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All Journal JurTI (JURNAL TEKNOLOGI INFORMASI) ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Jurnal Sistem Informasi Kaputama (JSIK) EXPLORER Jurnal Minfo Polgan (JMP) Prosiding Snastikom Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Prioritas : Jurnal Pengabdian Kepada Masyarakat International Journal of Health, Engineering and Technology Jurnal Ilmu Komputer dan Sistem Informasi Router : Jurnal Teknik Informatika dan Terapan Router : Jurnal Teknik Informatika dan Terapan
Arnes Sembiring
Universitas Harapan Medan
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary

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Perancangan Sistem Keamanan Rumah Menggunakan Face Recognition (Pengenalan Wajah) Berbasis Raspberry Pi Adi Nugraha Batubara; Abdul Jabbar lubis; Arnes Sembiring
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 3 No. 3 (2024): September 2024
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v3i3.136

Abstract

Talking about technology, currently computer technology is developing very rapidly and is a field that has a very important role in several aspects of human life, including in the field of security. Currently, many home or room security systems have been developed with several identity verification methods using a computer system, using keys, cards, passwords, and so on. However, this method still has shortcomings such as humans' limitations in remembering number combinations which makes the door inaccessible. Therefore, techniques for reliable and accurate identification or verification can be designed using biometric technology that utilizes the special characteristics of the human individual.
Prediksi Tingkat Motivasi Belajar Siswa Menggunakan Metode Backpropagation Iga Putri Anjasari; Arnes Sembiring; Muamar Khadafi
Router : Jurnal Teknik Informatika dan Terapan Vol. 2 No. 3 (2024): September : Router : Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v2i3.261

Abstract

Motivation has an important role in the teaching and learning process for both teachers and students. For teachers, knowing students' learning motivation is very necessary. maintain and increase students' enthusiasm for learning. For students, learning motivation can foster enthusiasm for learning so that students are encouraged to carry out learning actions. Students carry out learning activities happily because they are driven by motivation. Currently, many students are less motivated to study. Backpropagation is a supervised learning algorithm and is usually used by perceptrons with many layers to change the weights connected to neurons in the hidden layer. Based on the learning rate and maximum epoch values, artificial neural networks using the backpropagation method can predict the level of student learning motivation with convergent results or the target error is achieved with an epoch of 11 iterations and a training process time (time) of 0.00.08 seconds. From the student learning motivation criteria data which is used as training data, the training targets can be identified. Yes and no input which is transformed into 0 and 1 can predict the level of student learning motivation with low, medium and high student motivation targets with reslt testing 80%.
Application Case Based Reasoning Method In Diagnosing Oil Palm Plant Diseases At PT Rapala, Gebang Sub-District Hafizah Husna; Hotler Manurung; Arnes Sembiring
International Journal of Health Engineering and Technology Vol. 3 No. 3 (2024): IJHET SEPTEMBER 2024
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (625.138 KB) | DOI: 10.55227/ijhet.v1i2.41

Abstract

In the last five years, the development of computers is very rapid. This can be seen from the number of computers owned by the community, with various sophistication and features and information systems that can spoil its users. One area of application that can be considered is the field of diagnosing oil palm plant diseases. Difficulties in diagnosing oil palm plant diseases at PT. RAPALA Kec. Gebang often occurs when you want to take preventive or curative action when an oil palm plant is attacked by a disease, because the old diagnostic system is due to limited experts so that the quality of operational performance is lacking. With the application of an expert system in diagnosing oil palm plant diseases, it is hoped that it will make it easier for field workers to diagnose oil palm plant diseases quickly without waiting for experts. This system is designed using PHP My Admin programming software and MySQL as database. The result of this study is the process of diagnosing diseases in oil palm plants using the Case Based Reasoning method where the design begins with entering symptom data, then the system calculates the diagnostic results according to the Case Based Reasoning method and displays it in the form of a report.
Expert System To Diagnose The Feasibility Of Drinking Water For Consumption Using Certainty Factor Method In Pdam Tirta Sari Kota Binjai Niko Ramot Saragi; Arnes Sembiring; Nurhayati
International Journal of Health Engineering and Technology Vol. 1 No. 2 (2022): IJHE-JULY 2022
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (676.835 KB) | DOI: 10.55227/ijhet.v1i2.29

