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Cardiac Imaging with Electrical Impedance Tomography (EIT) using Multilayer Perceptron Network Ristyawardani, Amelia Putri; Baidillah, Marlin Ramadhan; Adityawarman, Yudi; Busono, Pratondo; Rachmadi, Mochamad Adityo; Yantidewi, Meta; Rahmawati, Endah
Jurnal Elektronika dan Telekomunikasi Vol 25, No 1 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.705

Abstract

This research explores the enhancement of Electrical Impedance Tomography (EIT) for cardiac imaging using Multilayer Perceptron (MLP) networks, focusing on supervised and semi-supervised learning approaches. Using synthetic thoracic datasets simulating dynamic cardiac and respiratory conditions, the study demonstrates that supervised learning achieves lower mean squared error (MSE) values (minimum 4.76) and more stable predictions compared to semi-supervised learning (minimum MSE 5.08). However, semi-supervised learning excels in edge accuracy and noise reduction, particularly in regions with sharp conductivity gradients, making it viable for scenarios with limited labeled data. Dropout regularization at 0.3 provided optimal balance, enhancing model generalization and robustness. While supervised learning outperformed semi-supervised methods in overall accuracy, the latter showed potential for cost-effective and scalable applications in EIT-based cardiac imaging. These findings suggest that integrating advanced machine learning with EIT can improve diagnostic accuracy and enable efficient use of sparse labeled data, paving the way for future optimizations and clinical applications.
Analysis of Critical Thinking Skills of Prospective Elementary School Teacher Student Julianto, Julianto; Wiryanto, Wiryanto; Suprayitno, Suprayitno; Susetyo R, Asri; Hidayati, Fitria; Rahmawati, Endah
IJORER : International Journal of Recent Educational Research Vol. 4 No. 3 (2023): May
Publisher : Faculty of Teacher Training and Education Muhammadiyah University of Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46245/ijorer.v4i3.302

Abstract

Objective: Education is one of the basic needs of humans. The current educational challenge is to produce individuals who can compete in the 21st century. We can access various information freely via the internet, and there is no guarantee that the news we see is true. To use this information properly, individuals must evaluate data and information sources. Method: The type of research used is qualitative research. The population in this study is all ESTE FoE Unesa students, and the sample used is the 2018-2020 class. The sample used was class 2019, D, and F, totaling 84 students. The data collection method used in this study is the test. The instrument used in this study was a critical thinking skills test. Data analysis was carried out in percentage terms. Results: The results showed that the critical thinking skills of Elementary School Teacher Education Faculty of Education Unesa students were in a low category. The results of this study are expected to be used by lecturers or researchers to design and develop learning activities that can facilitate students to practice critical thinking skills. Novelty: Lecturers can design the implementation of learning in the classroom that trains critical thinking skills to become more qualified, effective, and efficient.
Tidal Flood Prediction in Surabaya Based on Hydrometeorological Data Using Gradient Boosting and Logistic Regression Setyaningrum, Kartika Dwi Indra; Masfufah, Kiki Syalasyatun; Rahmawati, Endah; Hermanto, Ady
Jurnal Pijar Mipa Vol. 20 No. 6 (2025)
Publisher : Department of Mathematics and Science Education, Faculty of Teacher Training and Education, University of Mataram. Jurnal Pijar MIPA colaborates with Perkumpulan Pendidik IPA Indonesia Wilayah Nusa Tenggara Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpm.v20i6.10068

Abstract

This research aims to develop a predictive model for tidal inundation at Tanjung Perak Port in Surabaya, a region identified as critical and highly susceptible to such events. The foundational data incorporated comprises hydrometeorological indicators, such as lunar cycles, tidal patterns, and precipitation levels, which were sourced from the BMKG Tanjung Perak Maritime Meteorological Station. A dataset comprising 26,275 individual data points was compiled and subsequently partitioned into training sets (80% of the data) and validation sets (20%) via randomization. This apportionment is intended to support the robustness and applicability of the developed model. The initial data preparation phase involved techniques such as data normalization, imputation of missing values, and the determination of variable weights based on their respective degrees of impact. Subsequently, two distinct machine learning methodologies were employed to construct the predictive framework: Gradient Boosting (specifically, XGBoost) and Logistic Regression. The efficacy of the resultant models was rigorously assessed using various metrics, including accuracy, confusion matrix analysis, ROC-AUC scores, and feature significance analysis. Analysis of the outcomes indicated that the Gradient Boosting model achieved a superior accuracy of 99.96%, whereas Logistic Regression attained 99.85%. An examination of the features revealed that lunar cycles and tidal conditions were the principal determinants of tidal inundation, with precipitation exerting a comparatively minor effect. These observations substantiate the efficacy of integrating suitable data preparation techniques with machine learning methodologies to achieve precise predictive outcomes. The principal contribution of this investigation is the establishment of a computational framework to facilitate the development of an advanced warning system for tidal flooding, thereby aiding hazard reduction and limiting adverse societal, financial, and operational consequences in littoral regions.
Rancangan Sistem Pendukung Keputusan Pemilihan Calon Pegawai Honorer Pemerintah Kabupaten Lamandau Menggunakan Metode Profile Matching Irmayanti, Ade; Rahmawati, Endah; Julita, Maya
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 8 No. 3 (2024): IKRAITH-INFORMATIKA Vol 8 No 3 November 2024
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikraith-informatika.v8i3.4368

