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All Journal Jurnal Gamma Jurnal Sain Veteriner MEDIA ELEKTRIKA Majalah Ilmiah Teknologi Elektro Paramita: Historical Studies Journal Journal of Consumer Science Catharsis JOIV : International Journal on Informatics Visualization Journal of Consumer Sciences Jurnal Penelitian Pendidikan IPA (JPPIPA) Jurnal SOLMA Khadimul Ummah Journal of Social Dedication MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Journal of Innovation in Business and Economics EDUMATIC: Jurnal Pendidikan Informatika Jurnal Perilaku dan Strategi Bisnis Abdi Masyarakat ASSET: Jurnal Manajemen dan Bisnis Jurnal Teknik Informatika (JUTIF) Jurnal Teknimedia: Teknologi Informasi dan Multimedia Prosiding Konferensi Nasional PKM-CSR Jurnal Begawe Teknologi Informasi SainsTech Innovation Journal Jurnal Karya Pengabdian Teknik Mesin Jurnal Kabar Masyarakat JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah Jurnal INFOTEL Jurnal Pengabdian Kepada Masyarakat (JPKM) Jurnal Pengabdian Masyarakat dan Riset Pendidikan Infact: Jurnal Sains dan Komputer Majalah Ilmiah Teknologi Elektro Jurnal Wicara Desa SainsTech Innovation Journal
Heri Wijayanto
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Journal : JOIV : International Journal on Informatics Visualization

 1 
Tree-based Filtering in Pulse-Line Intersection Method Outputs for An Outlier-tolerant Data Processing Damarjati, Cahya; Trinanda Putra, Karisma; Wijayanto, Heri; Chen, Hsing-Chung; Nugraha, Toha Ardi
JOIV : International Journal on Informatics Visualization Vol 6, No 1 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.1.861

Abstract

Pulse palpation is one of the non-invasive patient observations that identify patient conditions based on the shape of the human pulse. The observations have been practiced by Traditional Chinese Medicine (TCM) practitioners since thousands of years ago. The practitioners measure the patient’s arterial pulses in three points of both patient wrists called chun, guan, and chy, then diagnose based on their knowledge and experience. Pulse-Line Intersection (PLI) method extract features of each pulse from the observed pulse wave sequence. PLI is performed by summing the number of intersections between the artificial line and the pulse wave. The method is proven in differentiating between hesitant with moderate pulse waves. As the method implemented in Clinical Decision Support System (CDSS) related to pulse palpation, some outlier data might emerge and affect the measurement result. Thus, outlier filtering is needed to prevent unnecessary prediction processes by machine learning (ML) models inside CDSS. This study proposed an outlier filtering model using a decision tree algorithm. This concept is designed by analyzing pulse features values and the chance of odd values combination. Then inappropriate values are excepted using several rules. Every pulse feature list that did not pass the filtering rule is categorized as outliers and were not included for further process. The proposed model works more efficiently than ML models dealing with outliers since this procedure is unsupervised learning with a small number of parameters. Overall, the proposed filtering method can be used in pulse measurement applications by eliminating outlier data that might decrease the performance of ML models.
Analyzing Coverage Probability of Reconfigurable Intelligence Surface-aided NOMA Widodo, Agung Mulyo; Wijayanto, Heri; Wijaya, I Gede Pasek Suta; Wisnujati, Andika; Musnansyah, Ahmad
JOIV : International Journal on Informatics Visualization Vol 7, No 3 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.3.2054

Abstract

Along with the explosive growth of wireless communication network users who require large frequency bands and low latency, it is a challenge to create a new wireless communication network beyond 5G. This is because installing a massive 5G network requires a large investment by network providers. For this reason, the authors propose an alternative beyond 5G that has better quality than 5G and a relatively lower investment value than 5G networks. This study aims to analyze the downlink of the cooperative non-orthogonal multiple access (NOMA) network, which is usually used in 5G, combined with the use of a reconfigurable intelligence surface (RIS) antenna with decode and forward relay mechanisms. RIS is processed with a limited number of objects utilizing Rayleigh fading channels. The scenario is created by a user who relays without a direct link for users near the base station and with a direct link for users far from the base station. Under the Nakagami-m fading channel, the authors carefully evaluated the probability of loss for various users as a function of perfect channel statistical information (p-CSI) utilizing simply a single input-output (SISO) system with a finite number of RIS elements. As a key success metric, the efficiency of the proposed RIS-assisted NOMA transmission mechanism is evaluated through numerical data on the outage probability for each user. The modeling outcomes demonstrate that the RIS-aided NOMA network outperforms the traditional NOMA network
A Conversion of Signal to Image Method for Two-Dimension Convolutional Neural Networks Implementation in Power Quality Disturbances Identification Berutu, Sunneng Sandino; Chen, Yeong-Chin; Wijayanto, Heri; Budiati, Haeni
JOIV : International Journal on Informatics Visualization Vol 6, No 4 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.4.1529

Abstract

The power quality is identified and monitored to prevent the worst effects arise on the electrical devices. These effects can be device failure, performance degradation, and replacement of some device parts. The deep convolutional neural networks (DCNNs) method can extract the complexity of image features. This method is adopted for the power quality disruption identification of the model. However, the power quality signal data is a time series. Therefore, this paper proposes an approach for the conversion of a power quality disturbance signal to an image. This research is conducted in several stages for constructing the approach proposed. Firstly, the size of a matrix is determined based on the sampling frequency values and cycle number of the signal. Secondly, a zero-cross algorithm is adopted to specify the number of signal sample points inserted into rows of the matrix. The matrix is then converted into a grayscale image. Furthermore, the resulting images are fed to the two-dimension (2D) CNNs model for the PQDs feature learning process. When the classification model is fit, then the model is tested for power quality data prediction. Finally, the model performance is evaluated by employing the confusion matrix method. The model testing result exhibits that the parameter values such as accuracy, recall, precision, and f1-score achieve at 99.81%, 98.95%, 98.84, and 98.87 %, respectively. In addition, the proposed method's performance is superior to the previous methods. 
Text Classification Using Genetic Programming with Implementation of Map Reduce and Scraping Wedashwara, Wirarama; Irmawati, Budi; Wijayanto, Heri; Arimbawa, I Wayan Agus; Widartha, Vandha Pradwiyasma
JOIV : International Journal on Informatics Visualization Vol 7, No 2 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.2.1813

