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All Journal Jurnal Ilmiah Informatika Komputer Teknika Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Informatika dan Teknik Elektro Terapan CESS (Journal of Computer Engineering, System and Science) Jurnal CoreIT JURNAL KAJIAN TEKNIK ELEKTRO JTAM (Jurnal Teori dan Aplikasi Matematika) METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi INTECOMS: Journal of Information Technology and Computer Science KACANEGARA Jurnal Pengabdian pada Masyarakat Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) IJID (International Journal on Informatics for Development) JURIKOM (Jurnal Riset Komputer) Jurnal Tekno Kompak TEKNOKOM : Jurnal Teknologi dan Rekayasa Sistem Komputer Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Indonesian Journal of Electrical Engineering and Computer Science Bubungan Tinggi: Jurnal Pengabdian Masyarakat Jurnal Manajemen Informatika Jayakarta International Journal Software Engineering and Computer Science (IJSECS) Berdikari : Jurnal Pengabdian kepada Masyarakat Malcom: Indonesian Journal of Machine Learning and Computer Science Technology and Informatics Insight Journal KAMI MENGABDI Journal of Data Science Theory and Application Journal of Digital Business and Management Prosiding Seminar Nasional Rekayasa dan Teknologi (TAU SNAR- TEK) Jurnal Indonesia : Manajemen Informatika dan Komunikasi Edusight International Journal of Multidisciplinary Studies (EIJOMS) International Journal of Law Social Sciences and Management Computer Journal
Tundo, Tundo
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Classification of Apple Ripeness Detection System Using Self-Organizing Map (SOM) Method Tundo; Shindy Apriani; Sugeng
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3734

Abstract

Apple (Malus Domestica) is one of the most popular types of fruit and is in high demand by the public because of its varied flavors. Apples have many nutrients and various vitamins including healthy fats, carbohydrates, proteins, vitamins and many more. The Apple is one of the apple varieties developed in Batu City, Malang and planted in several areas with suitable agroclimates for apple growth. This research uses Anna apple images as datasets. Various ways can be employed to distinguish Anna apples' maturity, including through color image analysis. But to the naked eye, Anna apples are often difficult to distinguish. This research classifies the maturity of Anna apples based on color analysis with the Self-Organizing Map method. Using Google Colab and Python programming language and datasets from kaggle.com as many as 139 datasets, 46% training data, 54% validation data. The Self-Organizing Map method was chosen because of its ability to recognize visual patterns accurately. The accuracy of the results based on the SOM Method performance evaluation metrics namely Quantization Error, Silhouette Score and Topographic Error. Quantization Error RGB (0.004737) is lower than HSV (0.073178) which indicates RGB's ability is effective in representing data in SOM. Silhouette Score HSV (0.704204) is higher than RGB (0.599846) indicating the ability of HSV is slightly better in grouping objects.
Chili Type Detection System Using Principal Component Analysis Method Rindy Julianda; Tundo; Sugeng
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3735

Abstract

Classification of types of chili vegetables is an important aspect in the agricultural industry to increase the efficiency of product management, packaging and distribution. This research aims to implement the Principal Component Analysis (PCA) method in the process of classifying vegetables and types of chilies. PCA is used to reduce the dimensionality of the data and extract the main features that are significant in distinguishing vegetable categories. The research dataset consists of digital images of chili vegetables which are extracted into color, texture and shape attributes. The research results show that PCA is able to significantly improve classification accuracy by minimizing computational complexity. Experiments were carried out with various numbers of principal components in PCA to determine the optimal configuration. In the best configuration, this method achieves classification accuracy of 90%, with PCA effectively reducing data dimensionality by up to 95% without losing important information. In conclusion, this approach has great potential to be implemented in vegetable classification automation systems to support efficiency in agricultural supply chains.
Prediksi Produksi Sablon di Perusahaan Tomoinc dengan Perbandingan Metode Single Moving Average dan Single Exponential Smoothing Galih Satria Yacob; Tundo; Dadang Iskandar Mulyana; Sri Lestari
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 1 (2025): JANUARI-MARET 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i1.3018

