Jurnal Sistim Informasi dan Teknologi
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.
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216 Documents
<![CDATA[Klasifikasi Kualitas Mutu Daun Gambir Ladang Rakyat Menggunakan Metode Convolutional Neural Network ]]>
<![CDATA[Teddy Winanda]]>;
<![CDATA[Y Yuhandri]]>;
<![CDATA[H Hendrick]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3 ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i3.51
<![CDATA[Indonesia is one of the countries which have the best Gambier quality in the world. Those are a few areas in Indonesia which have best gambier quality such as Aceh, Riau, North Sumatera, Bengkulu, South Sumatera and West Sumatra. Kabupaten 50 Kota is one of the regencies in west Sumatra that supplies gambier in Indonesia. The gambier leaf selection is mostly done by manual inspection or conventional method. The leaf color, thickness and structure are the important parameters in selecting gambier leaf quality. Farmers usually classify the quality of gambier leaves into good and bad. Computer Vision can help farmers to classify gambier leaves automatically. To realize this proposed method, gambier leaves are collected to create a dataset for training and testing processes. The gambier image leaves is captured by using DLSR camera at Kabupaten 50 Koto manually. 60 images were collected in this research which separated into 30 images with good and 30 images with bad quality. Furthermore, the gambier leaves image is processed by using digital image processing and coded by using python programming language. Both TensorFlow and Keras were implemented as frameworks in this research. To get a faster processing time, Ubuntu 18.04 Linux is selected as an operating system. Convolutional Neural Network (CNN) is the basis of image classification and object detection. In this research, the miniVGGNet architecture was used to perform the model creation. A quantity of dataset images was increased by applying data augmentation methods. The result of image augmentation for good quality gambier produced 3000 images. The same method was applied to poor quality images, the same results were obtained as many as 3000 images, with a total of 6000 images. The classification of gambier leaves produced by the Convolutional Neural Network method using miniVGGNet architecture obtained an accuracy rate of 0.979 or 98%. This method can be used to classify the quality of Gambier leaves very well.]]>
<![CDATA[Tingkat Korelasi Prestasi Akademik Terhadap Siswa SMP Menggunakan Metode Backpropagation ]]>
<![CDATA[Nasma Yeni]]>;
<![CDATA[Y Yuhandri]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3 ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i3.52
<![CDATA[Student academic achievement plays a very important role in determining the quality of a school. Student grades sometimes change every semester, there are increases and decreases. There is an assumption that students whose grades are in the previous semester will be in the next semester and vice versa. is expected to make it easier for us as educators to see the extent to which changes in student academic achievement. The data tested is the data of 60 class VII students in 2 semesters. Furthermore, it will be tested using the MatLab Application, then the results of the changes that occur will come out. The results of this study found that they did not know the value of semester 1 with the value of semester 2 TP. 2019/2020 is very good with an architectural pattern of 10-10-1 with a value of 95.3%. So students who excel in semester 1 are likely to excel in the following semester. So that it can help the school in seeing the Correlation Level of Student Academic Achievement at SMPN 3 Lengayang.]]>
<![CDATA[Identifikasi dalam Penetapan Staf Dosen dan Karyawan Berprestasi dengan Menggunakan Metode SMART ]]>
<![CDATA[Nur Azizah]]>;
<![CDATA[Gunadi Widi Nurcahyo]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3 ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i3.53
<![CDATA[STMIK Indonesia Padang annually selects the best lecturers and employees to give appreciation for the performance of lecturers and employees. Lecturers and employees who take the assessment to appreciate the Performance Appraisal must meet the requirements and participate in the assessment process. The purpose of this research is to identify in determining the staff of lecturers and staff with achievement who are shorter in terms of calculations and also in accordance with the criteria. The sample in this study consisted of 4 lecturer data and 3 employee data taken randomly from 36 lecturer data and 26 employee data sourced from LP3M STMIK Indonesia Padang. Based on the analysis of lecturer and employee data, several criteria were obtained for processing these criteria, namely for lecturers the suitability of teaching materials with RPS (K) (Q1) teaching materials (Q2), teaching time (Q3), research (Q4) and GPA (Q5). ) then for employees, namely attendance (R1), performance (R2) and loyalty (R3). The method in this research is SMART (Simple Multi - Attribute Rating Technique) because this method is able to solve problems with multi-criteria. The results of the data testing obtained were Lecturers with achievements, namely DHD lecturers with a value of 0.8521 and outstanding employees, namely ARD employees with a value of 0.9998. The results of this study are expected to provide solutions for the identification of outstanding lecturers and staff at STMIK Indonesia Padang based on predetermined criteria.]]>
<![CDATA[Prediksi Hasil Belajar Siswa Secara Daring pada Masa Pandemi COVID-19 Menggunakan Metode C4.5 ]]>
<![CDATA[Yetti Fitriani]]>;
<![CDATA[Sarjon Defit]]>;
<![CDATA[Gunadi Widi Nurcahyo]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3 ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i3.54
