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All Journal Jurnal Pekommas Telematika : Jurnal Informatika dan Teknologi Informasi Jurnal Teknologi dan Sistem Komputer Compiler Journal of Dedicators Community Jurnal Penelitian Pers dan Komunikasi Pembangunan JISKa (Jurnal Informatika Sunan Kalijaga) Jurnal Berdaya Mandiri Indonesian Journal of Data and Science Jurnal Abdimas Kartika Wijayakusuma PELS (Procedia of Engineering and Life Science) Indonesian Journal on Data Science Teknomatika: Jurnal Informatika dan Komputer International Journal of Artificial Intelligence in Medical Issues
Aris Wahyu Murdiyanto
Universitas Jenderal Achmad Yani Yogyakarta
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Desain User Interface Dan User Experience Prototype Mobile Learning Menggunakan Metode Design Thinking Metode Design Thinking Angkotasan, Muhamad Arabi Rizki; Murdiyanto, Aris Wahyu; Himawan, Arif; Syahruddin, Fajar
Jurnal Teknomatika Vol 16 No 2 (2023): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v16i2.1254

Abstract

Abstract - Do Up uses the website as online learning. users complain about the accessibility of the website with some minimal features and an unattractive UI when accessed via a smartphone will make the UX limited and will limit user interaction in using Do Up. Designing UI and UX prototypes of mobile learning at startup Do Up, using the design thinking method to solve problems and find the right solution according to the user's wishes. The author applies design thinking in this research. The author makes an illustration in the form of a Do Up mobile learning UI design that is in accordance with user needs and provides the design to Do Up stakeholders. In SEQ there are 4 scales given by users, namely 4.5, 6 and 7 scale. Most users give a 7 scale on the UI/UX design of the Do Up mobile learning prototype. On SUS which shows that the final score is 87 It means that the prototype has been well received by the users. The author has applied design thinking which consists of empathize, define, ideate, prototype and test stages in this study.
Assessing Bagging-meta Estimator in Imbalanced CT Kidney Disease Classification: A Focus on Sobel and Hu Moment Techniques Setiawan, Rudi; Kadir Parewe, Andi Maulidinnawati Abdul; Latipah, Asslia Johar; Puji Astuti, Nur Rochmah Dyah; Murdiyanto, Aris Wahyu; Putra, Fajri Profesio
International Journal of Artificial Intelligence in Medical Issues Vol. 1 No. 2 (2023): International Journal of Artificial Intelligence in Medical Issues
Publisher : Yocto Brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijaimi.v1i2.100

Abstract

This study investigates the efficacy of the Bagging-meta estimator in classifying CT kidney diseases, focusing on an imbalanced dataset processed through Sobel segmentation and Hu moment feature extraction. The research utilized a quantitative approach, applying the Bagging-meta estimator to a dataset comprising CT images classified into four categories: Normal, Cyst, Tumor, and Stone. These images were preprocessed using Sobel segmentation to highlight critical structures and Hu moment feature extraction for robust classification features. The study employed a 5-fold cross-validation method to evaluate the model's performance, assessing metrics such as accuracy, precision, recall, and F1-Score. The results indicated a significant variation in the model's performance across different folds, with accuracy ranging from 49.86% to 66.17%, precision between 51.86% and 65.93%, recall from 57.95% to 64.44%, and F1-Scores spanning 48.26% to 60.74%. These findings suggest that while the Bagging-meta estimator can achieve reasonable accuracy in classifying kidney diseases from CT images, its performance is affected by the imbalanced nature of the dataset. This study contributes to the understanding of the challenges and potential of machine learning in medical imaging, particularly in the context of imbalanced datasets. It highlights the need for specialized approaches to handle such datasets and underscores the importance of preprocessing techniques in enhancing model performance. Future research directions include exploring methods to address data imbalance, investigating alternative feature extraction techniques, and testing the model on diverse datasets to enhance its generalizability and reliability in clinical settings. This research offers valuable insights into the development of automated diagnostic tools in medical imaging and advances the field of computer-aided diagnosis in nephrology.
Instagram Hashtag Trend Monitoring Using Web Scraping Priadana, Adri; Murdiyanto, Aris Wahyu
Jurnal Pekommas Vol 5 No 1 (2020): April 2020
Publisher : Sekolah Tinggi Multi Media “MMTC” Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30818/jpkm.2020.2050103