Abstract

This study aims to design a Decision Support System (DSS) that implements the Profile Matchingmethod for the selection of honorary employees in the Lamandau District Government. The oftennon-systematic selection process results in less objective decisions, necessitating a system that canenhance effectiveness and transparency in decision-making. The Profile Matching method is usedto compare the profiles of candidates with predetermined criteria, leading to a fairer and moreaccurate selection process. Data were collected through interviews with relevant stakeholders inthe Lamandau District Government, which were then analyzed to identify appropriate selectioncriteria. The findings indicate that the application of DSS can reduce subjectivity and improveclarity in the evaluation process. Additionally, the designed computer-based system facilitatesfaster data processing and presents information in a more comprehensible manner. Thus, thisresearch is expected to make a significant contribution to the development of employee selectionsystems in local government and enhance the quality of human resources in public service. Theimplementation of information technology in DSS is anticipated to serve as a reference for futureresearch in decision-making and human resource management.
Pemberdayaan Masyarakat Melalui Eco-Enzyme untuk Pengelolaan dan Degradasi Limbah Cair Industri Tempe di Desa Sukorejo Trenggalek Firdaus, Rohim Aminullah; Rahmawati, Endah; Dzulkiflih, Dzulkiflih; Khoiro, Muhimmatul; Putri, Nugrahani Primary; Yantidewi, Meta
Lumbung Inovasi: Jurnal Pengabdian kepada Masyarakat Vol. 10 No. 4 (2025): December
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/6eyqtz37

Abstract

Limbah cair industri tempe memiliki beban organik tinggi (COD, BOD, TSS) yang berpotensi menurunkan kualitas lingkungan jika dibuang tanpa pengolahan. Sebagian besar pelaku UMKM tempe di pedesaan belum memiliki akses terhadap teknologi pengolahan yang murah dan sederhana, sehingga diperlukan pendekatan alternatif berbasis partisipasi masyarakat. Kegiatan Pengabdian kepada Masyarakat (PKM) ini bertujuan memberdayakan warga Desa Sukorejo, Trenggalek dalam pengelolaan limbah cair menggunakan eco-enzyme hasil fermentasi sampah organik rumah tangga. Berbeda dari pendekatan konvensional, kegiatan ini menerapkan model partisipatif dengan pembuatan dan penerapan eco-enzyme berbasis rumah tangga yang terintegrasi dengan monitoring masyarakat, sebuah pendekatan yang belum umum diterapkan pada pengelolaan limbah tempe skala kecil. Metode meliputi pemetaan pelaku usaha, sosialisasi, pelatihan pembuatan eco-enzyme (rasio 3:1:10; fermentasi ±90 hari), penyusunan SOP aplikasi (1–5% v/v), dan pendampingan uji sederhana (pH, bau, kekeruhan). Program diikuti 18 peserta dan menghasilkan kelompok pengelola serta unit percontohan. Observasi menunjukkan penurunan bau dan kekeruhan dalam 24–48 jam serta peningkatan pengetahuan peserta. Evaluasi respon peserta menunjukkan kategori sangat baik (rata-rata >90%). Kegiatan ini efektif meningkatkan kapasitas masyarakat dan menunjukkan potensi eco-enzyme sebagai solusi awal pengolahan limbah cair tempe yang murah dan berkelanjutan. Community Empowerment Through Eco-Enzymes for the Management and Degradation of Liquid Waste from Tempeh Industries in Sukorejo Village, Trenggalek Abstract Liquid waste from tempeh production contains high organic loads (COD, BOD, TSS) that can degrade environmental quality if discharged without proper treatment. Most small-scale tempeh producers in rural areas lack access to simple and low-cost treatment technologies, necessitating an alternative approach grounded in community participation. This Community Service Program (PKM) aims to empower residents of Sukorejo Village, Trenggalek in managing liquid waste using eco-enzymes produced from the fermentation of household organic waste. Unlike conventional approaches, this program adopts a participatory model involving the household-based production and application of eco-enzymes integrated with community monitoring—an approach that is rarely implemented for small-scale tempeh wastewater management. The methods included stakeholder mapping, awareness-building activities, training on eco-enzyme production (3:1:10 ratio; ± 90-day fermentation), preparation of application SOPs (1–5% v/v), and facilitation of simple testing (pH, odor, turbidity). The program involved 18 participants and resulted in the formation of a management group and a pilot demonstration unit. Observations indicated reductions in odor and turbidity within 24–48 hours, alongside improved participant knowledge. Participant response evaluations showed excellent results (average >90%). This program effectively enhanced community capacity and demonstrated the potential of eco-enzymes as a low-cost and sustainable preliminary solution for treating liquid waste from tempeh production.