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OPTIMIZATION OF SOFTWARE DEFECT PREDICTION USING CNN AND ADABOOST: ANALYSIS AND EVALUATION Basit, Muhammad Abdul; Setyanto, Arief; Hidayat, Tonny
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 3 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i3.6405

Abstract

This study focuses on enhancing software defect prediction (SDP) by integrating Convolutional Neural Networks (CNN) with the AdaBoost algorithm. The PROMISE dataset was employed in this research, and data balancing was achieved using the SMOTE Tomek technique. With the help of AdaBoost, we were able to increase the prediction accuracy after building a complex CNN model to extract features from the da-taset. The AdaBoost model's hyperparameters were fine-tuned using GridSearch to find the best values for enhanced model performance. For the studies, we used StandardScaler to normalize the data after splitting it into training and testing groups with an 80:20 ratio. The ex-perimental results show that compared to the baseline method, SDP's accuracy is significantly improved when CNN, AdaBoost, and GridSearch hyperparameter tweaking are used together. Accuracy, pre-cision, recall, F1 score, MCC, and AUC were some of the measures used to assess the model's performance.
Rekayasa kebutuhan untuk pengembangan sistem perangkat lunak pelayanan kesehatan: Literatur Reviu Sistematis Setiawan, Anjar; Auliyah, Ulul Azmiati; Noviyanto, Noviyanto; Basit, Muhammad Abdul; Sidiq, Muhammad
JNANALOKA Vol. 05 No. 01 Maret Tahun 2024
Publisher : Lentera Dua Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36802/jnanaloka.2024.v5-no01-1-11