Abstract

A common problem faced by companies is predicting future production of goods based on previously recorded data. The company produces only according to orders, conducting production processes solely based on consumer demand. Any excess production is stored as stock to meet sudden consumer demands. These predictions significantly influence management decisions regarding the quantity of goods that must be prepared, considering factors like general business and economic conditions, competitors' actions, government policies, market trends, product life cycles, styles and fashions, changes in consumer demand, and technological innovations. This research aims to identify and analyze screen printing production predictions using the Moving Average and Exponential Smoothing methods. The more data used for comparison, the more accurate the prediction results. The research successfully developed a screen printing production prediction system, facilitating easier determination of future production quantities.
Analisis Sentimen Kepuasan Publik Terhadap Masa Kepemimpinan Shin Tae Yong Menggunakan Algoritma Naïve Bayes Pramudya Nugraha; Rasiban; Frencis Matheos Sarimole; Tundo
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 1 (2025): JANUARI-MARET 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i1.3020

Abstract

Shin Tae Yong is the coach of the Indonesian national team who has been a football player in South Korea and has coached the South Korean national team at the 2018 World Cup in Russia. Many people watch or pay attention to Shin Tae Yong's behavior and behavior when coaching the Indonesian national team. Shin Tae Yong has considerable worry with the Indonesian national team because of his strategy. However, there are several media that frame Shin Tae Yong's news differently so that differences in viewpoints and opinions on Shin Tae Yong are controversial, inviting many people to give their opinions. Therefore, people choose social media as a place to channel opinions. In this study, we will take tweets from X with search keywords for Shin Tae Yong and the Indonesian national team to process and classify the text using the sentiment analysis method. The text classification process is divided into two classes, namely positive sentiment classes and negative sentiment classes. The data used amounted to 2495 data that had been cleansed, which amounted to 2.348 Positive sentiment data and 147 data with negative sentiments so that they can be presented 98.94% positive and 60.00% negative, based on the classification of the Naïve Bayes algorithm model, using a split comparative data 0.8 :  0.2 With the value of k=3 for Shin Tae Yong's dataset, an accuracy value of 96.67%.
Penerapan IoT dalam Sistem Monitoring Suhu dan Kelembapan pada Lahan Bawah Tanah (Basement) Masjid Al-Barkah Tundo; Anisah Nurul Azhar; Kiki Setiawan; Raisah Fajri Aula
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 1 (2025): JANUARI-MARET 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i1.3199

Abstract

Underground areas, commonly referred to as basements, are often used for essential functions such as parking and electrical distribution spaces. However, unstable temperature and humidity levels due to poor air circulation can affect comfort and safety. Therefore, a system capable of automatically monitoring and controlling temperature and humidity is needed to optimize comfort and energy efficiency. This research employs an Internet of Things (IoT) approach using a DHT11 sensor to detect temperature and humidity in the basement. The data collected by the sensor is processed using a NodeMCU ESP32 microcontroller and then displayed in real-time on a web-based application via the cloud. The system also automatically controls the fan/blower to maintain ideal conditions in the basement. The results of this research show that the implemented IoT system demonstrates high effectiveness in monitoring temperature and humidity in real-time, providing accurate data, enabling energy savings by automatically regulating the fan/blower, and improving air quality and user comfort in the basement.
Perancangan UI/UX untuk Optimalisasi Booking Online dalam meningkatkan Potensi Wisata Daerah Leuwi Asih Humam Mu'asyir; Tundo; Husain Rahmani; Muhammad Derry Oktaviandi
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 3 (2025): JULI-SEPTEMBER 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i3.3794

Abstract

UI/ UX Design for development of online booking technology and digital tour guides in the Leuwi Asih tourist area aims to increase regional tourism potential through web-based services. This system is designed to make it easy for tourists to make reservations and get information related to tourist destinations efficiently. This research uses a qualitative method by collecting data through direct interviews with local residents and local tourism business owners. The result of this research is a website that functions as a platform to facilitate the management of tourist reservations and provide digital tourist information. Thus, this system is able to support the development of local tourism and improve the tourist experience significantly.
Prediksi Motif Batik dengan Menggunakan Metode Gabor Filter Convolution Neural Network Yudisman Ferdian Bili; Tundo; Nandang Sutisna; Atsilah Daini Putri; Dita Tri Yuliantoro; Laily Nurmayanti
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 3 (2025): JULI-SEPTEMBER 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i3.3798