<![CDATA[Student learning in schools has changed since the Covid-19 pandemic. Student learning in normal conditions is carried out face-to-face and turns into online or online learning. The research was conducted to predict student learning outcomes during the COVID-19 pandemic so that the results of this study can be used as a reference in policymaking in schools. The C4.5 method was used in the study to classify the data for class XII of the Multimedia Department at SMKN 2 Padang Panjang and the classification results could predict student learning outcomes during the pandemic. Processed student value data were taken from 1 (one) subject as the research data sample. Analysis of the value of student learning outcomes using the C4.5 Method to obtain new knowledge from student learning outcomes data carried out during the COVID-19 pandemic. The data analyzed consisted of attributes of attendance, assignments, daily tests, and test scores which influenced the decision criteria for student learning outcomes in online learning. The learning outcome decision criteria consist of "Satisfactory" and "Not Satisfactory" which refer to the Minimum Completion Criteria. Tests conducted on the training data of learning outcomes show that the value of the Daily Test is the most influential attribute in decision making. Implementation of the results using the RapidMiner Studio 9.2.0 software and produces an accuracy of 83.33% of the test data testing with the rules of data analysis training results. The results of the C4.5 classification testing method in this study can be used to predict student learning outcomes. The test results with an accuracy of 83.33% can be recommended to help schools in making policies]]>
<![CDATA[Akurasi Klasifikasi Pengguna terhadap Hotspot WiFi dengan Menggunakan Metode K-Nearest Neighbour ]]>
<![CDATA[Raemon Syaljumairi]]>;
<![CDATA[Sarjon Defit]]>;
<![CDATA[S Sumijan]]>;
<![CDATA[Yusma Elda]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3 ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i3.55
<![CDATA[The Current wireless technology is used to find out where the user is in the room. Utilization of WiFi strength signal from the Access Point (AP) can provide information on the user position in a room. Alternative determination of the user's position in the room using WiFi Receive Signal Strength (RSS). This research was conducted by comparing the distance between users to 2 or more APs using the euclidean distance technique. The Euclidean distance technique is used as a distance calculator where there are two points in a 3-dimensional plane or space by measuring the length of the segment connecting two points. This technique is best for representing the distance between the users and the AP. The collection of RSS data uses the Fingerprinting technique. The RSS data was collected from 20 APs detected using the wifi analyzer application, from the results of the scanning, 709 RSS data were obtained. The RSS value is used as training data. K-Nearest Neighbor (K-NN) uses the Neighborhood Classification as the predictive value of the new test data so that K-NN can classify the closest distance from the new test data to the value of the existing training data. Based on the test results obtained an accuracy rate of 95% with K is 3. Based on the results of research that has been done that using the K-NN method obtained excellent results, with the highest accuracy rate of 95% with a minimum error value of 5%.]]>
<![CDATA[Sistem Pendukung Keputusan bagi Penerima Bantuan Komite Sekolah Menggunakan Metode Topsis ]]>
<![CDATA[Suci Mardayatmi]]>;
<![CDATA[Sarjon Defit]]>;
<![CDATA[Gunadi Widi Nurcahyo]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3 ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i3.56
<![CDATA[Vocational High School Number 3 Mukomuko was the school that has given assistance for the learners. It was by exempting learners from paying committee charge monthly, it called Bantuan Komite Sekolah (BKS). In order to give motivation for the learners who was unfortunate to keep staying at the school, so it can make the learners to keep going on teaching and learning process (KBM). This research used Topsis method by collecting data for the prospective scholarship learners as many as 20 learners by categorizes were parents’ revenue, the total numbers of duties, the distance of residence, the average score of report and the condition of living environment. The result of try out from 20 learners who was obtain BKS by using Topsis Method showed that there were 18 learners who were significant to obtain scholarship by validity score was 90%. It was be a sample, before Topsis Method was used and the data was reliable after using Topsis Method. The development of supporting decision application system used Topsis Method that was getting in more accurated qualification. Futhermore, this system can help the school in constructing decisions to get the result be more advantageous in determining for the next BKS recipients.]]>
<![CDATA[Optimalisasi Penentuan Kriteria Penerima Bantuan Program Indonesia Pintar dengan Metode TOPSIS ]]>
<![CDATA[Dina Ayudia]]>;
<![CDATA[Gunadi Widi Nurcahyo]]>;
<![CDATA[S Sumijan]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3 ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i3.57
<![CDATA[The distribution of scholarships is carried out to assist in the determination of recommending someone who deserves to receive a scholarship, a Decision Support System is needed because the system for selecting scholarship candidates is still manual, and has many weaknesses. The large number of scholarship participant applicants makes schools having difficulty handling manual data processing so that software is needed to simplify the data processing. There for not all students who apply to receive scholarships can be granted, because the number of students who apply is very large, it is very necessary to build an SPK with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method which can help provide recommendation for scholarship recipients. Based on the analysis of the DSS with the TOPSIS method, it was carried out by means of a questionnaire, interview observation and system implementation. In the assessment of scholarship acceptance, it can be used as a basis for facilitating decisions on scholarship recipients because the system will process data and provide information quickly, precisely and consistently to the principal of students to receive the best scholarships to be awarded. Can form a decision that is right, effective and efficient in managing data on student recipients who are truly entitled to receive the scholarship. The TOPSIS method can be used to determine scholarship recipients, SPK in the assessment of scholarship acceptance can facilitate decisions in grade 7 students of SMP Negeri 17 Padang proportionally based on the results of student data processing including family cards, parents 'jobs, parents' income, number of dependents of parents and age parents accurately and accurately because the system can minimize errors in the process of calculating data normalization.]]>
