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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 18 Documents
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Search results for , issue "2021, Vol. 3, No. 4" : 18 Documents clear
Algoritma K-Means Clustering dalam Mengklasifikasi Data Daerah Rawan Tindak Kriminalitas (Polres Kepulauan Mentawai) Yoni Aswan; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (558.183 KB) | DOI: 10.37034/jsisfotek.v3i4.73

Abstract

Crime is all kinds of actions and actions that are economically and psychologically harmful that violate the laws in force in the State of Indonesia as well as social and religious norms. Ordinary criminal acts affect the security of the community and threaten their inner and outer peace. The research location is the Mentawai Islands Police, which is an agency that can provide security and protection for the community, especially those in the Mentawai Islands Regency. The problem is that it is difficult for the Mentawai Islands Police to classify areas that are prone to crime in the most vulnerable, moderately vulnerable and not vulnerable categories. Especially considering the condition of the Mentawai, there are four large islands consisting of 10 sub-districts, where crime is increasing every year, especially those in the Mentawai Islands Regency area such as motor vehicle theft. Based on the background of the problem above, the researcher is interested in taking research in creating a system to predict the crime rate in the Mentawai Islands Regency in order to anticipate the surge in crime that will come. The method used is the K-Means Clustering Algorithm as a non-hierarchical data clustering method to partition existing data into one or more clusters or groups. This method partitions data into clusters so that data with the same characteristics are grouped into the same cluster and data with different characteristics are grouped into other clusters. Clustering is one of the data mining techniques used to get groups of objects that have common characteristics in large enough data. The data used is data on cases of criminal theft of motor vehicles for the last 5 years from 2016 to 2020. The results of the test show that South Sipora District is an area prone to the crime of motor vehicle theft.
Metode Forward Chaining dalam Menganalisis Penyakit Kucing Akibat Infeksi Virus Lova Endriani Zen; Gunadi Widi Nurcahyo; Y Yuhandri
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (348.175 KB) | DOI: 10.37034/jsisfotek.v3i4.74

Abstract

Cats are pets that are very popular today, their cute behavior and cute body shapes make people from all walks of life love them. We, especially those who like and keep cats, must pay attention to the cat's health condition, because it is possible that viral infections suffered by the cat can be contagious. At this time, the public does not have enough knowledge about education about cat diseases due to viral infections, resulting in cats being often late in getting treatment. This study aims to analyze cat diseases due to viral infections using the Forward Chaining method based on symptoms and to design an Expert System to measure the accuracy of analyzing cat diseases due to viral infections. The data needed in this study are cat data, symptom data and solution or treatment data needed to make decisions that are sourced from veterinarians from Paw's Vet Padang. Sourced form data analysis provided by the expert, the expert has a decision-making mode, which is to collect facts first to reach a conclusion or decision, so the Forward Chaining method can be used to conduct this research. The stages of data processing include preparing input data, expert decision tables, determining rules, conducting tracking processes, making decision trees and tracking results. The results obtained are successful in analyzing the symptoms and can determine diseases related to viral infectious diseases in cats so that solutions and initial steps can be determined for handling them. The results of trials conducted by comparing the data with the system that has been designed have a very good level of accuracy.
Sistem Pakar dalam Membandingkan Metode Forward Chaining dengan Certainty Factor untuk Mengidentifikasi Jenis Kulit Wajah Nadya Alinda Rahmi; Gunadi Widi Nurcahyo
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (390.146 KB) | DOI: 10.37034/jsisfotek.v3i4.75

