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JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 2686228X     DOI : -
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Artikel yang dimuat melalui proses Blind Review oleh Jurnal JOSH, dengan mempertimbangkan antara lain: terpenuhinya persyaratan baku publikasi jurnal, metodologi riset yang digunakan, dan signifikansi kontribusi hasil riset terhadap pengembangan keilmuan bidang teknologi dan informasi. Fokus Journal of Information System Research (JOSH)
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 754 Documents
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Sistem Pendukung Keputusan Seleksi Pertukaran Mahasiswa Dalam Mendukung Kampus Merdeka Menerapkan Metode ROC dan TOPSIS Assrani, Dwika; Triayudi, Agung; Simanjuntak, Handayani; Panjaitan, Fricia Oktaviani; Mesran, Mesran
Journal of Information System Research (JOSH) Vol 5 No 2 (2024): Januari 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i2.4806

Abstract

The Indonesian Minister of Education, Nadiem Anwar Makarim, B.A., M.B.A. make a policy, namely an independent campus that strongly supports students in doing learning outside of campus in order to get new views of creative and innovative mindsets so that university graduates are expected to be able to compete in the world of work. In conducting the selection of student exchanges in supporting the independent campus, Budi Darma University is less effective, so to facilitate the student selection process in supporting the independent campus, a decision support system is needed in decision making, namely by using the Rank Order Centroid (ROC) method and the Technique For Orders Reference by Similarity to Ideal Solution (TOPSIS). The results of this study are the TOPSIS method, the best alternative is A4 for Desi Novria Siregar with a value of 1 and the lowest alternative is A6 for Fabyen Sabillah Chan with a value of 0.0645
Penerapan Metode Metode Multi Attribute Utillity (MAUT) dengan Pembobotan Rank Order Centroid (ROC) dalam Pendukung Keputusan Pemilihan Mahasiswa Berprestasi Tampake, Damian; Malau, Morando; Iskandar, Agus
Journal of Information System Research (JOSH) Vol 5 No 2 (2024): Januari 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i2.4824

Abstract

Outstanding students are one of the most important parts of a university or institute where outstanding students can help raise the quality level of a university, both public and private. The achievements that have been achieved can become a benchmark for an active student in a particular field, but the number of students who excel becomes a problem for lecturers and lecturers to choose the best. Therefore, a Decision Support System is needed by applying the MAUT method with ROC weighting so that it is expected to produce a systematic and accurate ranking that makes it easier for teachers or lecturers to choose students who are eligible to be outstanding students. Obtaining calculations on several data with predetermined criteria, resulted in an accurate ranking on behalf of Melati Intan as the first rank on alternative A6 resulting in the best preference value of 10.3719.
Prediksi Jumlah Sampah Kelurahan Menggunakan Neural Network Backpropagation Khamid, Mayu Shofwan; Maimunah, Maimunah; Sukmasetya, Pristy
Journal of Information System Research (JOSH) Vol 5 No 2 (2024): Januari 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i2.4825

Abstract

Serious problems related to waste in urban areas, including Magelang City, have led to deepening problems. Rapid population growth and limited land at Banyuurip landfill make it difficult for the government to manage waste and potentially cause negative impacts on the surrounding environment. In an effort to overcome this problem, it is necessary to predict the amount of waste received at Banyuurip landfill from each village in Magelang city every day. The method used is Backpropagation Neural Network with five steps such as data collection, data preparation, data pre-processing, prediction modeling and model evaluation, with the results showing that the Backpropagation Neural Network method, using parameters 30-7-1 and number of epochs 1000, produces the best Mean Squared Error (MSE) value of 0.00013 in Potrobangsan Village. The importance of data normalization in pre-processing is also emphasized, because it can minimize errors and improve prediction accuracy. In this study, data normalization was carried out using an equation, with minimum and maximum values of 0.610 and 4.600 respectively, which were obtained from actual values.The study also determined the percentage of data division, with 15% for test data (361 data) and 85% for training data (1039 data). The low error rate of the prediction model shows the best performance. The model successfully predicts the daily amount of waste for each day in January 2023 in 17 urban villages in Magelang City, using the Backpropagation ANN method with architecture and models that have gone through training and testing stages.
Implementasi Text Mining Dalam Penentuan Kinerja Layanan Antara Grab dan Gojek Berdasarkan Opini Masyarakat Menggunakan LDA Syapira, Tiwi; Zufria, Ilka
Journal of Information System Research (JOSH) Vol 5 No 2 (2024): Januari 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i2.4833

Abstract

Public transportation is currently based on applications and the internet, so it is called online transportation. Grab and Gojek are two online transportation service providers who want to provide the best service. Users provide responses, experiences, criticism and suggestions via Twitter. This research will use the LDA algorithm to map topics that users frequently discuss regarding Gojek and Grab. Latent Dirichlet Allocation (LDA) is an unsupervised learning algorithm used to detect topics in a collection of text documents. LDA assumes that each document consists of a mixture of several topics, and that each topic consists of a probability distribution over words. LDA works by modeling the generative process of documents. This process begins by selecting a topic for the document, then selecting words from that topic. The probability of selecting certain topics and words is determined by parameters learned from the data. Data was obtained via Twitter with the keywords "#grabid" and "#gojekindonesia". From the research results, it was found that the best topic mapping results for Gojek objects were 2 topics, namely promotions and orders. Meanwhile, Grab objects are divided into 4 topics, namely communication, transactions, orders and orders
People Entity Recognition in Indonesian Alquran Translation using Roberta Mutia, Aufa; Bijaksana, Moch Arif
Journal of Information System Research (JOSH) Vol 5 No 2 (2024): Januari 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i2.4838