Abstract

In recent years, Instagram has become one of the fastest growing social media platforms. Searching images on Instagram can be done by using a particular keyword or often known as the hashtag. The hashtag is one of the parameters that can use to find out the topics that are being talked about on social media. There are many advantages for knowing a hot topic on social media to support decision making. This study aims to monitor trends of hashtags on the Instagram platform using web scraping techniques. This research has succeeded in extracting and analyzing post data on Instagram to provide trend information from a #MerryChrismas hashtag. The results of this study are the visible trend in the #MerryChrismas hashtag experienced an increase in the last two days, namely on 24 and 25 December 2019. In addition, this research also succeeded in displaying posts with the most number of likes and comments from a hashtag at a certain time period.
Penerapan Teknologi Pemasaran Digital Bagi Masyarakat UMKM Dusun Brajan di Gedung Tani Banjararum Murdiyanto, Aris Wahyu; Rahayu, Suparni Setyowati; Sutanta, Edhy; Hanafi, Ahmad; Rosid, Ibnu Abdul; Arbintarso, Ellyawan Setyo; -, Purnawan
Journal of Dedicators Community Vol 8, No 3 (2024)
Publisher : Universitas Islam Nahdlatul Ulama Jepara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34001/jdc.v8i3.5733

Abstract

Community service activities carried out in Banjararum Village, Kapanewon Kalibawang, Kulon Progo Regency, DIY, on November 4 2023 aim to provide solutions to the problems faced by three Non-Governmental Organizations (NGOs), namely the Punthuk Ngepoh Tourism Awareness Group (Pokdarwis). , Srikandi Farming Women's Group (KWT), and Gapoktan Ngudi Makmur. The problems faced include the absence of an optimal electricity network, the absence of infographic information/spatial plans for the Punthuk Ngepoh Tourist Attraction, the absence of a digital marketing platform, the absence of cassava cutting tools, lack of water in agricultural areas during the dry season, manure from livestock which causes disturbances in the form of unpleasant odors and there is no management of livestock manure. The solutions include repair and development of solar panels as well as the process of exploring springs in Punthuk Ngepoh to be used as a tourism support facility, the application of TTG in the form of a cassava cutting tool, and the application of TTG in the form of gasification in the coconut oil extraction process. Community service activities in the Banjararum District have provided solutions to the problems faced by the three NGOs. It is hoped that the solutions offered can boost the community's economy through programs created by the NGO.
ANALISIS SENTIMEN DI MEDIA SOSIAL TWITTER DENGAN STUDI KASUS KARTU PRAKERJA Iqbal Hadi Subekti; Muhammad Habibi; Aris Wahyudi Murdiyanto; Alfun Roehatul Jannah
Jurnal Teknomatika Vol 14 No 2 (2021): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v14i2.1101

