Jurnal Sistim Informasi dan Teknologi
Jurnal JSisfotek (Jurnal Sistem Informasi dan Teknologi) dimaksudkan sebagai media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai penelitian Rekayasa Sistem, Teknik Informatika/Teknologi Informasi, Manajemen Informatika dan Sistem Informasi. Sebagai bagian dari semangat menyebarluaskan ilmu pengetahuan hasil dari penelitian dan pemikiran untuk pengabdian pada Masyarakat luas dan sebagai sumber referensi akademisi di bidang Teknologi dan Informasi.
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72 Documents
<![CDATA[Akurasi Klasifikasi Pengguna terhadap Hotspot WiFi dengan Menggunakan Metode K-Nearest Neighbour ]]>
<![CDATA[Syaljumairi, Raemon]]>;
<![CDATA[Defit, Sarjon]]>;
<![CDATA[Sumijan, S]]>;
<![CDATA[Elda, Yusma]]>
<![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.v3i3.152
<![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[Kompetensi yang Optimal Terhadap Penilaian Kinerja Guru dengan Metode Simple Additive Weighting ]]>
<![CDATA[Alfarisdon, A]]>;
<![CDATA[Sumijan, S]]>;
<![CDATA[Nurcahyo, Gunadi Widi]]>
<![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.v3i3.154
<![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 93%. This study is expected to bring benefits for school leaders as the reference in order to optimize the teacher performance evaluation objectively.]]>
<![CDATA[Klasifikasi Kualitas Mutu Daun Gambir Ladang Rakyat Menggunakan Metode Convolutional Neural Network ]]>
<![CDATA[Winanda, Teddy]]>;
<![CDATA[Yunus, Yuhandri]]>;
<![CDATA[Hendrick, H]]>
<![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.v3i3.156
<![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[Prediksi Tingkat Kriminalitas Menggunakan Metode Single Moving Average (Studi Kasus Polres Asahan Sumatera Utara) ]]>
<![CDATA[Lubis, Mustopa Husein]]>;
<![CDATA[Sumijan, S]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4 (Accepted) ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i4.167
<![CDATA[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 endanger their lives and minds. The research location is the Asahan Police which is an agency that can provide security and protection for the community, especially those in Asahan Regency. The problem that occurs in this location is that there is no prediction system in Asahan Regency, due to the lack of knowledge factor in processing crime rate data. So it is difficult to know how much increase or decrease in criminal cases committed at the Asahan Police. The data used is data on cases of murder, sexual monitoring, tracing, violent theft, weight theft, motorcycle theft, fraud and counterfeiting money for the last 5 years in 2016 as many as 2020. Based on these problems, create a system for the crime rate in the Regency. Asahan to anticipate future crimes. The system that will be made uses forecasting or forecasting. With the Single Moving Average forecasting method. The Single Moving Average method is a forecast for the time in the future. The results of the calculation of criminal acts in 2021 found that there were 3 cases of murder, 2 cases of sexual intercourse in 2021, 252 cases of the 2021 return, 27 cases of violent theft in 2021, and 348 cases of bicycle theft in 2021. motorbikes in 2021 which open 90 cases, in 2021 which opens 85 cases, and money counterfeiting in 2021 which opens 1 case.]]>
<![CDATA[Perangkingan Potensi Guru dalam Penentuan Calon Kepala Sekolah Menggunakan Metode TOPSIS ]]>
<![CDATA[Wardana, Bendra]]>;
<![CDATA[Sumijan, S]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4 (Accepted) ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i4.168
<![CDATA[Efforts to increase the value of the quality of education for students as the next generation of the nation require teachers who have competence in providing education to students. The competence of a teacher can be assessed when a teacher has carried out his duties in accordance with the standard provisions he has. The ranking of potential teachers is used to motivate teachers to be active in carrying out each activity and is expected to have a positive effect on their work to face challenges in this era of globalization. The data that is processed for the ranking of teacher potential is the assessment data of elementary school teachers sourced from the korwildik of the Batang kapas sub-district. This ranking is based on several criteria and weights are determined. Furthermore, this ranking is processed using a system created by the researcher. This ranking uses a method called TOPSIS to assist researchers in ranking. The TOPSIS method is a multi-criteria decision support method with the principle that the chosen alternative must have the closest distance from the positive and negative ideal solutions. The results of ranking with the TOPSIS method are able to support the ranking decisions of potential teachers using predetermined criteria. So that the highest value is found in the 5th alternative with a value of 0.7321 and the lowest value is found in the 1st alternative with a value of 0.2218. The ranking of potential teachers has proven to be able to help the South Coast District Education and Culture Office, especially the korwildik of the Batang kapas sub-district in determining prospective school principals.]]>
