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Journal : Jurnal INFOTEL

Optimization of software defects prediction in imbalanced class using a combination of resampling methods with support vector machine and logistic regression Windyaning Ustyannie; Emy Setyaningsih; Catur Iswahyudi
JURNAL INFOTEL Vol 13 No 4 (2021): November 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v13i4.726

Abstract

The main problem in producing high accuracy software defect prediction is if the data set has an imbalance class and dichotomous characteristics. The imbalanced class problem can be solved using a data level approach, such as resampling methods. While the problem of software defects predicting if the data set has dichotomous characteristics can be approached using the classification method. This study aimed to analyze the performance of the proposed software defect prediction method to identify the best combination of resampling methods with the appropriate classification method to provide the highest accuracy. The combination of the proposed methods first is the resampling process using oversampling, under-sampling, or hybrid methods. The second process uses the classification method, namely the Support Vector Machine (SVM) algorithm and the Logistic Regression (LR) algorithm. The proposed, tested model uses five NASA MDP data sets with the same number attributes of 37. Based on the t-test, the < = 0.0344 < 0.05 and the > = 3.1524 > 2.7765 which indicates that the combination of the proposed methods is suitable for classifying imbalanced class. The performance of the classification algorithm has also improved with the use of the resampling process. The average increase in AUC values using the resampling in the SVM algorithm is 17.19%, and the LR algorithm is at 7.26% compared to without the resampling process. Combining the three resampling methods with the SVM algorithm and the LR algorithm shows that the best combining method is the oversampling method with the SVM algorithm to software defects prediction in imbalanced class with an average accuracy value of 84.02% and AUC 91.65%.
Performance improvement of the shredder machines using IoT-based overheating controller feature Emy Setyaningsih; Satriawan Dini Hariyanto; Dewi Wahyuningtyas; Samuel Kristiana
JURNAL INFOTEL Vol 14 No 4 (2022): November 2022
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v14i4.812

Abstract

Plastic shredding plays an essential role in the plastic waste recycling process. Plastic waste can be enumerated manually using a knife and scissors or a crushing machine. The use of a shredder machine to chop plastic waste, especially those whose primary drive is an electric motor, often experience problems. The main obstacle is the need for high power consumption (more than 1 HP) and the reliability of the drive elements against overheating. Overheating can damage the electrical circuit components that connect the power supply to electric motors, especially AC electric motors, causing a lot of loss in terms of performance and user safety. Internet of Things (IoT) technology is widely used to minimize energy resources by automating various systems. This study proposed the design of a shredder machine with a control system using IoT technology integrated with a shredder and conveyor machine designed using the Quantity Functional Diagram (QFD) method. The advantages of the shredder machine presented in this study are that it can operate at home using electric power, is more flexible, and minimizes overheating with an IoT-based overheating controller. This research succeeded in keeping the temperature of the electric motor of the shredder machine stable at a temperature of 40℃-55℃. The average delay of the IoT module to control on and off the shredder machine design system in this study is 219 ms and 200 ms, which are in the good category according to the Telecommunications and Internet Protocol Harmonization Over Network (TIPHON) standard.
Co-Authors Achmad Fauzi Agus Harjoko Agus Subekti Al Faruq, Tsabit Faiz Alan Primayoga Ambarwati, Anisa Fitriana Amir Hamzah Amir Hamzah Analis, Dian Anggraini Kusumaningrum, Anggraini Ani Purwanti Anton Setiawan Honggowibowo Argaditia Mawadati Ariyana, Renna Yanwastika Arwin Datumaya Wahyudi Sumari Astika AyuningTyas, Astika Benge, Defaullo Benge, Defaullo Andrean Ronaldino Catur Iswahyudi Catur Iswahyudi Dedu, Maria Oktafiana Dewi Wahyuningtyas Dhamayanti, Katherina Irene Dian Analis Dian Analis Dwi Setyowatie Dzakiya, Nurul Edhy Sutanta (Jurusan Teknik Informatika IST AKPRIND Yogyakarta) Edy Supriyanto Effendi, Tirta Meidival Eska Almuntaha Faradila, Niza Faradilla, Niza Fiorina Yunavania, Fiorina Gatot Santoso Harmastuti - Harmastuti Harmastuti Harmastuti, Harmastuti Hasibuan, Albar Adetary Hormat, Petronius Istiari, Satiti Jihanto, M. Vinda Nur Joice Lumban Tobing Joko Winarno Katherina Irene Dhamayanti Khalil sidik Listiyanto, Ziko M. Andang Novianta M. Vinda Nur Jihanto Manggala, Habib Eky Maulana Wahid, Rindo Mohamad Anas Muhammad Andang Novianta Muhammad Andang Novianta Muhammad Andang Novianta Muhammad Andang Supriatna, Muhammad Andang Muhammad, Nawafil Murni Yuniwati, Murni Naniek Widyastuti Naniek Widyastuti Nidia Lestari Novianta, M. Andang Nurcahyo, Raden Wisnu Nuryatno, Edi Triono Perdiansa, Aldi Prabowo, Fajar Yulianto Prasetya, Dwi Sabda Budi Primayoga, Alan Pujiastuti, Asih Purnawan - Purnawan Purnawan Purnomo, Sekar Chairunnisa Ratna Wardani Said - Said Said, Said Samuel Kristiana Saputra, Hendrik Saputro Febri Satriawan Dini Hariyanto Sekar Chairunnisa Purnomo Seran, Vianney Laura Setyawan, Imanuel Calvin Shidiq F, Muhammad Simbolon, Yohana Christine Simbolon, Yohana Cristine Sinaga, Sultoni Wijaya Sisilia Endah Lestari, Sisilia Endah Slamet Hani, Slamet Suparni Setyowati Rahayu Surya, Godeliva Sang Suwanto Raharjo Toto Rusianto Utubira, Berliana Isel Windyaning Ustyannie Wintolo, Hero Yoga, Alan Prima Yuli Asriningtias Yuli Purwanto Yuli Purwanto Yuli Purwanto, Yuli Zahra, Nafisa Ananda