algorithm to predict retail product sales volumes based on historical data from 2024–2025. The research utilizes the CRISP-DM framework, which consists of the following stages: Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. The data cleaning and preprocessing processes involve several steps such as data cleaning, label encoding, feature selection, and data splitting with an 80:20 ratio. The model is further evaluated using the Mean Absolute Error (MAE) and the coefficient of determination (R²) metrics to assess prediction accuracy. The findings indicate that XGBoost is capable of effectively capturing sales patterns and generating accurate predictions to support decision-making strategies in the retail sector, particularly in stock planning and sales optimization. Therefore, the implementation of this data-driven predictive approach is expected to assist companies in enhancing operational management as well as improving competitiveness in the market.
Co-Authors - Wijanarto - Wijanarto -, Wijanarto -, Wijanarto Abdussalam Abdussalam Abdussalam Abdussalam Abdussalam Abiyyi, Ryandhika Bintang Adrian Angga Pramono Afrizal Aziz Maulana Agus Winarno Agus Winarno, Agus Akhmad Rizaldy Ali Muqoddas Ali, Rabei Raad Alviana Dina Putri Anak Agung Gede Sugianthara Anggraeny, Tiara Antonio Ciputra Antonius Erick Handoyo Antonius Wibowo Atmojo, Cahyo Tri Bayu Wicaksono Briliantino Abhista Prabandanu Bustami, Sri Heri Cahyani, Anis Putma Carmelita, Bastiaans Jessica Christy Atika Sari Ciputra, Antonio D.R.I.M. Setiadi De Rosal Ignatius Moses Setiadi Desi Purwanti Desi Purwanti Kusumaningrum Dian Kristiawan Nugroho Didik Hermanto Dimas Irawan Ihya’ Ulumuddin Doheir, Mohamed Dwi Puji Prabowo Dwi Puji Prabowo, Dwi Puji Eko Hari Rachmawanto Elkaf Rahmawan Pramudya Ericsson Dhimas Niagara Erwin Erwin Etika Kartikadarma Fakhriyan Nur Rofiq Farrel Athaillah Putra Febrian, Muhamad Rizky Fajar Fikri Budiman Fikri Budiman Galih Setyo Wibowo Gan, Hong-Seng Gilang Raharjito Haqikal, Hafidz Hayu Wikan Kinasih Hilmi, Muhammad Abror Auliya Ibnu Gemaputra Ramadhan Ibnu Utomo Ibnu Utomo W.M. Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono, Ibnu Utomo Ibnu Utomo WM Ihya Ulumuddin, Dimas Irawan Imam Kurniawan Imam Prayogo Pujiono Indra Kusuma Islam, Hussain Md Mehedul Istiqomah, Annisa Ayu Karis Widyatmoko Khafiizh Hastuti Krismawan, Andi Danang Kusuma, Tiara Widya Kusumawati, Yupie L. Budi Handoko Laksono, Enggar Adji Lalang Erawan Latifah Diah Kumalasari Lutfi Madiono Marjuni, Aris Md Kamruzzaman Sarker Md Kamruzzaman Sarker Mega Bintang Hatmi Moch Arief Soeleman Mochammad Lukman Mohammad Arif Muttaqin Mohd Yaacob, Noorayisahbe Muhammad Atho’il Maula Muhammad Nur Haztinanto Mulyanto, Ibnu Utomo Mulyono, Ibnu Utomo Wahyu Mulyono, Ibnu Utomo Wahyu Mulyono, Ibnu Utomo Wahyu Musfiqur Rahman Sazal Muslih Muslih Muslih Muslih Muslih Nabiha Riandika, Muhammad Afiq Ningrum, Novita Kurnia Nova Rijati Novita Kurnia Ningrum Novita Kurnia Ningrum Nugroho, Widhi Bagus Ojugo, Arnold Adimabua Ozagastra Caluella Prambudi Panjaitan, Yonathan Gani Panjaitan, Yonathan Gani Purwanto, Purwanto Putri, Clara Edrea Evelyna Sony Rachman, Rahadian Kristiyanto Raga Nufusula Raihan Yusuf Ramadhan, Aditya Wahyu Respatria, Nabila Maharani Rico Rian Alvian Rosyida, Ghaitsa Ardelia Sabilillah, Ferris Tita Saputra, The Manuel Eric Saraswati, Galuh Wilujeng Sarker, Md Kamruzzaman Sembiring, Rinawati Setiarso, Ichwan Sinaga, Daurat Sinaga, Daurat Sinar Setyawan Stefanus Santosa Sudaryanto Sudaryanto Sudaryanto Sudaryanto SUDARYANTO SUDARYANTO Sudaryanto Sudaryanto Suprayogi Suprayogi Teresa Enades Hari Setia Tiara Anggraeny Tiara Widya Kusuma Tri Wulandari Utomo W.M, Ibnu Utomo W.M, Ibnu Wellia Shinta Sari Widyatmoko Karis Wijanarto Wijanarto Wijanarto Wijanarto Wijanarto Wijanarto Yaacob, Noorayisahbe Mohd. Yupie Kusumawati Zahrotul Umami, Zahrotul Zainal Arifin Hasibuan Zuama, Leygian Reyhan