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TeknoIS : Jurnal Ilmiah Teknologi Informasi dan Sains
Published by Sekolah Tinggi Ilmu Komputer Binaniaga
ISSN : 20873891     EISSN : 25978918     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Engineering
TEKNOIS : Jurnal Ilmiah Teknologi - Informasi & Sains Publish by the STIKOM Binaniaga. TeknoIS published twice a year, in May and November. TeknoIS includes Research in the field of Information Technology, Information System, Computer Science and Other. Editors invite research lecturers the reviewer, practitioners industry, and observers to contribute to this journal.
Arjuna Subject : -
Articles 14 Documents
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Search results for , issue "Vol 13, No 1 (2023)" : 14 Documents clear
Pemodelan Aplikasi Pemesanan E-Tiket pendakian Gunung Berbasis Android Agus Suwarno; Edora Edora; Rifki Hamimi
TeknoIS : Jurnal Ilmiah Teknologi Informasi dan Sains Vol 13, No 1 (2023)
Publisher : Universitas Binaniaga Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36350/jbs.v13i1.188

Abstract

Ordering climbing tickets, which are getting more and more, requires a system to make it easier for climbers. Climbing activities are a hobby for climbers who like nature activities. Evidenced by the increasing number of enthusiasts of climbing activities today, booking climbing tickets is an important problem. Some climbers are willing to queue for 30 minutes and they even have to be willing to spend the night at the ticket reservation to get a climbing ticket. The solution to overcome this problem is to make an online ticket booking application. The method used in designing this application is the waterfall method. This design is made with an Android-based program so that it can be accessed anytime and anywhere. Purchasing tickets is easier because the ordering system is online. Hikers can easily see information about climbing so that it is more efficient.
Penerapan Algoritma C4.5 Untuk Rekomendasi Mentor Santri Baru Adiat Pariddudin; Fajri Syabani Warsa
TeknoIS : Jurnal Ilmiah Teknologi Informasi dan Sains Vol 13, No 1 (2023)
Publisher : Universitas Binaniaga Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36350/jbs.v13i1.169

Abstract

The acceptance of new students is something that is routinely carried out by pesantren every year. The very large number of students and the limited number of teaching staff which can have an impact on the ineffectiveness of the activities of the educational process in the pesantren environment. This is common and has been predicted to always occur at every new student admission. The pesantren has also taken steps to anticipate this phenomenon that usually occurs every year, namely by selecting mentors for new students. In the selection of mentors for new students, the pesantren chose seniors who had been studying at the pesantren for a long time. By choosing an accurate mentor, the mentor function can be more effective. These results were tested for accuracy using the confusion matrix formula with an accuracy of 87.5%.
Penerapan Search Engine Optimazation untuk Optimasi Performa Konten Pada Website Kampus Anggra Triawan; An Nissa Pujiantina Majid
TeknoIS : Jurnal Ilmiah Teknologi Informasi dan Sains Vol 13, No 1 (2023)
Publisher : Universitas Binaniaga Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36350/jbs.v13i1.180

Abstract

The use of content on the campus website that is still static, using a single meta tag, and not applying meta writing techniques causes the content on the website to be not optimal and the use of meta tags, headings and subheadings in website content is not yet effective, so optimization on page optimization is still weak. Search Engine Optimization (SEO) is a way to optimize a website so that it ranks at the top of search results. On Page Optimization is a technique for optimizing content on website pages. This study applies Search Engine Optimization On Page to optimize content on the Binaniaga Indonesia University website. The results of the measurements carried out for one week obtained the final result measurement of 3.59, the average number of persession pages from 5 users, with an increase of 41.78% after implementing Search Engine Optimization. So that the developed application can be categorized into a very feasible interpretation.
Penerapan Metode AHP untuk Prediksi Persiapan Total Ekuitas Year of Year pada Bank Julio Warmansyah
TeknoIS : Jurnal Ilmiah Teknologi Informasi dan Sains Vol 13, No 1 (2023)
Publisher : Universitas Binaniaga Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36350/jbs.v13i1.162

Abstract

Banking has its own assessment of the total equity owned by the bank or as the total shares issued per year. This can be predicted using several variables including cash of credit return of assets, return of equity and gross credit. Prediction of this assessment can be developed using linear programming seen with a certain scale of banking assessment starting from 2017 to 2021. The handling of the variables mentioned above can also be arranged using priorities using the process hierarchical analytical method. Multiple linear analysis used to analyze the prediction of shares that will be released on the market predicts shares that can be released on the market based on the variables cash of credit, return of assets, return of equity and gross credit.
Penerapan Restful API Pada Push Notofication Untuk Rekam Data Perwalian Arif Harbani; Pangestu Septiansyah
TeknoIS : Jurnal Ilmiah Teknologi Informasi dan Sains Vol 13, No 1 (2023)
Publisher : Universitas Binaniaga Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36350/jbs.v13i1.170

