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All Journal Infotekmesin Indonesian Journal of Electrical Engineering and Computer Science Blend Sains Jurnal Teknik
Rahadi, Nur Wahyu
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Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Handling missing values and clustering industrial liquid waste using K-medoids Maharrani, Ratih Hafsarah; Abda'u, Prih Diantono; Ikhtiagung, Ganjar Ndaru; Rahadi, Nur Wahyu; Zaenurrohman, Zaenurrohman
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i2.pp1411-1420

Abstract

The textile industry is a significant contributor to environmental pollution due to its wastewater, which contains hazardous substances such as dyes, heavy metals, and chemicals that can severely harm aquatic ecosystems. Effective management of this wastewater is crucial to mitigate its environmental impact. This study focuses on classifying industrial liquid waste data using the K-medoids clustering method, chosen for its robustness to noise and outliers compared to K-means. To address challenges in wastewater data processing, such as missing values and varying data scales, two approaches are compared: replacing missing values with zero and K-nearest neighbors (KNN) imputation, alongside Z-score normalization for data uniformity. The clustering quality is evaluated using the Davies-Bouldin index (DBI) for cluster variations of k=2, 3, 4, and 5. The results show that the best clustering quality is achieved at k=2, with the smallest DBI values obtained using KNN imputation (0.139) and zero replacement (0.149). The superior performance of KNN imputation highlights its effectiveness in handling missing data. These findings provide valuable insights into the characteristics of textile industry wastewater pollution, offering a robust framework for effective wastewater management. The study concludes with practical recommendations for policymakers and industry stakeholders to adopt advanced data-driven approaches for sustainable wastewater treatment strategies.
Metode Fuzzy Time Series Markov Chain Untuk Peramalan Curah Hujan Harian Sari, Laura; Romadloni, Annisa; Listyaningrum, Rostika; Hazrina, Fadhilla; Rahadi, Nur Wahyu
Infotekmesin Vol 15 No 1 (2024): Infotekmesin: Januari, 2024
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v15i1.2182

Abstract

Cilacap Regency has diverse topography and geographical conditions which cause this region to have rainfall that varies spatially and temporally; therefore, a forecasting method to overcome these uncertainties and fluctuations is needed. Fuzzy Time Series Markov Chain utilizes Fuzzy logic which provides flexibility in handling uncertain and unstructured data. Moreover, the addition of Markov chain elements that utilize Fuzzy logic concepts provides flexibility in handling data allowing the model to capture inter-time relationships and changes in system state that depend on previous states. Therefore, the research aims to see the suitability of the Fuzzy Time Series Markov Chain for predicting daily rainfall in Cilacap Regency. The method is suitable for predicting rainfall data for Cilacap Regency. The accuracy value in this study can be seen from the RMSE and SMAPE values ​​on the training data (in-sample), respectively, which are 58.76469 and 0.7227493. Meanwhile, the testing data (out sample) was 56.01818 and 0.7055117.
Penerimaan Sistem Peringatan Dini Tsunami oleh Masyarakat Pesisir Melalui Integrasi Variabel Kontekstual dalam Model TAM Prabowo, Annas Setiawan; Prihantara, Andesita; Rahadi, Nur Wahyu; Bahroni, Isa
Blend Sains Jurnal Teknik Vol. 4 No. 3 (2026): Edisi Januari
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/blendsains.v4i3.1374

Abstract

Kabupaten Cilacap yang terletak di Pesisisr selatan Pulau Jawa merupakan wilayah strategis dengan berbagai aktivitas kelautan dan perikaanan yang tinggi, namun dibalik potensi yang besar memilik tingkat akerentanan yang besar juga tentang ancaman Tsunami. Badan Meteorologi, Klimatologi, dan Geofisika telah mengembangkan Early Warning System (EWS) berupa Sistem Peringatan Dini Tsunami sebagai salah satu kegiatan pemerintah untuk mengurangi dampak resiko bencana tsunami. Infrastruktur dan teknologi sudah dibuat, namun tingkat adopsi system oleh masyarakat pesisir masih tergolong rendah. Hal tersebut menunjukkan bahwa ada kesenjangan antara perilaku penerimaan teknologi dengan ketersediaan teknologi. Tujuan penelitian ini adalah mengetahui faktor pengaruh penerimaan masyarakat pesisir Cilacap terhadap sistem peringatan dini Tsunami melalui model TAM dengan integrasi variable kontenstual yaitu trust, experience dan subjective norm. Pendekatan kuantitatif dilakukan dengan mengambil data menggunakan kuesioner serta pengukuran dengan skala likert kepada masyarakat pesisir Cilacap serta dianalisisi menggunakan Structural Equation Modeling. Hasil penelitian menemukan Perceived Ease of Use berpengaruh positif terhadap Perceived Usefulness dengan nilai koefisien 0,470, Perceived Usefulness berpengaruh positif terhadap Behavioral Intention to Use dengan nilai koefisien 0,396, dan Trust berpengaruh langsung terhadap Behavioral Intention to Use dengan nilai koefisien 0,422. Temuan ini menunjukkan penerimaan teknologi penerimaan dini tsunami dipengaruhi oleh persepsi manfaat dan tingkat kepercayaan terhadap penyedia layanan teknologi.
Co-Authors Annisa Romadloni Hazrina, Fadhilla Ikhtiagung, Ganjar Ndaru Isa Bahroni, Isa Listyaningrum, Rostika Maharrani, Ratih Hafsarah Prabowo, Annas Setiawan Prih Diantono Abda`u Prihantara, Andesita Sari, Laura Zaenurrohman Zaenurrohman