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All Journal Sebatik JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) J-SAKTI (Jurnal Sains Komputer dan Informatika) Aptisi Transactions on Technopreneurship (ATT) TEPIAN J-SAKTI (Jurnal Sains Komputer dan Informatika) Informatika Wicida BEduManageRs Journal : Borneo Educational Management and Research Journal
Heny Pratiwi
Teknik Informatika, STMIK Widya Cipta Dharma
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Social Sciences Other

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Journal : J-SAKTI%20(Jurnal%20Sains%20Komputer%20dan%20Informatika)

 1 
Perbandingan Algoritma ELM Dan Backpropagation Terhadap Prestasi Akademik Mahasiswa Heny Pratiwi; Kusno Harianto
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 3, No 2 (2019): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (551.042 KB) | DOI: 10.30645/j-sakti.v3i2.147

Abstract

Extreme Learning Machine and Backpropagation Algorithms are used in this study to find out which algorithm is most suitable for knowing student academic achievement. The data about students are explored to get a pattern so that the characteristics of new students can be known every year. The evaluation process of this study uses confusion matrix for the introduction of correctly recognized data and unknown data. Comparison of this algorithm uses student data at the beginning of the lecture as early detection of students who have problems with academics to be anticipated. The variables used are the value of the entrance examination for new students, the first grade IP value, Gender, and Working Status, while the output variable is the quality value as a classification of academic performance. The results of this study state that the Extreme Learning Machine algorithm has a 14.84% error rate lower than Backpropagation 28.20%. From the model testing stage, the most accurate result is the Extreme Learning Machine algorithm because it has the highest accuracy and the lowest error rate.
Sistem Monitoring Lulusan Perguruan Tinggi Dalam Memasuki Dunia Kerja Menggunakan Tracer Study Kusno Harianto; Heny Pratiwi; Yonatan Suhariyadi
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 3, No 2 (2019): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v3i2.148

Abstract

This research is titled Monitoring System of Higher Education Graduates in Entering the World of Work Using Tracer Study. The problem raised in this study is that the BKK (Bursa Kerja Khusus) STMIK Widya Cipta Dharma Samarinda get information about the performance of STMIK graduate students Widya Cipta Dharma, analyze graduate data to obtain the relevance of the competency of STMIK graduates Widya Cipta Dharma Samarinda, change the old system into a system that new. The purpose of this research is to provide information and reports on the results of tracer study data collection from alumni of STMIK Widya Cipta Dharma Samarinda. Data collection methods used are literature study, field studies. The system development method used is the waterfall method. Informatic System of Alumnus Record Tracer Study Based Website of STMIK Widya Cipta Dharma Samarinda is a computer-based system that was built with the aim of processing the alumnus search to find out the description of the profile, performance, and distribution of work location of the alumnus. Informatic System of Alumnus Record Tracer Study Based Website of STMIK Widya Cipta Dharma Samarinda is expected to help assist the BKK (Bursa Kerja Khusus) in recording alumnus and record the track record of alumnus scattered in serveral areas.
Membangun Game Edutainment “Pengenalan Komputer” Menggunakan Shuffle Random (SR) Dan Finite State Machine (FSM) Untuk Anak Tunagrahita Ringan Heny Pratiwi; Ita Arfyanti; M Za’iem Sururi
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 3, No 2 (2019): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v3i2.149

Abstract

Research to build an Edutainment Game "Introduction to Computers" for mild retarded children is a study designed for teachers to deliver material to special school students (SLB) with special needs such as children with visual impairment, hearing impairment, mental retardation, intellectual disability, autism and blindness. . In this game the player will be presented with a variety of learning menus about "Computer Devices" and a game menu consisting of a guessing picture quiz to train memory, then there are typing games and labyrinth games to develop motor movements and increase students' responses and interests. Shuffle and Finite State Machine randomization algorithms will be applied in this study, with the aim of arranging the image position to be randomized in the learning menu and typing games as well as randomizing the position of the main characters and enemies in the labyrinth game made in three levels. This is done to improve students' learning and curiosity. The technology applied in this research is intelligent agent (intelligent system) which has a game agent character that will accompany children to learn and play.
Co-Authors Ahmad Abul Khair Ahmad Rofiq Hakim Amelia Yusnita Arsita Ashari Ramadani Azahari Dana Aulia Rahman Dendy Kurniawan Dessy Purnamasari Ekawati, Hanifah Harianto, Kusno Ita Arfyanti M Yuditia Arfiyanto T Nassa M Za’iem Sururi M. Irwan Ukkas Irwan Ukkas Ukkas Muhammad Fachri Sanjaya Muhammad Ibnu Saad Saad Muhammad Rega Praduana Nursobah, Nursobah Pahrudin, Pajar Pitrasacha Adytia Putri Wulandari Salmon Shinta Palupi Susi Salviati Syamsuddin Mallala Yonatan Suhariyadi