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All Journal International Journal of Electrical and Computer Engineering TEKNIK INFORMATIKA Seminar Nasional Aplikasi Teknologi Informasi (SNATI) ELKHA : Jurnal Teknik Elektro Proceedings of KNASTIK TELKOMNIKA (Telecommunication Computing Electronics and Control) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Global Strategis Jurnal Teknologi dan Sistem Komputer Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Jurnal Penelitian Politik Conference SENATIK STT Adisutjipto Yogyakarta Jurnal Pertahanan : Media Informasi tentang Kajian dan Strategi Pertahanan yang Mengedepankan Identity, Nasionalism dan Integrity JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) KACANEGARA Jurnal Pengabdian pada Masyarakat MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Mnemonic Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat Abdimasku : Jurnal Pengabdian Masyarakat Aiti: Jurnal Teknologi Informasi Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Jurnal Pertahanan dan Bela Negara BHAKTI PERSADA Jurnal Aplikasi IPTEKS (Journal of Applied Sciences and Technology) ELPOSYS: Jurnal Sistem Kelistrikan Jurnal Elektrosista Jurnal Informatika Polinema (JIP) Jurnal TNI Angkatan Udara Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmiah Tenaga Listrik.
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Journal : TELKOMNIKA (Telecommunication Computing Electronics and Control)

Towards cognitive artificial intelligence device: an intelligent processor based on human thinking emulation Catherine Olivia Sereati; Arwin Datumaya Wahyudi Sumari; Trio Adiono; Adang Suwandi Ahmad
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 3: June 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i3.14835

Abstract

The intervention of computer technology began the era of a more intelligent and independent instrumentation system based on intelligent methods such as artificial neural networks, fuzzy logic, and genetic algorithm. On the other hand, processor with artificial cognitive ability has also been discovered in 2016. The architecture of the processor was designed based on knowledge growing system (KGS) algorithm, a new concept in artificial intelligence (AI) which is focused on the emulation of the process of the growing of knowledge in human brain after getting new information from human sensory organs. KGS is considered as the main method of a new perspective in AI called as cognitive artificial intelligence (CAI). The design is to obtain the architecture of the data path of the processor. We found that the complexity of the processor circuit is determined by the number of combinations of sensors and hypotheses as the main inputs to the processor. This paper addresses the development of an intelligence processor based on cognitive AI in order to realize an Intelligence Instrumentation System. The processor is implemented in field programmable gate array (FPGA) and able to perform human thinking emulation by using KGS algorithm.
Architecture design for a multi-sensor information fusion processor Catherine Olivia Sereati; Arwin Datumaya Wahyudi Sumari; Trio Adiono; Adang Suwandi Ahmad
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 1: February 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i1.10180

Abstract

This paper discusses the design of the architecture of an information fusion processor. This processor emulates the way of human thinking, namely by drawing conclusions from the obtained collection of information. Architecture design for this processor is based on Knowledge Growing System (KGS) algorithm. KGS is a novelty in Artificial Intelligence field. Compared to other AI methods, KGS focuses on the observation of the process of the knowledge growth within human brain based on information received from the surrounding environment. By using KGS algorithm, this processor works by receiving inputs from a set of sensors and possible hypotheses obtained after the processing of the information. The processor generates a value which is called as Degree of Certainty (DoC), which show the most possible hypothesis among all alternative ones. The Processor Elements which are used to perform KGS algorithm is designed based on systolic array architecture. The design of this processor is realized with VHSIC Hardware Design Language (VHDL) and synthesized by using FPGA Quartus II.13.1. The results show that the data path which has been design is able to perform the mechanism of KGS computation.
Cognitive artificial-intelligence for doernenburg dissolved gas analysis interpretation Karel Octavianus Bachri; Umar Khayam; Bambang Anggoro Soedjarno; Arwin Datumaya Wahyudi Sumari; Adang Suwandi Ahmad
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 1: February 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i1.11612

