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All Journal Berkala Fisika Indonesia : Jurnal Ilmiah Fisika, Pembelajaran dan Aplikasinya JFA (Jurnal Fisika dan Aplikasinya) Jurnal MoZaiK Jurnal Pendidikan Fisika dan Teknologi GERVASI: Jurnal Pengabdian kepada Masyarakat JURNAL CRANKSHAFT Jurnal Abdi Insani Jurnal Pengabdian Masyarakat Indonesia Magnetic: Research Journal of Physics and It’s Application Jurnal Pijar MIPA Jurnal Dinamika Informatika (JDI) JRFES Antigen: Jurnal Kesehatan Masyarakat dan Ilmu Gizi Emitor: Jurnal Teknik Elektro
Wahyu Sugianto
Universitas PGRI Yogyakarta
Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

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Developing Multi-Frequency Bioelectrical Impedance Analysis for Fat-Free Mass Estimation in Early Childhood Wismaya, Herenda Sela; Sugianto, Wahyu; Hanifah, Rida Dwi
Jurnal Pendidikan Fisika dan Teknologi (JPFT) Vol 10 No 2 (2024): July - December
Publisher : Department of Physics Education, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpft.v10i2.8228

Abstract

This study aims to develop and evaluate a Multi-Frequency Bioelectrical Impedance Analysis (MFBIA) system for estimating body composition, specifically Fat-Free Mass (FFM) and Body Fat Percentage (BF%). The primary objective was to assess the accuracy and reliability of the MFBIA system by comparing its measurements with those obtained from a commercially validated Smart Body Fat analyzer and traditional anthropometric methods. The research involved regression analysis to examine the correlation between FFM and BF% measurements from MFBIA and anthropometric data, including height and weight. Additionally, impedance measurements were taken at multiple frequencies (25 kHz, 50 kHz, and 100 kHz) to determine the system's ability to estimate body composition parameters across various conditions. The results showed a strong correlation between the FFM and BF% values ​​derived from MFBIA and those obtained using the Smart Body Fat analyzer. The regression analysis indicated high linearity, with R² values ​​ranging from 0.9439 to 0.9692, signifying the robustness of the system in predicting body composition. Furthermore, the MFBIA system demonstrated a high degree of consistency and accuracy in measuring FFM and BF%, with minimal deviations from the reference device. This research presents a multi-frequency BIA device designed specifically to measure fat-free mass (FFM), an important indicator for assessing the nutritional status of children. The results of this research offer a practical, affordable, and non-invasive tool for healthcare providers to assess body composition in children. The MFBIA system has the ability to track nutritional status, supporting targeted interventions to promote child health and prevent stunting.
Literasi Peduli Lingkungan Global melalui Edukasi E-waste di Sekolah Menengah Kebangsaan Bandar Baru Uda Ferra Arik Tridaleatari; Wahyu Sugianto; Margala Juang Bertorio; Fathah Dian Sari; Dena Anugrah; Adhila Fayasari
Jurnal Pengabdian Masyarakat Indonesia Vol 5 No 6 (2025): JPMI - Desember 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpmi.3790

Abstract

Permasalahan limbah elektronik (e-waste) menjadi isu lingkungan global yang mendesak, khususnya di negara-negara berkembang. Kegiatan pengabdian internasional ini bertujuan untuk meningkatkan literasi lingkungan hidup siswa SMK Bandar Baru UDA (BBU), Johor Bahru, Malaysia, melalui edukasi e-waste yang dikemas dalam bentuk penyuluhan interaktif dan kegiatan partisipatif. Kegiatan diikuti oleh 142 peserta, yang terdiri dari 124 siswa, 7 guru pendamping, serta tim dari Universitas PGRI Yogyakarta dan CSNano Universitas Teknologi Malaysia. Materi disampaikan melalui metode audio-visual, pameran poster, dan kuis interaktif yang dirancang untuk meningkatkan pemahaman serta sikap terhadap pengelolaan e-waste. Hasil evaluasi menunjukkan adanya peningkatan signifikan dalam literasi lingkungan: pemahaman terhadap bahaya e-waste dan pentingnya daur ulang meningkat dari 63,71% menjadi 72,58%, sikap bertanggung jawab dalam pengelolaan e-waste naik dari 56,45% menjadi 64,41%, dan minat mengikuti kampanye e-waste meningkat dari 45,97% menjadi 54,23%. Dukungan terhadap pentingnya edukasi e-waste di sekolah juga mengalami peningkatan dari 71% menjadi 74,58%. Temuan ini mengindikasikan bahwa pendekatan edukatif berbasis kolaborasi internasional efektif dalam meningkatkan kesadaran dan partisipasi aktif generasi muda terhadap isu lingkungan hidup. Ke depannya, sebaiknya dilaksanakan program yang bersifat lebih aplikatif, sekaligus memperkaya kegiatan dengan aksi nyata seperti kompetisi daur ulang, kampanye berbasis kreativitas, serta pemaparan langsung inovasi teknologi dalam pengelolaan limbah elektronik.
Prediksi Penyakit Diabetes Mellitus Tipe I dan Tipe II Menggunakan Metode KNN di Klinik Dharma Husada Richa Nanda Fitria; Wahyu Sugianto; Amalia Cemara Nur’aidha
Antigen : Jurnal Kesehatan Masyarakat dan Ilmu Gizi Vol. 2 No. 3 (2024): Agustus : Antigen: Jurnal Kesehatan Masyarakat dan Ilmu Gizi
Publisher : LPPM STIKES KESETIAKAWANAN SOSIAL INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57213/antigen.v2i3.303