Abstract

Kartu Prakerja is one of the government's flagship programs in providing training to the workforce. In its implementation there is a lot of information scattered, especially on social media Twitter both in the pros and cons of Kartu Prakerja program. Based on information in the form of tweets that have not been analyzed in depth, it is necessary to analyze sentiment on the Kartu Prakerja in order to obtain appropriate information based on the opinions of netizen s on Twitter. This study discusses sentiment analysis of tweet data with the keyword “Kartu Prakerja” which uses data as many as 6658 tweet data taken in the period May 27 - August 5, 2021. This research uses the Naive Bayes Classification method which has several stages, namely data retrieval, data preprocessing, manual labeling, data training and testing. The solution offered in this study is to create an analysis model that can be used to perform sentiment analysis about Kartu Prakerja on Twitter. Based on the results of this study obtained that the calculation of accuracy obtained a value of 86% for training data and 87% for data testing. This study concluded that the Kartu Prakerja has a positive sentiment by Twitter netizens based on the results of Classification that discusses many positive sentiments such as the benefits, effectiveness and addition of the Kartu Prakerja budget.
Desain User Interface Dan User Experience Prototype Mobile Learning Menggunakan Metode Design Thinking Metode Design Thinking Angkotasan, Muhamad Arabi Rizki; Murdiyanto, Aris Wahyu; Himawan, Arif; Syahruddin, Fajar
Jurnal Teknomatika Vol 16 No 2 (2023): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v16i2.1254

Abstract

Abstract - Do Up uses the website as online learning. users complain about the accessibility of the website with some minimal features and an unattractive UI when accessed via a smartphone will make the UX limited and will limit user interaction in using Do Up. Designing UI and UX prototypes of mobile learning at startup Do Up, using the design thinking method to solve problems and find the right solution according to the user's wishes. The author applies design thinking in this research. The author makes an illustration in the form of a Do Up mobile learning UI design that is in accordance with user needs and provides the design to Do Up stakeholders. In SEQ there are 4 scales given by users, namely 4.5, 6 and 7 scale. Most users give a 7 scale on the UI/UX design of the Do Up mobile learning prototype. On SUS which shows that the final score is 87 It means that the prototype has been well received by the users. The author has applied design thinking which consists of empathize, define, ideate, prototype and test stages in this study.
Performance Comparison of CNN and ResNet50 for Skin Cancer Classification Using U-Net Segmented Images Aris Wahyu Murdiyanto; Zulfikar, Dian Hafidh; Waluyo Poetro, Bagus Satrio; Siregar, Alda Cendekia
Indonesian Journal of Data and Science Vol. 5 No. 3 (2024): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v5i3.200

Abstract

Skin cancer is a significant global health issue, with melanoma, basal cell carcinoma, and actinic keratosis being the most common types. Early and accurate detection is critical to improve survival rates and treatment outcomes. This study evaluates the performance of Convolutional Neural Networks (CNN) and ResNet50 in classifying segmented images of skin lesions. The dataset, sourced from Kaggle, was pre-processed using U-Net for lesion segmentation to enhance the quality of input data. Both models were trained and evaluated using accuracy, precision, recall, and F1-score metrics. The CNN model demonstrated a balanced performance across classes, with a weighted F1-score of 47%, but suffered from overfitting, as indicated by the divergence between training and validation losses. ResNet50 achieved better recall for basal cell carcinoma (100%) but failed to classify actinic keratosis and melanoma, resulting in a macro F1-score of 23%. The findings reveal that U-Net segmentation improved classification focus but was insufficient to address dataset imbalance and model-specific limitations. This study highlights the challenges of skin cancer classification using deep learning and underscores the importance of addressing data imbalance and overfitting. Future research should explore advanced techniques, such as ensemble methods, data augmentation, and transfer learning, to improve the generalization and clinical applicability of these models. The proposed framework serves as a foundation for further investigation into automated skin cancer detection systems.
Analisis Sentimen Transfer Pemain Klub La Liga Spanyol Pada Bursa Transfer Musim Dingin Eropa Di Twitter Ahmad Adita Shiddiq; Aris Wahyu Murdiyanto; Arif Himawan
INDONESIAN JOURNAL ON DATA SCIENCE Vol. 1 No. 1 (2023): Indonesian Journal on Data Science
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/ijds.v1i1.859