Abstract

Guardianship is counseling carried out by students with guardian lecturers, to provide direction for the tutoring process at the tertiary level. Currently the academic guardianship system has an indication of a problem, which is when the student has a guardianship record every semester. And in the existing guardianship academic system, they don't have that yet. Because it is caused by students who are on leave and students who are repeating courses. In addition, guardian lecturers cannot track courses taken by students, this can be said to be ineffective. Thus, data recording and Reminder Information were developed, so that guardian lecturers can carry out the teaching and learning process more effectively and students can carry out lectures properly, because of the technology used in the academic system. This research uses the RestFul API method on Push Notifications to Record Guardianship Data to be more effective. Then to Respond and Request trust history data, namely using JSON, so that it is more structured and easier to use. The methods applied are Get, Post, Put, and Delete. Each method has uses, namely displaying trusteeship data records using the Get method, then providing guardianship records using the Post method, as well as changing records using the Put method and deleting using the Delete method. With the implementation of the RestFul API in Push Notification for the trust data recording system, a feasibility test has been carried out and obtained a value of 81.05%, which means that the application built is very feasible so that it can help the process of recording trust data.
Implementasi Metode Prototype Pada Perancangan Sistem Informasi Pengajuan Prakerin Alam Supriyatna; Ahmad Fauzi
TeknoIS : Jurnal Ilmiah Teknologi Informasi dan Sains Vol 13, No 1 (2023)
Publisher : Universitas Binaniaga Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36350/jbs.v13i1.183

Abstract

Arridho Islamic Vocational School was established in 2007 consisting of 4 (Four) Competency Expertise/Departments: (1) Akuntansi Keuangan dan Lembaga; (2) Bisnis Daring dan Pemasaran; (3) Teknik Komputer dan Jaringan; dan (4) Teknik Bisnis Sepeda Motor. From the expertise/department competencies, Arridho Islamic Vocational School has an allocation of 17 classes, a total allocation of around 36 students per class. Industrial relations are very risky in data collection and very detailed job demands, so that students can carry out their internship well. Not a few students submitted several internship applications before obtaining willingness from objects that had previously been submitted, especially if several objects provided willingness to these students. The media for the announcement of objects and information about internships were also not conveyed properly, because the media was full, damaged and covered with other information. This study has a formulation of the problem, namely how to submit independent submissions for students who have not been determined by the school where the internship will take place. Each submission must obtain a willingness from the industry/agency that will be used as a place for internships. If approved, a letter of application will be made and submitted to the company. This study aims to make the processing time in managing internship submissions better with data collection stored in the system to make it easier for the vice principal. The test results for the Submission Information System for Arridho Islamic Vocational High School were included in the very feasible category with a percentage value of 88.9% Processing Results of Expert Trial Questionnaire Data and 92% Processing Results of User Trial Questionnaire Data.
Penerapan Algoritma C4.5 Untuk Prediksi Keterlambatan Pembayaran Sumbangan Pembinaan Pendidikan (SPP) Santri Bayu Angkoso; Irmayansyah Irmayansyah
TeknoIS : Jurnal Ilmiah Teknologi Informasi dan Sains Vol 13, No 1 (2023)
Publisher : Universitas Binaniaga Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36350/jbs.v13i1.166

Abstract

SPP is a mandatory fee for students used by Islamic boarding schools to facilitate all learning activities carried out by students, with a predetermined payment time. One of the problems in paying tuition fees is the case of students being late in paying tuition fees. The problem of late payment of tuition fees is something that must be considered because this can affect the implementation of education and fulfillment of needs and result in a decrease in the financial income of the pesantren. If the problem of late tuition payments can be predicted more quickly, then the management can prevent and anticipate earlier. To overcome this problem, the c4.5 algorithm is applied to predict late payment of tuition fees in order to produce a pattern based on the classification results. By using the variables of Parents' Income, Dependents, Father's Job, First Payment, Second Payment and Third Payment. This is done to see students who have the potential to be late in making tuition payments so that they can anticipate a decline in the financial income of the pesantren. In this study, the accuracy of the c.45 algorithm method has been tested for prediction of late tuition payments using the confusion matrix formula with an accuracy of 76.92%.
Penerapan Algoritma Naïve Bayes Untuk Penentuan Balita Penerima Makanan Tambahan (PMT) Berdasarkan Status Gizi Di Pos Pelayanan Terpadu (POSYANDU) Derman Janner Lubis; Gemilang Karunia Gusti
TeknoIS : Jurnal Ilmiah Teknologi Informasi dan Sains Vol 13, No 1 (2023)
Publisher : Universitas Binaniaga Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36350/jbs.v13i1.177

