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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Physics Student Journal Jurnal EECCIS Natural B Journal of Engineering and Technological Sciences Science and Technology Indonesia JOIV : International Journal on Informatics Visualization Journal of Information Technology and Computer Science Indonesian Physical Review JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Mitra Akademia: Jurnal Pengabdian Masyarakat Jurnal Nasional Teknik Elektro dan Teknologi Informasi Prisma Sains: Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram
Agus Naba
Departemen Fisika, Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Brawijaya
Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Physics Social Sciences Other

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Assessment of Post-Disaster Building Damage Levels Using Back-Propagation Neural Network Prediction Techniques Wibowo Almais, Agung Teguh; Fajrin, Rahma Annisa; Naba, Agus; Sarosa, Moechammad; Juhari, Juhari; Susilo, Adi
JOIV : International Journal on Informatics Visualization Vol 9, No 3 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.3.2711

Abstract

Indonesia is susceptible to natural disasters, with its geographical location being one of the contributing factors. To mitigate the harmful effects of natural catastrophes, a disaster emergency response must be undertaken, consisting of steps taken immediately following the event. These operations include rescuing and evacuating victims and property, addressing basic needs, providing protection, and restoring buildings and infrastructure. Accurate data is required for adequate recovery after a disaster. The Badan Penanggulangan Bencana Daerah (BPBD) oversaw disaster relief efforts, but faulty damage assessments slowed restoration. Surveyor subjectivity and differing criteria result in discrepancies between reported damage and reality, generating issues during the post-disaster reconstruction. The objective of this study is to develop a prediction system to measure the extent of damage caused by natural disasters to buildings. The five criteria that decide the level of building damage after a disaster are building conditions, building structure condition, physical condition of severely damaged buildings, building function, and other supporting conditions. The data used are from the BPBD of Malang city from 2019 to 2023. This system would allow surveyors to make speedy and objective evaluations. Five different models were tested using the Neural Network Backpropagation approach. Model A2 produces the highest accuracy of 93.81%. A2 uses a 40-38-36-34 hidden layer pattern, 1000 epochs, and a learning rate 0.1. These findings can lay the groundwork for advanced prediction models in post-disaster building damage evaluation research.
Autonomous mobile robot implementation for final assembly material delivery system Firdaus, Ahmad Riyad; Sholihuddin, Imam; Hutasoit, Fania Putri; Naba, Agus; Suciningtyas, Ika Karlina Laila Nur
International Journal of Electrical and Computer Engineering (IJECE) Vol 16, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v16i1.pp158-173

Abstract

This study presents the development and implementation of an autonomous mobile robot (AMR) system for material delivery in a final assembly environment. The AMR replaces conventional transport methods by autonomously moving trolleys between the warehouse, production stations, and recycling areas, thereby reducing human intervention in repetitive logistics tasks. The proposed system integrates a laser-SLAM navigation approach, customized trolley design, RoboShop programming, and robot dispatch system coordination, enabling real-time route planning, obstacle detection, and material scheduling. Experimental validation demonstrated high accuracy in path following, with root mean square error values ranging between 0.001 to 0.020 meters. The AMR achieved an average travel distance of 118.81 meters and a cycle time of 566.90 seconds across three final assembly stations. The overall efficiency reached 57%, primarily due to reduced idle time and optimized material replenishment. These results confirm the feasibility of AMR deployment as a scalable and flexible intralogistics solution, supporting the transition toward Industry 4.0 smart manufacturing systems.
Quartz Crystal Microbalance (QCM) Sensor Array with Varying PMMA Coatings for Coffee Roasting Aroma Monitoring Muttaqin, Adharul; Sakti, Setyawan Purnomo; Naba, Agus; Mudjirahardjo, Panca
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 14, No 1: March 2026
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v14i1.7760