Abstract

Drinking water is water that has been processed or without processing that meets health requirements and can be drunk directly. Meanwhile, to find out the water is fit for consumption or not. It is difficult to distinguish what causes errors that lead to problems that occur such as health problems. Such as metal content must be safe for consumption. It takes a system that can be used as an information provider to determine the quality of drinking water suitable for consumption which is managed by PDAM Tirta Sari, Binjai City. An expert system using the certainty factor method in diagnosing the feasibility of drinking water for consumption. Drinking water in determining whether or not water is feasible and helps provide valid information about the feasibility of drinking water for consumption to customers.
Design and Build an Automated School Bell System Using Voice-Based IoT Khairul Abdi Azizi; Arnes Sembiring; Mili Arfisyari
International Journal of Health Engineering and Technology Vol. 1 No. 3 (2022): IJHET-SEPTEMBER 2022
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (837.898 KB) | DOI: 10.55227/ijhet.v1i3.64

Abstract

A tool for Designing an Automated School Bell System Using Voice-Based IOT has been designed. The system of this tool uses a NodeMCU ESP8266 microcontroller where the NodeMCU ESP8266 functions as a data processor, and also a WI-FI network receiver emitted by a WI-FI network system. This tool system uses a control system using an android smartphone to turn on the school bell, namely the entrance bell, the recess bell, and the home bell, this tool uses a WI-FI network communication system so that the device system and android smartphone can be connected, the system of this tool uses the ISD1820 module as an output connected to the speaker and the speaker functions to emit the sound of the bell on the designed tool system. The smart phone application used in the design of this tool is the BLYNK application which can be downloaded on playstore or google.com It is hoped that this tool can help and make it easier for teachers who are on duty in turning on the school bell
Prediksi Tingkat Motivasi Belajar Siswa Menggunakan Metode Backpropagation Iga Putri Anjasari; Arnes Sembiring; Muamar Khadafi
Router : Jurnal Teknik Informatika dan Terapan Vol. 2 No. 3 (2024): September : Router : Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v2i3.261

Abstract

Motivation has an important role in the teaching and learning process for both teachers and students. For teachers, knowing students' learning motivation is very necessary. maintain and increase students' enthusiasm for learning. For students, learning motivation can foster enthusiasm for learning so that students are encouraged to carry out learning actions. Students carry out learning activities happily because they are driven by motivation. Currently, many students are less motivated to study. Backpropagation is a supervised learning algorithm and is usually used by perceptrons with many layers to change the weights connected to neurons in the hidden layer. Based on the learning rate and maximum epoch values, artificial neural networks using the backpropagation method can predict the level of student learning motivation with convergent results or the target error is achieved with an epoch of 11 iterations and a training process time (time) of 0.00.08 seconds. From the student learning motivation criteria data which is used as training data, the training targets can be identified. Yes and no input which is transformed into 0 and 1 can predict the level of student learning motivation with low, medium and high student motivation targets with reslt testing 80%.
Co-Authors Abdul Jabbar Lubis Adi Nugraha Batubara Ahmad Zakir Aidilvi Prya Pratama Azwar Angga Bagas Putra Sundana Budi Arisa Utomo Siregar Budi Santoso Budi Santoso Dian Novita Pardede Divi Handoko Evi Triana Hafizah Husna Haida Dafitri Harahap, Herlina Hasibuan, Ade Zulkarnain Hotler Manurung Iga Putri Anjasari Indra Indra Kalvin Chiuloto Khairul Abdi Azizi M. Rizky Pahlepy Lubis Mhd Ridho Wiratama Mili Arfisyari Muamar Khadafi Muhammad Imam Syahputra Muhammad Rizky Irwansyah Nadia Vathresia1 Niko Ramot Saragi Nizmaldy Astoro Witjati Nurhayati Rachmat Aulia Rahman, Sayuti Risko Liza Robby Darwis Siregar, Yunita Sari Sultan Shidqi Syafi Qurrahman Lubis Tengku Mhd Diansyah Ummul Khair Ummul Khair Yessi Fitri Annisah Lubis