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All Journal International Journal of Electrical and Computer Engineering 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 JMM (Jurnal Masyarakat Mandiri) 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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Journal : International Journal of Electrical and Computer Engineering

 1 
Rule Optimization of Fuzzy Inference System Sugeno using Evolution Strategy for Electricity Consumption Forecasting Gayatri Dwi Santika; Wayan Firdaus Mahmudy; Agus Naba
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 4: August 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (849.029 KB) | DOI: 10.11591/ijece.v7i4.pp2241-2252

Abstract

The need for accurate load forecasts will increase in the future because of the dramatic changes occurring in the electricity consumption. Sugeno fuzzy inference system (FIS) can be used for short-term load forecasting. However, challenges in the electrical load forecasting are the data used the data trend. Therefore, it is difficult to develop appropriate fuzzy rules for Sugeno FIS. This paper proposes Evolution Strategy method to determine appropriate rules for Sugeno FIS that have minimum forecasting error. Root Mean Square Error (RMSE) is used to evaluate the goodness of the forecasting result. The numerical experiments show the effectiveness of the proposed optimized Sugeno FIS for several test-case problems. The optimized Sugeno FIS produce lower RMSE comparable to those achieved by other well-known method in the literature.
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.
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 Gumelar, Dito Ibrahim Hamles Leonardo Latupeirissa Hanafi, Muhammad Gusti Alif Zuhry Handono Kalim Hari Santoso Hari Santoso Hariyadi Soetedjo Harry Soekotjo Dachlan Herditomo Herditomo Hutasoit, Fania Putri Idmi, Mohammad Habibiy Ika Karlina Laila Nur Suciningtyas Ilham Ilham 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 Muhammad Aziz Muslim Muhammad Fadlil Khoironi Muhammad Fathur Rouf Hasan Muhardi Purwanto Purwanto Ridwan Awalin Rizky Benny Relado, Rizky Benny Setyawan Purnomo Sakti Sri Herwiningsih Sugeng Rianto Suhayat Minardi Sunaryo Sunaryo Umi Salamah Wayan Firdaus Mahmudy Yogie Susdyastama Putra Yudianto, Didik Yuyun Yueniwati