Abstract

Skin is one piece of the body that has adaptable properties to shield the human body from natural effects. A great many people need facial skin that is tight and liberated from skin illnesses, particularly skin inflammation inclined skin. Next, everybody ought to do facial consideration and utilize a few fixings that are appropriate for facial skin, there are five kinds of ordinary skin, sleek skin, dry skin, blend skin and touchy skin. To inspect the kind of facial skin by contrasting the Forward Chaining and Certainty Factor procedures. This assessment utilizes 30 information acquired from interviews with subject matter experts. There are a few signs acquired from different issues distinguished on facial skin which are utilized as indication data for facial skin types constrained by subject matter experts. This data is utilized to check the sort of facial skin dependent on guidelines and data from a trained professional. The preliminary advances taken are to look at the Forward Chaining and Certainty Factor strategies. The outcomes acquired subsequent to testing and assessment of the Forward Chaining and Certainty Factor strategies were 83.33% and the discoveries expressed that the customer had a commonplace skin type. The test outcomes can be seen from the two strategies that test unequivocal facial skin types, then, at that point the principle system utilized not set in stone to help dermatologists in analyzing facial skin types.
Tingkat Formulasi Model Soal dalam Permutasi Acak Menggunakan Algoritma Fisher Yates Puji Chairu Sabila; Gunadi Widi Nurcahyo
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (255.389 KB) | DOI: 10.37034/jsisfotek.v3i4.76

Abstract

The problem model in random permutations results in random randomization of the most commonly used questions in exam practice in education ranging from elementary school to college level and even some agencies that utilize exams to test one's abilities. This Problem Model can produce a high random percentage with more complex processes compared to analogues. Conduct Model Formulations on infinite questions so that they can be easily utilized without complicated calculations. The problems processed in this study are from 50 questions, and 12 students are sourced from the Information System Study Program of STMIK Logika, at Medan Indonesia state. Based on the collection of the question by the head of the study program in charge of the STMIK. Furthermore, the problem is saved into the database. The next stage is to randomize the question based on the number of students taking the exam. The problem has been randomized into a model formulation of the question in a random permutation of the question at the time of the Test practice. The result of the test on this question is a matter of courses. Randomized questions can form a problem model in random permutations based on many questions, the number of questions. All questions are made by lecturers who teach courses and help the study program in the teaching and learning process with the formulation of the problem model.
Sistem Pakar dalam Menganalisis Penyakit Kelenjar Getah Bening Menggunakan Metode Certainty Factor Sri Layli Fajri; Gunadi Widi Nurcahyo
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (572.903 KB) | DOI: 10.37034/jsisfotek.v3i4.77

Abstract

In general, a person is difficult do dermine whether a lump or swelling of the lymph nodes in the body, is just a normal lump or whether it has become cancer. If the lumph does not go away whitin a few days, the patient is required to immediately consult a doctor to get detailed information about the disease and how to treat it. Lymph nodes scattered in the human body are round and are part of the lymphatic system that plays a role in fighting viruses that enter the body. The cause of these enlarged lymph nodes can be due to the type of food consumed, congenital disease in the patient’s body (comorbid), infection to lymph node cancer (lymphoma). For this reason, an Expert System is needed by applying the Certainty Factor method in order to assist the public in analyzing lymph node disease by answering several questions regarding the symptoms experienced. This system is implementad using the PHP programming language and MySQL database. The result of this study show that the Certainty Factor method can work well in the Expert System analysis process. From the result of system trials with several patient data, the disease accuracy rate in the patient named S is 63% and the disease accuracy rate in the patient named MR is 68%. Besides being useful for an expert, this Expert System can help patients to find out the type of disease they are suffering from, the accuracy of disease, the method of treatment and a guide for making decisions.
Identifikasi Tingkat Kerusakan Peralatan Labor Teknik Komputer Jaringan Menggunakan Metode Decision Tree Dinda Permata Sukma; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (527.183 KB) | DOI: 10.37034/jsisfotek.v3i4.78