Abstract

Diabetes Mellitus (DM) is a metabolic disorder characterized by high blood sugar levels due to insulin deficiency. Factors causing Diabetes Mellitus (DM) are lifestyle which includes diet, lack of exercise, monitoring blood sugar, and medication. Most people do not realize that they have DM and only find out when they experience severe symptoms. To avoid this, the k-Nearest Neighbor (KNN) method can be used to predict the possibility of developing diabetes. The aim of this research is to classify diabetes mellitus using the K-Nearest Neighbor (KNN) method and make people more aware of the risk of disease through healthy lifestyle changes. Data received from the Dharma Husada Clinic is categorized based on researchers' needs, including age, BMI, insulin, skin thickness, glucose, diabetes, genetics, and insulin. This research was carried out in three main steps: dataset input, preprocessing, and evaluation. The first stage is data analysis which begins by entering a dataset to train and test the model, where each data element has certain characteristics (attributes) and classes. Preprocessing steps include training data generation and data cleaning, which includes sanitization, lowercase, normalization, stopwords, stemming, and tokenizing. The final step is evaluating. Evaluation includes building an evaluation model and measuring the level of accuracy, building a predictive model, and saving the model. This research shows that the K-Nearest Neighbor (KNN) method can be used to classify diabetes mellitus (DM), but especially in a small dataset consisting of 245 dates and 8 attributes it is not accurate for patients aged 30 years. . A k value that is too small can cause overfitting, and a k value that is too large can cause underfitting. However, if the amount of data is small, the choice of k can have a large impact.
Sistem Cerdas Berbasis Website untuk Deteksi dan Analisis Acne Vulgaris Menggunakan CNN Chandra Aditya; Wahyu Sugianto
Jurnal Dinamika Informatika Vol. 15 No. 1 (2026): Vol. 15 No. 1 (2026)
Publisher : Program Studi Informatika Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/jdi.v15i1.433

Abstract

Perkembangan teknologi kecerdasan buatan, khususnya dalam bidang computer vision, membuka peluang besar dalam mendukung pemeriksaan dermatologi. Acne vulgaris merupakan salah satu kondisi kulit yang memerlukan identifikasi awal secara akurat untuk menentukan perawatan yang sesuai. Penelitian ini bertujuan mengembangkan website pendeteksi acne vulgaris berbasis Convolutional Neural Network (CNN). Dataset yang digunakan terdiri dari beberapa jenis lesi acne vulgaris, antara lain blackheads, whiteheads, pustules, Papules, dan kategori non-acne. Data citra diolah melalui tahap preprocessing seperti normalisasi, resizing, dan augmentation untuk meningkatkan kualitas pelatihan model. Model CNN yang dibangun kemudian diintegrasikan ke dalam aplikasi berbasis web/mobile agar dapat digunakan secara praktis. Hasil pengujian menunjukkan bahwa model mampu melakukan klasifikasi jenis lesi dengan tingkat akurasi yang cukup baik dengan accuracy: 0.8450, loss: 0.4269, val_accuracy: 0.8050, val_loss: 0.6159. Aplikasi ini diharapkan dapat membantu pengguna dalam mengenali jenis lesi acne vulgaris secara mandiri sebelum melakukan konsultasi lebih lanjut dengan tenaga medis.
Design of Arduino Uno-Based Height and Weight Measuring Instrument for Initial Screening of Stunting Cases: Talitha Nabila Hayuningclara, Wahyu Sugianto, and Amalia Cemara Nur ’Aidha Talitha Nabila Hayuningclara Talitha Nabila Hayuningclara; Wahyu Sugianto Wahyu Sugianto; Amalia Cemara Nur ’Aidha Amalia Cemara Nur ’Aidha
Jurnal Fisika dan Aplikasinya Vol 20 No 2 (2024): June 2024 Edition
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat, LPPM-ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24604682.v20i2.20400