Abstract

This study aims to determine toddlers who are classified as toddlers who are eligible to receive assistance as recipients of additional food (PMT) based on the nutritional status of toddlers. A toddler does not get nutrition in a balanced amount, malnutrition can occur, and the toddler himself will have stunted growth, so the problem I raised is that toddlers who are affected by malnutrition will be assisted by the Health and Posyandu in the Supplementary Feeding program (PMT) so that the nutrition of infants affected by malnutrition can be assisted in their recovery. This research was carried out from April to June 2022, located at Posyandu Melati, Kelurahan Margatunggal, Kecamatan Jayaloka, Musi-Rawas, South Sumatra. In this research, an application is made that can provide determination of eligible toddlers as recipients of additional food (PMT) to minimize errors in choosing toddlers who deserve this assistance by applying the Naive Bayes method. The variables used were based on the nutritional status of toddlers such as gender, nutritional status, weight based on age, nutritional status, height based on age, nutritional status, weight based on height, status of toddlers receiving additional food. % and is interpreted as very feasible while the results of the user eligibility percentage are 88.48%, then related to the application made can be categorized into a very feasible interpretation. And an accuracy test has also been carried out using a confusion matrix with 96% accuracy results.
Penerapan Convolutional Neural Networks Menggunakan Edge Detection Untuk Identifikasi Motif Jenis Batik Lis Utari; Ammar Zulfikar
TeknoIS : Jurnal Ilmiah Teknologi Informasi dan Sains Vol 13, No 1 (2023)
Publisher : Universitas Binaniaga Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36350/jbs.v13i1.184

Abstract

Batik is the work of the Indonesian nation which is a combination of art and technology by the ancestors of the Indonesian people. UNESCO designated batik as a Humanitarian Heritage for Masterpieces of the Oral and Intangible Heritage of Humanity, followed by a presidential decree on 2 October 2009 which was designated as Indonesia's National Batik Day. In maintaining the existence of batik in the era of technological advances, they have utilized Artificial Intelligence and Machine Learning technologies. Even though research on batik motifs has become a common topic, there are still many mistakes found during the process of identifying motifs. As is well known, Indonesia has various types of traditional batik which have very diverse colors, patterns and motifs. This is the main problem in the identification of batik motifs, where it is found that many batik motifs adopt or have similarities in either pattern or color to other batik motifs, giving rise to thin predictions when identified with other motifs. This study uses the Convolutional Neural Networks (CNN) method using Edge Detection to identify batik motifs. Using the main dataset of 1106 images divided into 4 classes, namely Kawung, Megamendung, Merak Ngibing, and Parang motifs. The research is focused on comparing the results of prediction effectiveness on the CNN model with Canny edge detection (CNN-Canny) and the CNN model with Sobel edge detection (CNN-Sobel). The training process for each model is applied the same configuration to the dataset with a ratio of 8:2. Then in the model augmentation the functions of random flip, random zoom, and random invert are applied. The results obtained from learning the machine learning model at the testing and validation stage on the CNN-Sobel model obtained an accuracy of 91.2% in the training process and 91.8% in the validation process. Meanwhile, CNN-Canny got 90.5% accuracy in the training process and 86.2% in the validation process. The results of the comparison of the performance of the two models which are mapped to the confusion matrix table on 16 data testing in the form of images of batik motifs that have never been studied by each model show that the CNN-Sobel model can work more optimally than the CNN-Canny model with an accuracy comparison percentage of 94%. compared to 76% in the process of identifying batik motifs.
Penerapan Information Gain Dan Algoritma K-Means Untuk Klasterisasi Kedisiplinan Pegawai Menggunakan Rapidminer Zulkarnaen Noor Syarif
TeknoIS : Jurnal Ilmiah Teknologi Informasi dan Sains Vol 13, No 1 (2023)
Publisher : Universitas Binaniaga Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36350/jbs.v13i1.165

Abstract

One aspect of the discipline of an employee in an agency can be seen from the side of attendance. The level of employee attendance is closely related to an employee's disciplinary assessment. The level of employee discipline can be seen by looking at the hours of attendance or check in attendance, so that with these parameters you will get early, on time and late entry. This study explores data on attendance by using the k-means clustering algorithm. Before calculating the k-means clustering algorithm, attribute selection using information gain is expected to reduce attributes with small weights. The calculations are performed using Rapidminer software. The results showed that the attribute that had the greatest influence was the percentage of late entry with a weight of 0.783. Clustering using the k-means algorithm produces three clusters with the performance value of the Davies Bouldin Index (DBI) -0.645. Cluster zero has fifteen members, cluster one has thirty-six members, and cluster two has fifty-two members. Cluster zero is a cluster that has a low level of discipline, cluster one is a cluster that has a high level of discipline, while cluster two is a cluster that has a moderate level of discipline.

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