Abstract

This paper proposes Cognitive Artificial Intelligence (CAI) method for Dissolved Gas Analysis (DGA) interpretation adopting Doernenburg Ratio method. CAI works based on Knowledge Growing System (KGS) principle and is capable of growing its own knowledge. Data are collected from sensors, but they are not the information itself, and thus, data needs to be processed to extract information. Multiple information are then fused in order to obtain new information with Degree of Certainty (DoC). The new information is used to identify faults occurred at a single observation. The proposed method is tested using the previously published dataset and compared with Fuzzy Inference System (FIS) and Artificial Neural Network (ANN). Experiment shows CAI implementation on Doernenburg Ratio performs 115 out of 117 accurate identification, followed by Fuzzy Inference System 94.02% and ANN 78.6%. CAI works well even with small amount of data and does not require trainings.
Co-Authors A.I. Wuryandari A.S. Ahmad Aciek Ida Wuryandari Adang Suwandi Ahmad Adang Suwandi Ahmad Adang Suwandi Ahmad Addin, Tri Nur Ade Ismail Adhika Febrianto Adinandra, Dimas Eka Affandi, Luqman Afifah Millatina Nugraheni Agustian, Harliyus Alfian, Ahmad Alfian Alvi Rahmadhani Anggraini Kusumaningrum, Anggraini Annisa Puspa Kirana Annurroni, Ilyas Anton Setiawan Honggowibowo Ardhia Rahmania, Diva Arie Rachmad Syulistyo Arya Septiawan Astika AyuningTyas, Astika Aziza, Nadia Layra Bachri, Karel Octavianus Bambang Anggoro Soedjarno Bambang Gastomo Bayu Anugerah Rahardjo Putra Benedictus Mardwianta, Benedictus Bima Gilang Lesmana Brian Adam Bhagaskara Catherine Olivia Sereati Chika Labita David Putra Setyawan David Putra Setyawan, David Putra Denny Dermawan Dhebys Suryani Hormansyah, Dhebys Suryani Dimas Rossiawan Hendra Putra Dimas Rossiawan Hendra Putra Djapri, Suparman Dwi Nugraheny, Dwi Dwiguspana, Edwin Emy Setyaningsih Farchan Agil, Mochammad Farel Putra Hidayat Farida Agustini Widjajati Febrianto, Adhika Firman Munthaha Hadi, Arijo Haruno Sajati Haryo Budi Rahmadi Hijriana, Sukriya Indrazno Siradjuddin Jaka Sembiring Jaka Sembiring Khayam, Umar Lovrencic, Sandra Luluk Mufida M. Ardli Aqdama Mamluatul Hani’ah Maulana Zinedin Zidane Mawarni, Putri Indah Moch Zawaruddin Abdullah Mochammad Syaifuddin Zuhri Muhammad Auful Kirom Muhammad Bisri Musthafa Muhammad Bisri Musthofa Muhammad Ifan Fanani Muhammad Oktoda Noorrohman Mustika Mentari Nabilah Hanun Nafisah, Nihayatun Naily Ikmalul Insiyah Ngat Mari Ngatmari Nugraheni, Afifah Milatina Nugroho, Sutopo Purwo Nuryatno, Edi Triono Odhitya Desta Triswidrananta Odhitya Desta Triswidrananta Pamungkas, Dedi Bintang Partono, Rani Perdana, Fatiha Eros Pramitarini, Yushintia Pranata, Aldi Surya Prihantoro, Mitro Pujiastuti, Asih Purwoko, Agus Rahmad, Cahya Rahman, Alex Firmansyah Rahmawati, Fajar Khanif Ricky Yulian Adi Pratama Rindu Alriavindra Funny Rokhimatul Wakhidah Rudy Laksmono Widayatno Salam Aryanto Sarwono Sutikno Satwika, Satriya Dipa Semmy Tyar Armandha Septafiansyah Dwi Putra Septian Enggar Sukmana Setiawan, Paulus Siswanto, Sela Aulia SUDARYANTO SUDARYANTO Sulistio, Andhika Syahbana, Muhammad Rifky Syamsiana, Ika Noer Syamsuri, Tresna Umar Trio Adiono Wahyudi, Moh Ari Wintolo, Hero Yenni Astuti, Yenni Yoda, Vincensius Arga Yohana, Puspa Ayu Yohana Yoppy Yunhasnawa Yushintia Pramitarini Yusuf Kurniawan Zaenal Abidin Zidan Shabira As Sidiq