Abstract

Monitoring nutritional status in toddlers is very important because it can be an early indicator of possible health problems in children. Currently, the process of monitoring children's nutrition is generally still carried out manually, which not only takes longer but is also less efficient in practice. To overcome the limitations of conventional measuring devices, a digital measuring device for height and weight was designed. This tool displays the results of height and weight measurements simultaneously on an LCD (liquid crystal display) screen. This tool works with uses an Arduino microcontroller as a control center and uses electronic sensors, namely the HC-SR07 ultrasonic sensor to measure height and the HX711 loadcell sensor to measure weight. From the data obtained, the error value and accuracy of the loadcell sensor after calibration produced an error value of 6.24% and an accuracy of 93.76%. Meanwhile, the ultrasonic sensor test results after the calibration process produced an error value of 0.052% and an accuracy of 99.94%.
Kajian Awal Karakteristik Impedansi Listrik Larutan NaCl pada Berbagai Konsentrasi Menggunakan Metode Spektroskopi Impedansi Listrik Wahyu Sugianto; Herenda Sela Wismaya
Magnetic: Research Journal of Physics and It’s Application Vol. 3 No. 1 (2023): Magnetic: Research Journal of Physics and It’s Application
Publisher : Program Studi Fisika - Universitas San Pedro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59632/magnetic.v3i1.254

Abstract

Larutan NaCl merupakan salah satu elektrolit utama dalam tubuh manusia. Selain itu, pemanfaatan larutan NaCl sebagai larutan pengencer pada bidang medis juga banyak digunakan. Makalah ini menganalisis karakteristik impedansi larutan NaCl dan juga hubungan antara konsentrasi dengan nilai impedansi listrik dari larutan NaCl. Metode Spektroskopi Impedansi Listrik (SIL) diterapkan dengan menginjeksikan arus listrik sebesar 1 mA ke dalam larutan NaCl. Tegangan keluaran respons dicatat menggunakan PicoScope 5244B. Pengukuran impedansi menggunakan dua elektroda jarum yang terbuat dari emas dalam rentang frekuensi 1 Hz hingga 100 kHz. Konsentrasi sampel larutan NaCl yang digunakan 1,7 mM- 513 mM. Karakteristik impedansi hasil pengukuran larutan NaCl memiliki pola seperti model rangkaian ekuivalen Randles. Pengukuran impedansi larutan NaCl yang baik adalah pada rentang frekuensi 10 kHz – 100 kHz dimana larutan NaCl memiliki sifat resistif yang dominan. Hasil pengukuran impedansi listrik dari Larutan NaCl semakin berkurang dengan bertambahnya konsentrasi larutan NaCl.
Identifikasi Jenis Larutan Ionik Berdasarkan Data Spektroskopi Impedansi Listrik Menggunakan Unsupervised Machine learning Wahyu Sugianto; Herenda Sela Wismaya
Magnetic: Research Journal of Physics and It’s Application Vol. 5 No. 2 (2025): Magnetic: Research Journal of Physics and It’s Application
Publisher : Program Studi Fisika - Universitas San Pedro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59632/magnetic.v5i2.644

Abstract

Identifikasi jenis larutan ionik merupakan salah satu bagian fundamental dalam bidang biomedis. Spektroskopi Impedansi Listrik (SIL) merupakan sebuah metode yang terbukti mampu mengidentifikasi proses elektokimia yang unik untuk setiap larutan, namun interpretasi hasil pengukuran pada SIL terbilang cukup rumit. Disisi lain, metode identifikasi secara cepat, akurat, dan tanpa reagen menjadi kebutuhan penting dalam bidang biomedis dan lingkungan. Penelitian ini bertujuan untuk mengevaluasi potensi penggunaan Unsupervised Machine learning, khususnya metode Principal component analysis (PCA) dan K-Means untuk menginterpretasikan hasil pengukuran spektroskopi impedansi listrik (SIL) sehingga mampu membedakan jenis larutan ionik NaCl, Ringer Laktat (RL), dan Simulated Body Fluid (SBF). Pengukuran impedansi dilakukan pada rentang frekuensi 1 Hz hingga 1 MHz menggunakan dua elektroda tanpa modifikasi permukaan. Selanjutnya, hasil pengukuran impedani berupa  dan  dianalisis untuk mengekstrak data. Proses analisis meliputi pra-pemrosesan data, reduksi dimensi menggunakan Principal component analysis (PCA), dan klasterisasi dengan algoritma K-Means. PCA mampu merangkum informasi sebesar 75.8% dalam dua komponen utama, dan hasil klasterisasi menunjukkan pemisahan yang cukup jelas antara ketiga jenis larutan dengan nilai accuracy sebesar 88.9%, Adjusted Rand Index (ARI) sebesar 0.6865, serta silhouette score sebesar 0.4473. Hasil ini menunjukkan bahwa penggunaan kombinasi algortima PCA dan K-Means memiliki potensi untuk interpretasi hasil SIL yang tidak memerlukan data berlabel (unsupervised) dengan performa yang kompetitif jika dibandingkan dengan metode supervised, sehingga lebih fleksibel untuk aplikasi dimana pelabelan data sulit dilakukan.
OPTIMALISASI PEMANTAUAN PERTUMBUHAN ANAK DI POSYANDU UMBULHARJO MELALUI PENGGUNAAN PERANGKAT ANTROPOMETRI IoT Wahyu Sugianto; Herenda Sela Wismaya; Brevi Istu Pambudi
Jurnal Abdi Insani Vol 13 No 1 (2026): Jurnal Abdi Insani
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/abdiinsani.v13i1.3228