<![CDATA[Identifikasi Penderita COVID-19 Berdasarkan Chest X-Ray Menggunakan Algoritma Jaringan Syaraf Tiruan Backpropagation ]]>
<![CDATA[Putra, Heru Rahmat Wibawa]]>;
<![CDATA[Yuhandri, Y]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4 (Accepted) ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i4.169
<![CDATA[Corona Virus Disease 2019 (COVID-19) is an infectious respiratory disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV2). This disease first appeared in Wuhan, China and spread throughout the world. COVID-19 has had a major impact on public health around the world. On March 9, 2020, the World Health Organization (WHO) declared COVID-19 a pandemic. Early identification of people with COVID-19 can help limit the wider spread. One of the factors behind the rapid spread of the disease is the long clinical trial time. Rapid clinical testing is a challenge facing the spread of COVID-19. Most countries, including Indonesia, face the problem of lack of detection equipment and experts in diagnosing this disease. Chest X-Ray is one of the medical imaging techniques and also an alternative to identify the symptoms of pneumonia caused by COVID-19. This study aims to identify pneumonia caused by COVID-19 and other diseases based on Chest X-Ray. 107 Chest X-Ray images used as material for this study were obtained from the General Hospital of Ibnu Sina Padang Indonesia, which consisted of 27 images of pneumonia caused by COVID-19, 51 images with other diseases and 29 images of normal lungs. Then pre-processing is carried out as an initial stage and then feature extraction is carried out. Furthermore, the learning and identification process is carried out using the Backpropagation Artificial Neural Network (ANN) algorithm. In this study, 92 images were used as training data, and 15 images were used as test data. The results of calculations carried out using a network with a pattern of 16-100-100-100-2 obtained an accuracy value of 73%. The results of the identification prediction can be used as consideration in establishing a diagnosis of COVID-19 sufferers, but cannot be used as an absolute reference.]]>
<![CDATA[Sistem Pakar dalam Menganalisis Defisiensi Nutrisi Tanaman Hidroponik Menggunakan Metode Certainty Factor ]]>
<![CDATA[Febrina, Yerri Kurnia]]>;
<![CDATA[Defit, Sarjon]]>;
<![CDATA[Nurcahyo, Gunadi Widi]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4 (Accepted) ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i4.170
<![CDATA[Saat ini sistem Pakar telah menjadi bidang penelitian bagi ilmuwan komputer juga ilmuwan pertanian untuk aplikasi dalam berbagai pengembangan informasi. Sistem Pakar dapat dirancang untuk mensimulasikan satu atau lebih dari cara seorang ahli pertanian menggunakan pengetahuan dan pengalamannya dalam membuat diagnosis dan meneruskan rekomendasi yang diperlukan terkait defisiensi nutrisi. Defesiensi nutrisi adalah kekurangan bahan makanan untuk kelangsungan hidup pada tanaman. Kandungan hara pada bagian tanaman, terutama didaun, sangat relevan digunakan untuk mengidentifikasi defisiensi nutrisi. Memberikan hasil diagnosis defisiensi nutrisi kepada petani untuk dapat menjadi patokan perbaikan hara tanaman serta pemberian nutrisi yang baik untuk tanaman hidroponik. Data yang digunakan adalah data defisiensi nutrisi dan gejala serta solusi pemberian nutrisi yang diperoleh dari data petani pada Dinas Pertanian Kota Payakumbuh. Metode yang dipakai dalam system pakar ini adalah metode Certainty Factor (CF). Metode ini memberikan diagnosis berupa kepastian atau ketidakpastian kondisi dalam rule yang digunakan untuk menyimpulkan. Hasil dari pengujian terhadap metode ini menunjukan sebanyak 12 defisiensi nutrisi yang terdeteksi dengan 41 gejala yang dialami. Sehingga dapat mengukur tingkat defisiensi nutrisi yang terjadi. Sistem Pakar dalam Menganalisis Defisiensi Nutrisi Tanaman Hidroponik Menggunakan Metode Certainty Factor dapat menunjukkan bahwa prediksi hamper 94% akurat.]]>
<![CDATA[Sistem Pakar Menggunakan Metode Certainty Factor dalam Menganalisis Penyakit Karies Gigi pada Manusia ]]>
<![CDATA[Andrean, Fajri Ilhami]]>;
<![CDATA[Yuhandri, Y]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4 (Accepted) ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i4.171