Abstract

Dari beberapa kompetisi Sepak Bola yang ada, Liga Champions UEFA yang paling digemari oleh masyarakat. Pada tahun 2022 bursa transfer pemain Eropa dibuka, bursa transfer yang dilakukan merupakan cara jangka pendek untuk memperbaiki tim dalam mengejar prestasi sepak bola Dengan media sosial sebagai wadah komunitas, para penggemar sepak bola dapat juga menyalurkan opini, informasi dan berita tentang klub kesayangan kepada masyarakat. Opini masyarakat terhadap transfer pemain Liga Spanyol memiliki peranan penting. Dengan dilakukannya analisis sentimen terhadap opini, dapat dijadikan suatu pola prediksi penilaian masyarakat terhadap transfer pemain serta dapat memberikan saran kepada tim sepak bola terkait bursa transfer pemain pada periode musim selanjutnya. Membuat analisis sentiment penggemar sepak bola terhadap transfer pemain Liga Spanyol apakah bersifat positif dan negatif. Metode Naïve Bayes Classifer (NBC) dalam penelitian ini dipilih dikarenakan pada algoritma NBC dapat melakukan proses pengolahan data diskrit dan data kuantitatif dengan menggunakan sampel yang relative sedikit dan juga perhitungan pada algoritma NBC lebih cepat. Pengambilan data berupa topik mengena keyword “Transfer La Liga”, “Transfer Real Madrid”, “Transfer Barcelona”, “Transfer Liga Spanyol” dan “Transfer Copa Del Ray”. Data tweet di ambil dari periode 1 Januari 2020 sampai dengan 31 Mei 2022, dengan jumlah data total 11.282. Pada penelitian telah berhasil mendapatkan akurasi dengan nilai 81,67 % pada data training dan 85 % untuk data testing. Pada penelitian ini berhasil membuat model analisis sentimen berupa file.pickle yang dimana untuk melakukan klasifikasi dan prediksi pada data tweet untuk mendapatkan sebuah hasil sentimen positif dan negative. Penelitian ini telah berhasil mendapatkan akurasi dengan nilai 81,67 % pada data training dan 85 % untuk data testing.Hasil analisis sentimen akhir dalam klasifikasi penelitian ini bernilai “Sentimen Negatif”
Analisis Sentimen Di Media Sosial Twitter Dengan Studi Kasus Vaksinasi Covid-19 Nufia Alfi Rohyana; Aris Wahyu Murdiyanto; Kharisma
INDONESIAN JOURNAL ON DATA SCIENCE Vol. 1 No. 1 (2023): Indonesian Journal on Data Science
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/ijds.v1i1.861

Abstract

With the COVID-19 pandemic, the World Health Organization or WHO conducted research and research trials on the COVID-19 vaccine. The Indonesian government has made several policies, one of which is the "Mass Vaccination Program". However, the COVID-19 vaccination program in the field received mixed responses in the community, there were those who supported the vaccine program and some who rejected the vaccine program. In this study, researchers conducted research on sentiment analysis on the opinion of vaccination programs against anti-vaccine community groups based on Twitter social media data using the Naïve Bayes Classifier algorithm to provide information on opinion assessments that lead to positive and negative sentiments. Objective: The purpose of this study is to find out the public perception of AntiVaccine against the COVID-19 Vaccination Program in Indonesia. This study uses the Naïve Bayes Classification. The use of the Naïve Bayes Classifier (NBC). This research uses tweets obtained from Twitter with the keywords/hashtags “Anti Covid-19 Vaccines” or by collecting data based on accounts related to news about vaccination programs such as @ The Ministry of Health of the Republic of Indonesia. Data collection was carried out in the period August 2021-December 2021, with a total of 889 data. This study has succeeded in obtaining an accuracy of 72 % for testing. The result of the final sentiment analysis in the classification of the Anti-Vaccine group in this study is "Negative Sentimen".
PENERAPAN TEKNOLOGI PEMBANGKIT LISTRIK TENAGA SURYA SEBAGAI SUMBER LISTRIK CADANGAN DI PONDOK PESANTREN HIDAYATULLAH YOGYAKARTA Marausna, Gaguk; Wahyu Murdiyanto, Aris; Rizki Putra, Ikbal; Eko Prasetiyo, Erwan; Yulianto Prabowo, Fajar
Jurnal Berdaya Mandiri Vol. 6 No. 3 (2024): JURNAL BERDAYA MANDIRI (JBM)
Publisher : Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/jbm.v6i3.7119