Abstract

Classification of text documents on online media is a big data problem and requires automation. Text classification accuracy can decrease if there are many ambiguous terms between classes. Hadoop Map Reduce is a parallel processing framework for big data that has been widely used for text processing on big data. The study presented text classification using genetic programming by pre-processing text using Hadoop map-reduce and collecting data using web scraping. Genetic programming is used to perform association rule mining (ARM) before text classification to analyze big data patterns. The data used are articles from science-direct with the three keywords. This study aims to perform text classification with ARM-based data pattern analysis and data collection system through web-scraping, pre-processing using map-reduce, and text classification using genetic programming. Through web scraping, data has been collected by reducing duplicates as much as 17718. Map-reduce has tokenized and stopped-word removal with 36639 terms with 5189 unique terms and 31450 common terms. Evaluation of ARM with different amounts of multi-tree data can produce more and longer rules and better support. The multi-tree also produces more specific rules and better ARM performance than a single tree. Text classification evaluation shows that a single tree produces better accuracy (0.7042) than a decision tree (0.6892), and the lowest is a multi-tree(0.6754). The evaluation also shows that the ARM results are not in line with the classification results, where a multi-tree shows the best result (0.3904) from the decision tree (0.3588), and the lowest is a single tree (0.356).
Co-Authors Adi Santoso Afwani, Royana Agitha, Nadiyasari Agus, I Made Agus Tresna Agustina Dwi Wijayanti Ahmad Fatoni Dwi Putra Ahmad Musnansyah Ahmad Zafrullah Mardiansyah Aiyah Akbar, Andi Hary Alfalah*, Muhammad Fathi Alfalah, Muhammad Fathi Alip Sugianto Alip Sugianto, Alip Aliyah Aliyah Andara, Melki Jonathan Ardi, Komala Khairani Ari Hernawan Arief Sulistiyono Arifianto, Dinar Ashrisnaini, Yudhia Azmi, Muhamad Nizam Baiq Rohiyatun Bimantari, Joselina Rizki Budi Irmawati Budiman Wijaya Cahya Damarjati Chamidah, Siti Chen, Hsing-Chung Chen, Yeong-Chin Deni Saputra Dewi Intan Kurnia Djuwitaningsih, Ekapti Wahjuni Eka Dwi Nurcahya, Eka Dwi Ellysabeth Usmiatiningsih Fadlurrahman, Firgi Febriyansyah, Benny Fitriani Fitriani Futaqi, Faruq Ahmad Garnika, Eneng Gilang, Aditia Hadi Sumarsono Haeni Budiati Hardyansah, Fitrah Huwae, Raphael Bianco I B K Widiartha I Gede Pasek Suta Wijaya I Wayan Agus Arimbawa, I Wayan Agus Ida Bagus K Widiartha Irma Putri Rahayu Jatmika, Andy Hidayat Jatmika, Andy Hidayat Khairani Ardi, Komala Kurrotaa'yun, Baiq Dwi Zulianti Kuska, Dila Ayu Ramanda Latifah, Nur Izza Ma'we, Hannatul Maharani, Sisilia Nabilla Mahendra Putra Raharja Mardiansyah, Ahmad Zafrullah Moh. Ali Wisudawan Prakara Moh. Ali Wisudawan Prakarsa S Muh. Ibnan Syarif, Muh. Ibnan Muhammad Ari Rifqi Munaji, Munaji Murpratiwi, Santi Ika Nabilla Maharani, Sisilia Naning Kristiyana, Naning Noor Alamsyah Octariana, Ghina Briliana Fatin Praseba, Diki Purnomo, Rochmat Aldy Putra, I Gede Darmawan Adi Pratama Rachmadia, Rizki Rahaman, Mosiur Rahman, Pradita Dwi Ramadhani, Rizky Insania Rayani, Dewi Reyhan Adiba, Rahmat Rhesma Intan Vidyastari Rian Maulidani, Ahmad Riyanto, Didik Rizky, Dimas Maulana Rohmayani, Laeli Rosika, Herliana Saputra, Asep Rokhyadi Permana Saputri, Meilan Yulia Satria Utama, Satria Setyo Budhi Sideman, Ida SRI ANGGRAINI Sri Hartono, Sri Sritrisniawati, Shella Elly Sunarto Sunarto Sunneng Sandino Berutu Suparjo Tajul Ma’arif, Muh Toha Ardi Nugraha Trinanda Putra, Karisma Tulus Haryono, Tulus Utami, Wiwid Vandha Pradwiyasma Widartha Wedashwara Wirawan, I Gede Putu Wirarama Wedashwara, Wirarama Wesdawara, Wirarama Widanta, I Putu Widia Lingga, Elza Widodo, Agung Mulyo Widowati Siswomihardjo Widya Oktary Setiawardhani Widyani, Aprilian Widyani, Aprillian Wiraguna, Diky Wirawan, I Gde Putu Wirarama Wedashwara Wisnujati, Andika Witarsana, I Nengah Dwi Putra Wulandari, Fidyah Ajeng Zahra, Dinda Zahrani, Nurul Qalbi Zubaidi, Ariyan