<![CDATA[Tingkat Kepuasan Pasien RSIA Siti Hawa dalam Upaya Peningkatan Kualitas Pelayanan Menggunakan Metode Service Quality (SERVQUAL) ]]>
<![CDATA[Rika Apriani]]>;
<![CDATA[Gunadi Widi Nurcahyo]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3 ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i3.58
<![CDATA[Patient satisfaction is an important indicator in improving the quality of the hospital. RSIA Siti Hawa always tries to improve the quality of the hospital in order to provide excellent service to patients. One of the efforts made to improve the quality of the hospital is by knowing the level of patient satisfaction. The purpose of this study was to determine the extent of patient satisfaction with the Siti Hawa Hospital service so that it can assist management in evaluating and improving services to improve quality. This research was conducted using the Service Quality (SERVQUAL) method which has five dimensions, namely tangible (physical evidence), reliability (reliability), responsiveness (responsiveness), assurance (assurance) and empathy (empathy). This measurement is carried out to identify the patient's expectations and perceptions so that from the five dimensions of Service Quality, the overall service quality can be seen by looking at the value of the gap that occurs due to the mismatch between patient expectations and perceptions. The data processed in this study were questionnaire data from 30 respondents / patient. The result of this test is that the service quality of the five dimensions of service quality consisting of 14 question attributes has a positive gap value. The highest gap value is 0.47 in the 12th question attribute regarding politeness and friendliness of officers in providing services, and the lowest gap value is in the 6th attribute with a value of 0.27 regarding the timeliness of service schedules. Based on the dimensions, the order of the rank dimensions from the highest is empathy, assurance, responsiveness, tangible and reliability. Based on the results of this study, it can be concluded that the services provided by RSIA Siti Hawa to patients can be said to be good, and the results of these measurements can be used as an evaluation in improving the quality of hospital services.]]>
<![CDATA[Kompetensi yang Optimal Terhadap Penilaian Kinerja Guru dengan Metode Simple Additive Weighting ]]>
<![CDATA[A Alfarisdon]]>;
<![CDATA[Gunadi Widi Nurcahyo]]>;
<![CDATA[S Sumijan]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3 ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i3.59
<![CDATA[Professional teachers should be able to improve their quality to achieve the vision and mission of the school where the teacher is carrying out their duty. The main task of an educator is to provide students with the process of learning, educating, training and giving directions to create a better learning process. Besides carrying out the task of teaching, an educator also needs to be able to develop themselves sustainably in order to increase self-competencies. There are four competencies should be owned by an educator they are pedagogic, personality, social and professional. To measure those competencies, school head master have to conduct teacher assessment by pointed assessors. Teacher performance assessment functions to analyses teachers ' professionalism in learning processes at a school, teachers participation on self-empowerment activities as well as capacity building. This study aims to calculate the value of teacher performance assessment optimally based on competence through a decision support system. Simple Additive Weighting method is used in this decision support system. By using Simple additive weighting, the sum of weight ratings performance on each alternative in all the attributes can be collected. This decision support system used to make it easier to take a decision and a supporter of decision in performance evaluations. Dataset treat in this research was collected in SMP Negeri 25 Padang. The data consisting of four different criteria in accordance with teacher competence. The result of the study reaches the level of accuracy of 100 %.This study is expected to bring benefits for school leaders as the reference in order to optimize the teacher performance evaluation objectively.]]>
<![CDATA[Klasterisasi Tingkat Masa Studi Tepat Waktu Mahasiswa Menggunakan Algoritma K-Medoids ]]>
<![CDATA[Fahmi Firzada]]>;
<![CDATA[Y Yuhandri]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3 ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i3.60
<![CDATA[The period of study on time is one of the parameters of a student's success in completing college to obtain a bachelor's degree. A student is said to have completed his studies on time if he is able to complete his studies less than or equal to the predetermined time. Academic Provides facilities to find out the estimated time of student graduation. By providing information on which students are included in the cluster, they can complete their studies on time and which students do not complete their studies on time. In this study, the data processed were data from students who had graduated in the previous year. Then the data is processed using rapidminer software. This study applies the K-Medoids algorithm in clustering. The result of testing this method is to determine the student clusters who can complete the study period on time and the student clusters who cannot complete the study period on time. This research is expected to contribute to the campus in evaluating the tendency of students to complete their studies on time or not. The results of the evaluation of performance can produce information for study programs, lecturers and students in making policies.]]>
