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Journal : JOIV : International Journal on Informatics Visualization

Application of IoT-based Intelligent Control Devices Empowered with Fuzzy Inference System in the Garment Industry Rizki, Agung Mustika; Ashari, Faisal; Yuliastuti, Gusti Eka; Haromainy, Muhammad Muharrom Al; Aditiawan, Firza Prima; Amnur, Hidra
JOIV : International Journal on Informatics Visualization Vol 9, No 5 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.5.3344

Abstract

The garment industry in Indonesia has experienced significant development in recent years. A critical aspect of this development is the increasing role of Micro, Small, and Medium Enterprises (MSMEs). Swari Garment Industries (SGI) is an example of an MSME that focuses on the garment sector. In practice, various problems and negligence can affect the course of the production process. One potential issue is using the machine inappropriately or excessively, which can lead to a short electrical circuit. Short electrical circuits are one of the problems that must be faced because they can cause various severe impacts, including equipment damage and even fire. Based on this risk analysis, a possible solution to be applied to SGI, one of the MSMEs in the garment sector, is the implementation of an intelligent control device. The implementation of intelligent control tools based on the Internet of Things (IoT) can enhance the efficiency of the production process and mitigate significant risks to workers and the environment. The Fuzzy Inference System, in which the equity, temperature, and humidity are the input values of the Intelligent Control Device. A hardware device for temperature and humidity control, accessible through an Android phone application, was implemented in SGI. Experiments have verified that we can achieve excellent results. The average percentage of temperature measurement error was 0.2% and for humidity, 0.26%. The average percentage of measurement error from the comparison between the system and MATLAB is 0.49%.
Implementing K-Nearest Neighbors (k-NN) Algorithm and Backward Elimination on Cardiotocography Datasets Kurniawan, Muchamad; Yuliastuti, Gusti Eka; Rachman, Andy; Budi, Adib Pakar; Zaqiyah, Hafida Nur
JOIV : International Journal on Informatics Visualization Vol 8, No 3 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.3.1996

Abstract

Having a healthy baby is a dream for mothers. Unfortunately, high maternal and fetal mortality has become a vital problem that requires early risk detection for pregnant women. A cardiotocograph examination is necessary to maintain maternal and fetal health. One method that can solve this problem is classification. This research analyzes the optimal use of k values and distance measurements in the k-NN method. This research expects to become the primary reference for other studies examining the same dataset or developing k-NN. A selection feature is needed to optimize the classification method, particularly for improving accuracy results. This study used the cardiotocography dataset from cardiotocograph examinations related to fetal conditions. The cardiotocography dataset consisted of 2,126 records with 22 features and variables. It also had three classification classes, normal, suspect, and pathological, from the Universal Child Immunization Machine Learning Repository website. It employed the K-Nearest Neighbor (k-NN) method and the backward elimination feature with ordinary least squares regression. The test in this research applied the scenarios of three distance calculations, i.e., Euclidean distance, Manhattan distance, and Minkowski distance, as well as four variations of k values. Evaluation of each scenario indicated the accuracy of the confusion matrix and execution time. This study compared K-Nearest Neighbor (k-NN) and Backward Elimination methods with K-nearest neighbor (k-NN) without selection features. The best accuracy of the Backward Elimination and K-Nearest Neighbor (K-NN) methods was 91%, as was the K-Nearest Neighbor (k-NN) method without selection features. Both had similar k values (k = 3) and Manhattan distance. The backward elimination method reduced the number of features from 22 to 14. Meanwhile, the execution times of the Backward Elimination and K-Nearest Neighbor (k-NN) methods got better results as each distance averaged 26.54, 19.23, and 68.09 seconds. K-Nearest Neighbor (k-NN) execution times without selection features were 26.83, 19.39, and 68.84, respectively. In conclusion, backward elimination did not increase accuracy because it yielded the same accuracy. However, backward elimination and K-nearest Neighbor (k-NN) produced faster results, with differences of 29%, 16%, and 75%, respectively.
Co-Authors Achmad Basyari Mushthofa Achmad Febrianto Adjie Prasetyo Nugroho Agung Mustika Rizki Agung Mustika Rizki Agung Mustika Rizki Agung Mustika Rizki, Agung Mustika Alphinda Rahma Safira Nisa' Andi M. A. K. Parewe Andy Rachman Anwar Sodik, Anwar Ardiansah, Ferdi Ariansyah, Fernando Yoga ASHARI, FAISAL Assyarif, Rafli Abi Azizi, Ilham Habib Bamahri, Fakhirah Budi, Adib Pakar Citra Nurina Prabiantissa Danang Haryo Sulaksono Danang Haryo Sulaksono, Danang Haryo Dhian Satria Yudha Kartika Dhiyas Rakha Allam Allam dwi, Igusti Ngurah Eka Prakarsa Mandyartha Faisal Muttaqin Fery Soewarianto Firmansyah, Mohammad Hafitz Firmansyah, Muhammad Farid Firza Prima Aditiawan Habibullah, Maulana Ahmad Haryono Haryono Hendro Nugroho Hendro Nugroho, Hendro Hidra Amnur I Kadek Agus Ariyasa Ishardita Pambudi Tama Ismaya, Agam Sulaiman Jaya, Agam Kaisul Fuqara Dewanda Khoiri, Muhammad Kusuma, Ris Fani M. Fajar J. Kharisma Maulana, Fadhil Dias Maulana, Hendra Moneter, Mochamad Rizky Muchamad Kurniawan, Muchamad Muhammad Muharrom Al Haromainy Muhammad Rohman Muhammad Zazin Nanang Fakhrur Rozi Ngaisah, Siti Nurlaili, Afina Lina Oktavyani, Adela Rizky Pamuji, Madadina Adilah Pradana, Andrean Firman Pratikto, Dimas Putra, Erico Maulana Putri, Chatarina Natassya Putri, Rahmi Rizkiana Qornain, Wafi Dzul Radissa Dzaky Issafira Rahmadianto, Ilyasa Nanda Rahmi Rizkiana Putri S Nurmuslimah, S Septiyawan Rosetya Wardhana Setiawan, Muhammad Charis Siti Agustini Siti Agustini, Siti Soedarto, Teguh Suthelie, Ryvana Teguh Soedarto Wardhana, Septiyawan Rosetya Wayan Firdaus Mahmudy Weny Mistarika Rahmawati Wicaksono, Redi Nurdin Yunanda, Sita Fara Zaqiyah, Hafida Nur