Abstract

This research aims to develop a batik motif classification system by utilizing Convolutional Neural Network (CNN) and Gabor Filter, in order to increase accuracy in texture feature extraction. The batik dataset used goes through a preprocessing stage, which includes normalization and data augmentation. During training, the model was tested with 10,000 iterations, using the Adam optimizer and the Categorical Cross-Entropy loss function, and evaluated via a confusion matrix. Test results show accuracy reaching 87%, with a precision and recall value of 90% each, and an F1-score of 89%. This method has proven effective for classifying batik motifs and has the potential to be applied in the fields of education, textile industry and cultural preservation.
Transformasi Digital: Pengembangan Sistem Informasi Penjualan Berbasis Web pada UMKM Barokah Jaya Cell di Bekasi dengan Pendekatan UI/UX Farras Abiyyu Handoko; Tundo; Kastum; Fauzan Ibnu Sarky; Rohmat Wijaya
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 3 (2025): JULI-SEPTEMBER 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i3.3820

Abstract

This study designs and develops a web-based sales information system for UMKM Barokah Jaya Cell in Bekasi using a UI/UX approach, applying the Waterfall method. The system development follows a structured process through requirement analysis, design, implementation, testing, and maintenance phases. The goal of this system is to improve efficiency in stock recording, sales transactions, and reporting. Evaluation was conducted through Time-on-Task Testing, Task Success Rate, Error Rate Analysis, and System Usability Scale (SUS). The test results indicate increased productivity, with faster task completion times, a task success rate improvement from 65% to 90%, and a reduction in errors in stock and transaction recording. With an average SUS score of 82, the system is considered intuitive, responsive, and easy to use.
Penerapan Data Mining Menggunakan Algoritma Single Moving Average pada Penjualan Mobil Honda Tundo; Marcia Rizky Hamdala; Andi Saidah; Muhammad Nurdin
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 3 (2025): JULI-SEPTEMBER 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i3.3847

Abstract

Data mining is a branch of artificial intelligence that is used to find patterns and information hidden in data. One of the common algorithms used in data mining is the Single Moving Average (SMA). The SMA algorithm can be used to analyze and predict trend data, such as sales, stocks, production, and so on. In this study, SMA will be used to provide forecasts on Honda car sales and find hidden patterns in them with the aim of finding out the dominant patterns in Honda car sales and preparing for all possible risks that will be obtained due to this forecasting system. The data used in this study is Honda car sales data from official Honda dealers, where data was collected as much as 90 data as a dataset, and 8 data as data to be tested from 2017 to 2023. The results of the study show that the SMA algorithm can be used to analyze Honda car sales data where the right order in this case is order 2 with a value obtained above 90% based on the results of calculations from MAPE and MSE. These results can be used by the Honda company to improve sales strategies and improve product quality in terms of inventory management.
Penerapan Prediksi untuk Klasifikasi Penerima Beasiswa Berprestasi pada SMK Islam Pemalang Berdasarkan Algoritma K-Nearest Neighbor Agung Yuliyanto Nugroho; Tundo; Riolandi Akbar
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 3 (2025): JULI-SEPTEMBER 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i3.3848