Abstract

The computer laboratory is a place for practical learning for students, where computers have an important role in the smooth running of the practice. The use of computer labor at any time is very vulnerable to damage. If there is damage it will disrupt the teaching and learning process. Utilization of data mining in determining the level of damage is one of them. SMKN 1 Sintuk Toboh Gadang has 3 laboratories, TKJ (Network Computer Engineering), RPL (Software Engineering) and Technician labor. Application of the Decision Tree method in identifying damage to computer laboratory equipment, especially TKJ (Computer Network Engineering) labor. The data obtained in this study are computer equipment sourced from the computer laboratory of SMKN 1 Sintuk Toboh Gadang. Based on the analysis of the computer laboratory, there are 50 computer laboratory equipment. Furthermore, if the data is processed, several variables are needed to identify the level of damage to labor equipment including the name of the tool, number of tools, inspection, duration of use, and condition. The result of testing this method is to test whether the labor equipment can still be used or repaired. The purpose of this research is to help computer labor technicians to identify computer labor equipment that can still be used or repaired so that no damage occurs during practical learning hours. Furthermore, the best method in determining the level of damage to computer laboratory equipment is the Decision Tree Algorithm method. Decision Tree Algorithm is a predictive model using a decision tree structure and makes complex decisions simpler. The results of the research method show that the condition variable has the highest Gain value, namely 0.4734353, then the variable length of use is obtained with a Gain value of 0.896038. The factors that cause damage include the condition of the tool and the duration of use.
Simulasi dalam Optimalisasi Pengadaan Barang menggunakan Metode K-Mean Clustering Indah Savitri Hidayat; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (579.407 KB) | DOI: 10.37034/jsisfotek.v3i4.79

Abstract

Products provided by a store have an influence on store sales. Consumers will be attracted to stores that provide products according to their wants and needs. The purpose of this research is to find out what ornamental flower products are most in demand by consumers, in demand by consumers and less desirable to consumers. Keywords: inventory of goods, K-Mean Clustering, Data Mining, cluster, optimal. Store managers can get information about goods that have been depleted of inventory stock to be updated immediately. The method used in this study is the K-Mean Clustering method which belongs to one of the branches of Data Mining. The data used in the study is data from January 2020 to December 2020 as many as 100 pieces taken from naafilah official shop, Padang. The data variables used in the entry of goods are the year, product name, price and amount sold. Furthermore, the data is processed using Rapid Miner software. The first stage of processing is to determine the value of clusters randomly, in this study researchers divided the cluster values into 3 groups. Next, the centroid value of each group will be determined. Centroid is derived from the minimum value, middle value and maximum value of the data provided. Then, the cluster process is calculated using the euclidean distance formula. Cluster calculations are done by calculating the closest distance to the data. The final result of this study is to find out the best-selling, best-selling and less-selling ornamental flowers, so that sellers can optimize the provision of ornamental flowers for the future.
Prediksi Penerimaan Mahasiswa Baru Pascasarjana dengan Menggunakan Model Simulasi Monte Carlo Julia Nurmantika
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (290.17 KB) | DOI: 10.37034/jsisfotek.v3i4.126

Abstract

Institut Agama Islam Negeri (IAIN) Batusangkar merupakan salah satu Perguruan Tinggi Keagamaan Islam Negeri (PTKIN) yang ada di Sumatera Barat. PTKIN ini memiliki program studi Pascasarjan. Program ini sangat mengalami fluktuasi peminat yang selalu naik turun dan tidak merata pada setiap jurusan. Penelitian ini bertujuan memprediksi penerimaan mahasiswa baru program Pascasarjana pada tahun yang akan datang dengan menengunakan data-data pada tahun sebelumnya. Metode simulasi yang digunakan adalah Monte Carlo. Hasil penelitian ini dapat memprediksi penerimaan mahasiswa baru pada tahun yang akan datang dan mengetahui jurusan mana yang paling rendah peminatnya. Dimana pada tahun 2018 dengan data real jumlah mahasiswa adalah 108 orang, pada data simulasi tahun 2018 adalah 107 orang dengan presentase perbandingan 82.94%. Sedangkan untuk data real tahun 2019 adalah 114 orang sama dengan data simulasi tahun 2019 yaitu 114 orang, dengan presentase perbandingan 87.21%. Maka penelitian ini sangat tepat untuk memprediksi penerimaan mahasiswa baru pada Tahun yang akan datang.

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