Abstract

Penelitian ini dilakukan untuk memberikan refleksi sistematis terhadap pengembangan sistem perangkat lunak untuk pelayanan kesehatan dengan fokus pada kebutuhan rekayasa. Hal ini dilakukan karena sistem perangkat lunak untuk pelayanan kesehatan merupakan sektor yang sangat kompleks dan dinamis. Proses ini melibatkan elisitasi, analisis, spesifikasi, validasi, dan manajemen persyaratan. Penelitian ini bertujuan untuk memberikan wawasan sistematis mengenai fase, teknik, dan alat yang digunakan dalam pengembangan persyaratan sistem perangkat lunak untuk layanan kesehatan, serta untuk mendiseminasikan kualitas penelitian yang ada. Beberapa teknik dapat digunakan dalam rekayasa persyaratan untuk mengembangkan sistem perangkat lunak untuk layanan kesehatan, seperti survei, wawancara, kasus penggunaan UML, dan prototipe. Perkembangan sistem kebutuhan perangkat lunak pada pelayanan kesehatan masih memberikan peluang yang sangat besar untuk pengembangan lebih lanjut khususnya sistem pelayanan kesehatan pada topik pencatatan data kesehatan secara digital yang menjadi isu terkini dan sangat dibutuhkan oleh masyarakat.
A Real-Time Hooke's Law Experiment using IoT Mobile Application Sudarmanto, Agus; Poernomo, Joko Budi; Suseno, Jatmiko Endro; Putranto, Ari Bawono; Basit, Muhammad Abdul
Journal of Physics and Its Applications Vol 8, No 1 (2026): February 2026
Publisher : Diponegoro University Semarang Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Hooke's Law is one of the topics in physics that can be simplified for better understanding through practical methods. This research aims to design a Real-Time remote Hooke's Law experiment in laboratory with Blynk as IoT Mobile Application, allowing students to experiment more flexibly in terms of time and location. The research methodology is based on Research and Development (R&D), including hardware design, software design, testing and data collection, data analysis, and report writing. This study resulted in the development of a laboratory Hooke's Law experiment and a Blynk application as its controller. The apparatus was tested by conducting experiments with three different loads: 30 grams, 40 grams, and 50 grams. The experiments aimed to obtain the spring constant, k, which were then processed using Hooke's Law formula based determine spring elongation data, ∆x. The 30 gram load yielded an average ∆x of 0.059 meters with an accuracy of 99.98% and an average k value of 4.90 N/m with an accuracy of 98.75%. The 40 gram load yielded an average ∆x of 0.059 meters with an accuracy of 99.93% and an average k value of 5.32 N/m with an accuracy of 95.40%. The 50 gram load yielded an average ∆x of 0.089 meters with an accuracy of 99.94% and an average k value of 5.53 N/m with an accuracy of 96.39%. The overall accuracy of the apparatus was 99.95% for ∆x and 96.18% for the spring constant. The system can choose the mass, m with control the stepper motor via mobile application and the result of research can be monitored in smartphone display such as such as spring elongation, ∆x, and spring constant, k as well as streaming video for monitoring purposes. [1]      Arsada, Bakhtiyar, and B. Suprianto, “Ultrasonic Sensor Application for Distance Position Detection in Space Using Arduino Uno” State Univ. of Surabaya, 6(2), 137-145, (2017).[2]      K. A. Gamage, D. I. Wijesuriya, S. Y. Ekanayake, A. E. Rennie, C. G. Lambert, and N. Gunawardhana, "Online delivery of teaching and laboratory practices: Continuity of university programmes during COVID-19 pandemic" Educ. Sci., 10(10), 291, (2020). [3]      H. S. Wattimena, A. Suhandi, and A. Setiawan, “Indonesian Physics Education Journal” Indones. Phys. Educ. J., 10(2), 128–139, (2014).[4]      B. K. Prahani, E. Hariyono, H. V. Saphira, I. Zakhiyah, S. Eliezanatalie, and M. H. Ismail, "Digitalization of Physics Laboratory Tools: Increase Undergraduate Students Learning Motivation and Problem-Solving Skills" TEM J., 14(3), 2371–2380, (2025).[5]      S. Madakam, R. Ramaswamy, and S. Tripathi, "Internet of Things (IoT): A Literature" J. Comput. Commun., 3, 164–173, (2015).[6]      M. N. Ramadhani, "Real Laboratory Praktikum Kefisien Muai Panjang Berbasis Internet of Things dan Aplikasi Android" S1 Thesis, Universitas Islam Negeri Walisongo Semarang, (2021).[7]      Z. Wan, Y. Song, and Z. Cao, "Environment dynamic monitoring and remote control of greenhouse with ESP8266 NodeMCU" in Proc. 2019 IEEE 3rd Inf. Technol., Netw., Electron. Autom. Control Conf. (ITNEC), 377–382, (2019). [8]      D. C. Giancoli, Physics, Vol. 1, Jakarta: Erlangga, (2001).[9]      N. Azman, Internet of Things dan Komputasi Edge: Pengenalan Hingga Keamanan, Jakarta: CV. Tampuniak Mustika Edukarya, (2020).[10]  A. Kusumaningrum, A. Pujiastuti, and M. Zeny, "Pemanfaatan Internet of Things pada Kendali Lampu" Compiler, 6(1), 53–59, (2017). [11]  T. Juwariyah, S. Prayitno, and A. Mardhiyya, "Perancangan Sistem Deteksi Dini Pencegah Kebakaran Rumah Berbasis ESP8266 dan Blynk" J. Transistor EI, 3(2), 120–126, (2018).[12]  I. Setiawan and D. Sutarno, "Pembuktian Eksperimental Pengaruh Jumlah Lilitan Pegas dan Diameter Pegas terhadap Konstanta Pegas" in Conf. Proc. Sci., (2011).[13]  P. F. Yudha and R. A. Sani, "Implementasi sensor ultrasonik HC-SR04 sebagai sensor parkir mobil berbasis Arduino" Einstein E-J., 5(3), 19–26, (2019).[14]  G. N. Prakasa, "Prototipe Kunci Pintu Menggunakan Motor Stepper Berbasis Arduino Mega 2560 Dengan Perintah Suara Pada Android" S1 Thesis, Universitas Lampung, (2017).[15]  Y. Efendi, "Internet of Things (IoT) Light Control System Using Mobile-Based Raspberry Pi" Sci. J. Comput. Sci., 4(1), 19–26, (2018). [16]   C. Dziuban, C. R. Graham, P. D. Moskal, A. Norberg, and N. Sicilia, "Blended learning: the new normal and emerging technologies" Int. J. Educ. Technol. High. Educ., 15(1), 3, (2018).[17]  C. Dziuban, C. R. Graham, P. D. Moskal, A. Norberg, and N. Sicilia, "Blended learning: the new normal and emerging technologies" Int. J. Educ. Technol. High. Educ., 15(1), 3, (2018).[18]  M. R. Hidayat, S. Christiono, and S. S. Budi, “Design of IoT-Based Home Security System with NodeMCU ESP8266 Using PIR HC-SR501 Sensor and Smoke Detector Sensor” Kilat J., 7(2), 140–141, (2018).A. Cocco and S. C. Masin, "The Law of Elasticity" Psicologica, 31(3), 647–657, (2010).