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INDONESIA
Jurnal Sistim Informasi dan Teknologi
Published by Asia Pacific Network for Sustainable Agriculture, Food and Energy
ISSN : 26863154     EISSN : 26863154     DOI : 10.37034
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
The Jurnal Sistim Informasi dan Teknologi (JSISFOTEK) aims to publish manuscripts that explore information systems and technology research and thus develop computer information systems globally. We encourage manuscripts that cover the following topic areas: - Analytics, Business Intelligence, and Decision Support Systems in Computer Information Systems - Mobile Technology, Mobile Applications - Human-Computer Interaction - Information and/or Technology Management, Organizational Behavior & Culture - Data Management, Data Mining, Database Design and Development - E-Commerce Technology and Issues in computer information systems - Computer systems enterprise architecture, enterprise resource planning - Ethical and Legal Issues of IT - Health Informatics - Information Assurance and Security-Cyber Security, Cyber Forensics - IT Project Management - Knowledge Management in computer information systems - Networks and/or Telecommunications - Systems Analysis, Design, and/or Implementation - Web Programming and Development - Curriculum Issues, Instructional Issues, Capstone Courses, Specialized Curriculum Accreditation - E-Learning Technologies, Analytics, Future.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
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Search results for , issue "2020, Vol. 2, No. 1" : 5 Documents clear
Identifikasi Karakteristik Anak Berkebutuhan Khusus Menggunakan Metode Case Based Reasoning Septiana Vratiwi; Y Yuhandri; Gunadi Widi Nurcahyo
Jurnal Sistim Informasi dan Teknologi 2020, Vol. 2, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (360.697 KB) | DOI: 10.37034/jsisfotek.v2i1.14

Abstract

Children with special needs are children who have different characteristics and limitations in ability. This child with special needs is called Tunagrahita. Developmental impairment is classified into three categories namely mild, moderate and severe. This study aims to help the process of identifying the characteristics of mental retardation experienced by children. This study uses the Case Based Reasoning (CBR) method to identify children with special needs using the data of the mentally disabled children in SLBN 1 Linggo Sari Baganti. Similarity results were 51.92% for moderate developmental impairment, 17.5% for mild developmental impairment and 8% for severe developmental impairment. Calculations are performed using Visual Basic Net 2010.
Akurasi Keputusan dalam Penentuan Guru Berprestasi dengan Menggunakan Metode Simple Additive Weighting W Wahyudi; Julius Santony; Gunadi Widi Nurcahyo
Jurnal Sistim Informasi dan Teknologi 2020, Vol. 2, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (495.187 KB) | DOI: 10.37034/jsisfotek.v2i1.15

Abstract

This study aims to obtain decision accuracy in determining teacher achievement using the Simple Additive Weighting method. Problems in Batam Muhammadiyah Vocational High School in determining the achievement of teachers using assessment criteria with the weight of educational qualifications, discipline, neatness, character, personality and teaching methods. The ranking process stage determines the alternatives of selected teacher achievement using the input of criteria weights. The results of this study get an accuracy rate of 80% with an accurate, fast, objective value. In the future, this research will be used as a new standard in determining teacher achievement.
Sistem Pakar dalam Mengidentifikasi Penyakit Kandungan Menggunakan Metode Forward Chaining Berbasis Android Adi Gunawan; Sarjon Defit; S Sumijan
Jurnal Sistim Informasi dan Teknologi 2020, Vol. 2, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (662.096 KB) | DOI: 10.37034/jsisfotek.v2i1.16

Abstract

Maternal Mortality Rate (MMR) in Indonesia is very high, so that maternal health problems are a national problem. This problem needs to get top priority. The health of pregnant women is crucial for the growth of the fetus they contain. Pregnancy can cause a decrease in maternal resistance. This decrease will trigger the arrival of various diseases. For that we need a system that can identify uterine diseases quickly and accurately. This study aims to identify uterine diseases in pregnant women based on symptoms experienced. This identification is the initial information that is useful to support the decision to take preventative action. Data processed in this study were 20 patients. This data is sourced from the Sungai Melati City Clinic which goes to an obstetrician, Dr. Yandi Zulkarnaen, SpOG. The method used in processing data is Android-based Forward Chaining. The results of this study include the name of the disease, description of the disease, and treatment solutions. After testing and calculating the level of system accuracy, a good degree of accuracy is obtained from the system calculation results with an expert decision of 90% of the 20 test data. Based on the level of accuracy, the expert system is very precise in identifying uterine diseases quickly.
Klasterisasi Tingkat Kehadiran Dosen Menggunakan Algoritma K-Means Clustering Ismail Virgo; Sarjon Defit; Y Yuhandri
Jurnal Sistim Informasi dan Teknologi 2020, Vol. 2, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (535.364 KB) | DOI: 10.37034/jsisfotek.v2i1.17

Abstract

Non-Civil Servant Lecturers of Batusangkar State Islamic Institute (IAIN) are still manual in recording the presence of non-civil servant lecturers. This study aims to use an application to record the number of meetings conducted during the teaching and learning process by non civil servant lecturers who are able to study courses. The meeting data will be an assessment of the performance of non civil servant lecturers. Higher education quality assurance institutions can classify non-civil servant lecturer meeting data using Knowledge Discovery in Database (KDD). The next stage is to do data mining with the K-Means Clustering Algorithm. The results of this study grouping lecturers into 3 groups: 72 subjects taught by non-civil servant lecturers in the group rarely meet (4,7650%), 69 courses that are taught by non-civil servant lecturers in the group are in meetings (4,5665%), and 1370 subjects taught by lecturers non civil servants in the diligent group meeting (90.6684%). Based on the results of the study it was concluded that the academic year 2017/2018 odd semester and even non-civil servant lecturers supporting certain subjects diligently entered at each meeting with attendance rates of 12-16 times meetings per semester
Analisis Tingkat Kejahatan pada Anak Dibawah Umur Menggunakan Metode FP-Growth Angga Putra Juledi; Sarjon Defit; Y Yuhandri
Jurnal Sistim Informasi dan Teknologi 2020, Vol. 2, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (413.793 KB) | DOI: 10.37034/jsisfotek.v2i1.18

Abstract

Crimes in minors are a series of negligence by parents who endanger or pose a dangerous threat to the child. The purpose of this study is to implement Data Mining, Association rule, and the FP-Growth Algorithm in cases of juvenile crime so that it can extract knowledge and important and interesting information from the database. The data source used is raw data that has not been processed and is a crime data on minors which are summarized in the form of reports from the West Sumatra Regional Police. The results of this study are in the form of software by analyzing data collected using the FP-Growth Algorithm and using the concept of FP-Tree development in searching for Frequent Itemset, for testing the results carried out with applications that have been designed namely the Php programming language. The results of testing are obtained from associations of crime cases that often occur in minors. So it can be seen that data mining using the FP-Growth Algorithm can be used to analyze cases of crime in minors as a material consideration for the police in order to know the ins and outs of crime in children so that it can assist the investigation process.

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