Abstract

The application of solar power plant technology as a backup power source at Hidayatullah Islamic Boarding School, Yogyakarta, aims to address the challenges caused by disrupted electricity supply. This Islamic boarding school has a strategic location due to its close access to the city center of Yogyakarta. The school relies on electricity for its educational and worship activities. A study was conducted to assess the potential of solar energy, geographical conditions, and the readiness of Hidayatullah Islamic Boarding School to adopt renewable energy technology. After the assessment, structured implementation activities, such as awareness socialization, training, and direct assistance, were carried out to ensure the management of the solar power system by the school administration. The results of the Community Service program showed that a solar power system had successfully been implemented to address disruptions during power outages, thereby improving worship and educational activities. This program encourages partner involvement and environmental awareness among the school management and students. Recommendations for ensuring the program’s sustainability include training, routine performance evaluations, and potential partnerships with government and private organizations to promote the use of renewable energy. This successful program is expected to serve as a model for other educational institutions seeking to implement renewable energy technology. Keyword: energy, solar, power plant, backup, community service.
Co-Authors -, Purnawan Adri Priadana Adri Priadana Agung Purwanto Soedarbe Agung Satria Panca Ahmad Adita Shiddiq Ahmad Adita Shiddiq Ahmad Hanafi Ahmad Hanafi Alfun Roehatul Jannah Alfun Roehatul Jannah Almayanti Susillia Ningrum Alwiah, Izmy Angkotasan, Muhamad Arabi Rizki Arbintarso, Ellyawan Setyo Arif Himawan Arif Himawan Arif Himawan, Arif Aulia Puji Rahayu Bara Falah Adikaputra Catur Iswahyudi David Sulistiyantoro David Sulistiyantoro, David Sulistiyantoro Dewi, Tika Sari Dian Hafidh Zulfikar Dimas Pratama Jati Edhy Sutanta (Jurusan Teknik Informatika IST AKPRIND Yogyakarta) Fitriatul Hasanah Gerlan Haha Nusa Gilang Argya Dyaksa Haha Nusa, Gerlan Hamada Zein Hariyanto, Satriawan Dini Ida Ristiana Iqbal Hadi Subekti Iqbal Hadi Subekti Kadir Parewe, Andi Maulidinnawati Abdul Kharisma Kharisma Kusumaningtyas, Kartikadyota Latipah, Asslia Johar M. Abu Amar Al Badawi Marausna, Gaguk Muhammad Habibi Muhammad Habibi Muhammad Luqman Bukhori Muhammad Rifqi Ma'arif Mukasi Wahyu Kurniawati Nafisa Alfi Sa'diya Naswin, Ahmad Nufia Alfi Rohyana Nufia Alfi Rohyana Nurcahyo, Raden Wisnu Nurul Fatimah Poetro, Bagus Satrio Waluyo Prasetiyo, Erwan Eko Puji Astuti, Nur Rochmah Dyah Purbobinuko, Zakharias Kurnia Purnawan Purnawan Putra, Fajri Profesio Putra, Ikbal Rizki Raden Wisnu Nurcahyo Risky Setyadi Putra Rosid, Ibnu Abdul Rudi Setiawan Samuel Kristiyana Septiyati Purwandari Siregar, Alda Cendekia Sisilia Endah Lestari, Sisilia Endah Sugeng Santoso Sumiyatun Suparni Setyowati Rahayu Surya Rizki Syahruddin, Fajar Tarigan, Thomas Edyson Umar Zaky Yulianto Prabowo, Fajar Zennul Mubarrok, Zennul Mubarrok