<![CDATA[Karies adalah penyakit gigi yang kerap ditemukan, yaitu suatu penyakit pada jaringan keras gigi berupa hilangnya ion – ion mineral secara terus menerus pada permukaan enamel gigi yang sebagian besar disebabkan oleh metabolisme bakteri. Tingkat kesadaran yang rendah dalam merawat gigi menyebabkan dampak buruk pada kesehatan gigi dan terhadap kesehatan tubuh. Pada saat sekarang ini umumnya masyarakat belum memiliki pengetahuan dalam menganalisis tentang penyakit karies gigi yang nantinya dapat mengakibatkan kerusakan yang parah terhadap gigi seperti matinya pulpa gigi. Penelitian ini bertujuan untuk menganalisis penyakit karies dengan menggunakan metode Certainty Factor. Dalam penelitian ini diolah data sebanyak 50 data yang diperoleh dari hasil wawancara dengan pakar pada Klinik Rahmatan Lil Alamin Padang Indonesia. Ditemukan beberapa faktor yang menyebabkan penyakit karies gigi pada manusia. Data tersebut diperoleh dari catatan medis pasien yang telah melakukan pemeriksaan di klinik. Data tersebut digunakan untuk menganalisis jenis penyakit karies berdasarkan bimbingan dari pakar tersebut. Tahapan pengolahan yang dilakukan adalah pemecahan rule, menentukan nilai bobot setiap gejala dan menghitung nilai Certainty Factor. Hasil yang didapatkan setelah dilakukan pengujian terhadap metode ini adalah terdapat 94% yang mengidap penyakit karies dengan jenis yang paling sering diderita pasien karies superfisialis. Hasil pengujian dapat menganalisis penyakit karies secara spesifik, dengan demikian sistem pakar yang digunakan telah dapat direkomendasikan untuk membantu dokter gigi menganalisis penyakit karies gigi pada manusia.]]>
<![CDATA[Optimalisasi dalam Penetrasi Testing Keamanan Website Menggunakan Teknik SQL Injection dan XSS ]]>
<![CDATA[Zikir Risky, Muhammad Arif]]>;
<![CDATA[Yuhandri, Y]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4 (Accepted) ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i4.172
<![CDATA[SQLI (SQL Injection) and XSS are hacking techniques that are often used by hackers. This technique can find out the contents of the database by inserting a script on the website. This technique can be a threat if a website does not have security that can ward off such attacks. Hackers will look for loopholes using this technique in a login menu, searching, upload menu, input menu and URLs that have parameters ending in numbers, but not all websites that can be attacked use this technique if you don't limit the use of characters. This research was conducted to find out the gaps in a website that can be attacked with SQLI and XSS techniques and help optimize website security to avoid these attacks. Penetration testing will be carried out on a CV car rental website. Merdeka Auto Rental which is located in Padang City. This penetration testing uses SQLI and XSS techniques to find security holes in a website. The result of this test is that on the car rental website there are 12 gaps that are vulnerable to SQLI and XSS attacks, based on the results of these tests, a PHP script function is made that can remove all dangerous special characters. The script function is inserted in the PHP input, process and output files. The use of this script function does not apply to attacks other than SQLI and XSS so that if hackers use attack techniques other than that, this website is vulnerable to these attacks. After the script is inserted in the source code of the website, it can be concluded that the 12 known loopholes in the previous test without using the script function have changed status to not vuln or not vulnerable to SQLI and XSS attacks.]]>
<![CDATA[Sistem Pakar dalam Mengidentifikasi Gejala Stroke Menggunakan Metode Naive Bayes ]]>
<![CDATA[Karim, Fajri]]>;
<![CDATA[Nurcahyo, Gunadi Widi]]>;
<![CDATA[Sumijan, S]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4 (Accepted) ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i4.173
<![CDATA[Stroke is a disease caused by brain damage caused by disruption of the blood supply to the brain. At this time in general, people are still not very familiar with how this stroke disease or do not realize the symptoms that may have appeared from the start. People also tend to be hesitant to visit the hospital to check their symptoms and feel they are delaying further examinations. This is certainly a scourge that continues to make the number of strokes increase. In assisting the community in identifying stroke disease, an expert system is needed that is able to identify the type of stroke based on the symptoms felt. The data used in this study were obtained from Brain Hospital. Dr. Drs. M. Hatta Bukittinggi which was later developed into a website-based system using the PHP Framework Laravel programming language and MySQL as the database. The system is built based on the Naive Bayes method which is one of the Expert System methods that has a high accuracy value. The use of this system is expected to be able to provide knowledge to the public about the symptoms that might lead to what type of stroke the user might suffer, so that the user can use the results of the system as a reference to visit the hospital and immediately get more targeted help. This system can perform calculations that match the results of the doctor's diagnosis with an accuracy value of 100% in identifying the type of stroke from 10 data samples used.]]>