Abstract

Stunting and underweight among children under five remain significant nutritional challenges in Indonesia, including in Sleman. These conditions are influenced by inadequate dietary intake, limited access to health services, and socioeconomic factors. Their long-term impact may hinder children's physical growth and cognitive development. Accurate growth monitoring is essential for early prevention of nutritional problems. This program aims to enhance community knowledge and skills in early detection of nutritional risks through the use of IoT-based anthropometric devices. The program involved problem identification, development of IoT anthropometric equipment, and training on device use for cadres and parents. Knowledge improvement was evaluated using Pre-Test and Post-Test scores analyzed with a paired t-test. Participants' knowledge increased by 12.3% based on the Pre-Test and Post-Test comparison. Cadres were able to operate the IoT anthropometric device independently and demonstrated good understanding during practice sessions. Participants showed high engagement, including four questions raised during discussions. The device provided real-time data and supported easier recording of child growth. Its implementation improved the accuracy of early detection of nutritional risks. The adoption of IoT-based anthropometric devices enhances early detection of nutritional problems and strengthens child growth monitoring at the Posyandu.
Viability Using Multimodal Integration of Bioimpedance Spectroscopy and Spectrophotometry Afrida Firdausi; Wahyu Sugianto; Argawi Kandito
Emitor: Jurnal Teknik Elektro Vol 26, No 2: July 2026
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/emitor.v26i2.17220

Abstract

Bacterial viability monitoring is generally carried out using the Total Plate Count (TPC) method, but this method requires an incubation time of 24–48 hours, making it less efficient for rapid detection. This study aims to develop a method for estimating the number of viable bacteria based on the integration of bioimpedance and absorbance. Cell lysis was induced using varying doses of alcohol, bioimpedance measurements were performed using the BioSMET system at a frequency range of 20 Hz–100 kHz and absorbance measurements at a wavelength of 260 nm. The analysis results showed that a frequency of 70 kHz had the highest correlation with bacterial viability and was selected as the optimal frequency. Integration of both parameters using the Multiple Linear Regression (MLR) model increased the prediction accuracy with a value and RMSE of 0.4156. These results indicate that the multimodal approach is able to provide more accurate and faster estimates compared to the conventional TPC method.
Identifikasi tingkat kematangan buah pisang berdasarkan karakteristik impedansi listrik dengan metode spektroskopi impedansi listrik menggunakan elektroda 4 jarum Wahyu Sugianto; Herenda Sela Wismaya
Berkala Fisika Indonesia : Jurnal Ilmiah Fisika, Pembelajaran dan Aplikasinya Vol. 15 No. 1 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/bfi-jifpa.v15i1.25556

Abstract

Co-Authors Adhila Fayasari Afrida Firdausi Ajeng Ayu Priyaniti Amalia Cemara Nur ’Aidha Amalia Cemara Nur ’Aidha Amalia Cemara Nuraidha, Amalia Cemara Amalia Cemara Nur’aidha Argawi Kandito Argawi Kandito Argawi Kandito Beatrix Violeta Brevi Istu Pambudi Budi Satrio, , R. Sugeng Chaerunisa, Salsabilla Thallah Chandra Aditya Dasmasela, Evangelista Militchia Christy Dena Anugrah Fathah Dian Sari Fathia D.S, Adinda Fajar Mila Ferra Arik Tridaleatari Hanifah, Rida Dwi Hayuningclara, Talitha Nabila Herenda Sela Wismaya Khulayfah, Ade Fitri Kumarajati, Dhananjaya Y.H. Kumarajati, Dhananjaya YH Margala Juang Bertorio Mira Setiana Pionis, Pankrasius Richa Nanda Fitria Talitha Nabila Hayuningclara Talitha Nabila Hayuningclara