Abstract

This research aims to help Pemalang Islamic SMK in identifying outstanding students and predicting potential scholarship recipients, by utilizing the algorithm, K-Nearest Neighbor (K-NN) in determining students who have the potential to receive scholarships. This research used 100 student data involving attributes such as report card grades, academic achievement, parental responsibilities, parental salary, and participation in organizations. Meanwhile, the testing process is carried out by adding 6 data on potential scholarship recipients to be predicted. The data is then processed and normalized before being applied to the K-NN algorithm. The K-NN steps involve determining the K parameter (number of nearest neighbors), calculating the Euclidean distance, sorting the distance results, and selecting the majority category as a prediction for the new object class. The research results show that the application of the K-NN algorithm with K=3 is successful in providing predictions of outstanding students by considering relevant attributes. This process is carried out with the help of JAVA programming to calculate and analyze data. The research conclusion shows that the K-NN algorithm can be used as an effective prediction tool for classification to determine students who excel and are worthy of receiving scholarships. This research contributes to increasing efficiency and accuracy in the selection of outstanding scholarship recipients in the school environment with an accuracy of 83.33%.
Co-Authors Abdus Salam, Abdus Agung Yuliyanto Nugroho Ahmad Satria Rizqi Maula Akbar, Rasyan Akbar, Riolandi Akbar, Yuma Alief Prima Gani Amelia, Ika Anisah Nurul Azhar Arinal, Veri Arvianto, Ramdani Aryanti, Putri Gea Atsilah Daini Putri Aula, Raisah Fajri Aulia Nur Septiani Azhar, Anisah Nurul Betty Yel, Mesra Betty Yel, Mesra Bobby Arvian James Dadang Iskandar Mulyana` Dalail Dalail Dalail, Dalail Devia, Elmi Dewantara, Rizki Dewanti, Elsa Mayorita Dharmawan, Tio Dita Tri Yuliantoro Doni Kurniawan Doni Kurniawan Eldina, Ratih Enny Itje Sela Fadillah Abi Prayogo Fakhrurrofi Fakhrurrofi Fakhrurrofi, Fakhrurrofi Faldo Satria Faridatun Nisa Farras Abiyyu Handoko Fauzan Ibnu Sarky Galih Satria Yacob Gatra, Rahmadhan Hadi Gunawan, Hadi Haryati Heri Mahyuzar Heri Mahyuzar Humam Mu'asyir Husain Rahmani James, Bobby James, Bobby Arvian Januarsyah, Firly Joko Sutopo Junaidi Junaidi Kasiono, Roy Kastum Kastum Kastum Kastum, Kastum Kevin Arya Josaphat Sitompul Khafid Nurohman Khana, Rajes Kiki Setiawan Laily Nurmayanti Laras Sitoayu Lutfi Nugrahaini M. A. Burhanuddin Maharani, Delia Maharani, Shinta Aulia Mahardika, Fajar Mahyuzar, Heri Marcia Rizky Hamdala Marliani, Tiara Marthy, Nicola Mohd Khanapi Abd Ghani Mubarak, Zulfikar Yusya Muhammad Derry Oktaviandi Muhammad Nurdin Muhammad Nurdin Muhammad Raffiudin Muhammad Syazidan Nabilah, Laila Nandang Sutisna Nandang Sutisna Nisa, Faridatun Nizar, Amin Nugraha, Pramudya Nugrahaini, Lutfi Nugroho, Agung Yuliyanto Nugroho, Wisnu Dwi Nuradi, Fahmi Nurohman, Khafid Opi Irawansah, Opi Paidi, Imam Pramudya Nugraha Prayogo, Fadillah Abi Priyanto, Imansyah Purwasih, Intan Putri Wibowo, Salsabila Qolbi, Rofika Rachmat Hidayat Insani Rachmat Hidayat Insani Rachmawati, Dea Noer Raden Dewa Saktia Purnama Raffiudin, Muhammad Raihanah, Syifa Raisah Fajri Aula Ramadhan, Abhirama Huga Ramadhani, Devika Azahra Rasiban Rasiban Ridho Akbar Rindy Julianda Riolandi Akbar Rizki Maulana, Rizki Rohmat Wijaya Romadan, Diva Putra Rona Guines Purnasiwi Saidah, Andi Saifullah, Shoffan Saktia Purnama, Raden Dewa Sarimole, Frencis Matheos Setiawan, Kiki Shindy Apriani Shofwatul ‘Uyun Sodik Sopan Adrianto SOPAN ADRIANTO SRI LESTARI Sugeng Sugiono Sugiono Sugiyono Sugiyono Sugiyono Sugiyono Suropati, Untung Sutisna, Nandang Syani, Muhammad Syifa Raihanah Tampubolon, Parlindungan Tasti, Andi Thalita Tiara Ratu Alifia Tresia, Eflin Tri Wahyudi Tri Wahyudi Tundo Tundo Untung Suropati Untung Suropati Wafiqi, Achmad Ulul Azmi Wagiman, Wagiman Waloeya, Farhan Adriansyah Wijonarko, Panji Wisnu Dwi Nugroho Yacob, Galih Satria Yudisman Ferdian Bili