Abstract

This study investigates how polymethyl methacrylate (PMMA) coating concentration (3–15 wt%) tunes the response of an eight-channel Quartz Crystal Microbalance (QCM) sensor array to real coffee roasting volatiles at 200–240 °C. One channel was left uncoated as a reference, while seven channels were coated with different PMMA concentrations to introduce controlled response diversity. Baseline-corrected frequency shifts were processed into qualitative features describing response magnitude, kinetics, and early recovery, and principal component analysis (PCA) was used to visualize multichannel pattern structure across repeated roasts. Consistent temperature-dependent response patterns were observed, while run-to-run variability increased at higher temperatures. The first two principal components captured ~75% of the total variance (PC1 dominated by integrated response magnitude and PC2 reflecting kinetic variability). Because chamber humidity increased during roasting, a supplementary robustness check was performed using recorded RH; temperature-dependent structure remained after accounting for humidity effects. Overall, discrimination arises from the collective multichannel response, suggesting potential applicability of PMMA-coated QCM arrays for qualitative coffee roasting monitoring, pending further validation with larger datasets and complementary analytical methods.
A Data-Driven Framework for Digital Fire Pump Condition Monitoring and NFPA 25 Compliance Support in Industrial Buildings Sholihuddin, Imam; Naba, Agus; Sucinintyas, Ika Karlina Laila Nur; Dharmawan, Hari Arief; Simatupang, Deo Dekri
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 20 No. 2 (2026)
Publisher : Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v20i2.2046

Abstract

Fire pump systems are critical components of building fire protection infrastructure, yet their predominantly standby operation increases the risk of undetected failures between inspections. This study presents a digital monitoring framework for fire pump condition monitoring and NFPA 25 compliance support that continuously records hydraulic and operational data, automatically classifies weekly and annual test events, and generates structured digital records without modifying certified fire protection control functions. The framework was implemented in an industrial facility with electric- and diesel-driven fire pumps. Hydraulic evaluation of a Monoflo KP MX150-140 fire pump covered a flow range of 4,410–6,724 L/min (70.0%–106.7% of rated capacity). Digitalpressure measurements closely matched manual readings, with differences of 0.00–0.10 bar, and all 22 labeled test events werecorrectly identified. The system also enabled performance trending and reduced annual testing and documentation effortfrom approximately four days to 10–30 min (>90% reduction). Because the no-flow and 150% rated-flow conditions were notevaluated, the results represent a partial hydraulic assessment. Overall, the proposed human-in-the-loop framework improvesmonitoring visibility, inspection traceability, and audit readiness while supporting compliance-oriented digitalization.
Co-Authors Abdurrouf - Adi Susilo Adi Susilo Agung Teguh Wibowo Almais Agus Wahid Ahmad Nadhir Ahmad Riyad Firdaus Alfina Taurida Alaydrus Andrijani Sumarahinsih Ciptaningrum, Mega Satya D. J. Djoko Herry Santjojo Djoko Santjojo eko teguh purwito, eko teguh Elta Sonalitha Erni Yudaningtyas Fachrudin Pakaja Fajrin, Rahma Annisa Fatimah Kunti Hentihu, Fatimah Kunti Firdaus, Ahmad Kanzu Syauqi Fitroh Amaluddin Gayatri Dwi Santika Hamles Leonardo Latupeirissa Handono Kalim Hari Arief Dharmawan Hari Santoso Hari Santoso Hariyadi Soetedjo Harry Soekotjo Dachlan Herditomo Herditomo Hutasoit, Fania Putri Ika Karlina Laila Nur Suciningtyas Imam Sholihuddin Juhari Juhari, Juhari Juwono, Alamsyah M. M. Aziz Muslim Maryantho Masarrang Maryantho Masarrang Mauludi Ariesto Pamungkas Mega Satya Ciptaningrum Moechammad Sarosa Moh. Fausi Mohamad Saad A.Sawa Mohammad Zoqi Sarwani, Mohammad Zoqi Mudjirahardjo, Panca Muhammad Aziz Muslim Muhammad Fadlil Khoironi Muhammad Fathur Rouf Hasan Muttaqin, Adharul Purwanto Purwanto Ridwan Awalin Rizky Benny Relado, Rizky Benny Setyawan Purnomo Sakti Simatupang, Deo Dekri Sri Herwiningsih Sucinintyas, Ika Karlina Laila Nur Sugeng Rianto Suhayat Minardi Sunaryo Sunaryo Umi Salamah Wayan Firdaus Mahmudy Yogie Susdyastama Putra Yudianto, Didik Yuyun Yueniwati