Abstract

The Quran was revealed in Arabic, which has a complex linguistic structure, a unique writing system, and intricate grammar, making it challenging to understand. Therefore, understanding and interpreting the Quran is a primary goal for Muslims. To comprehend the teachings contained in the Quran, Muslims need an understanding of the human entities mentioned in it. However, manually labeling human entities in the Quran can be a complex task prone to errors. The aim of this research is to facilitate the process of labeling human entities in Quranic texts by building a model with good performance. RoBERTa is a Named Entity Recognition (NER) model that is an extension of BERT, trained with enhanced training methodologies. This study focuses on the use of the RoBERTa model to identify human entities in the translated text of the Quran in Bahasa Indonesia. The input to this system consists of translated Quranic sentences, which are then processed by the model to generate output in the form of predicted labels for those sentence entities. The model is constructed by utilizing a dataset from the Tanzil Quran corpus, covering chapters 1 to 6. Data preprocessing involves punctuation removal, tokenization, and case folding. The dataset is divided into training data (80%) and testing data (20%). The RoBERTa model is trained with hyperparameters such as epochs, learning rate, and batch size. Evaluation is performed using metrics such as Precision, Recall, and F-Score on the testing data. The evaluation results of the constructed RoBERTa model show an F-Score value of 52%. This score is not better compared to the BERT model, indicating that the RoBERTa model tends to have inferior performance in identifying human entities in the translated text of the Quran.
Implementasi Metode COPRAS Dengan Pembobotan ROC Dalam Menentukan Food Delivery Application Terbaik Sihombing, Daniel Oktodeli; Yutika, Fitri; Cahyadi, Alex
Journal of Information System Research (JOSH) Vol 5 No 2 (2024): Januari 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i2.4839

Abstract

The food delivery application is a digital platform that allows users to order food from restaurants or other food vendors through smartphones or computers. Good service quality in the Food Delivery Application (FDA) has a positive and significant impact on customer loyalty to online food delivery services. Complex Proportional Assessment (COPRAS) is a multi-criteria decision-making method that has been extensively researched and applied in various fields. Weighting using the ROC method has proven to be highly effective in various research contexts. Data from 125 respondents used in this study were calculated using the COPRAS method and ROC weighting to generate rankings for each FDA. Service quality, promotions, features, costs, and UI/UX are criteria used in this calculation. The results of the calculation using the COPRAS method and ROC weighting show a slight difference, where alternative A1, GoFood, ranks first with a value of 0.55585381, followed by alternative A3, ShopeeFood, in second place with a value of 0.55584456, and alternative A2, GrabFood, in third place with a value of 0.55449330. Thus, the best FDA resulting from the calculation using the COPRAS method and ROC weighting is GoFood.
User Interface Redesign for the Course Card Filling Feature in the SIKAD Mobile Web Application using Goal-Directed Design Method Handayani, Fitri; Wisudiawan, Gede Agung Ary; Adrian, Monterico
Journal of Information System Research (JOSH) Vol 5 No 2 (2024): Januari 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i2.4844

Abstract

The SIKAD mobile web application is a platform for an online-based Academic Information System developed by the Islamic University of Riau. The primary objective of this application is to facilitate various crucial processes such as Course Card Filling, printing of Study Result Cards, transcript printing, viewing payment history, and leave application. However, after conducting a usability evaluation using the System usability scale (SUS) involving 5 respondents, namely students of the Islamic University of Riau, it was found that the SUS score for this application was 60.0. Additionally, through interviews with the head of the development team and the respondents, issues were identified in the Course Registration interface which involved Course Card Filling and Course Card Printing feature. These issues were related to an untidy layout, unclear information, and inappropriate button placement on the screens of each respondent's device. Consequently, the user experience in using the SIKAD mobile web application was less satisfactory for the students. Therefore, the objective of redesigning the SIKAD mobile web application is to enhance the user experience in the Course Registration on the mobile platform and improve user satisfaction. The method employed for this redesign is Goal-Directed Design (GDD), which is suitable for meeting user needs and objectives. The redesigned interface will be evaluated using the System usability scale (SUS) to measure the extent to which the desired goals have been achieved. Through the GDD approach, it is anticipated that interface issues in this application can be addressed, and the set objectives can be fulfilled, resulting in an overall improvement in the usability of the SIKAD mobile web application.
Solusi Numerik Model Verhulst Pada Estimasi Hasil Panen Melalui Perkembangan Produksi Padi dan Beras dengan Metode Milne-Simpson Arjuna, Dimas Bagus; Lubis, Riri Syafitri
Journal of Information System Research (JOSH) Vol 5 No 2 (2024): Januari 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i2.4857

Abstract

The aim of this research is to develop a numerical solution using the Verhulst model to estimate paddy and rice production in North Sumatra. The Milne-Simpson method is used in this research to provide an efficient numerical approach in solving the model, with the aim of increasing the accuracy and effectiveness of estimating rice plant growth and rice production in the North Sumatra region through a systematic and computational approach. In this research, the Milne-Simpson method is used to estimate paddy and rice production results in the following year. The results show that the estimated rice production in North Sumatra Province is 2,086,590.76 tons in 2023 and 2,098,149 tons in 2024. Meanwhile, the estimated rice production in North Sumatra Province is 1,198,678.38 tons in 2023 and 1,207,384 tons in 2024. The results of this research also show that every year rice production increases by an average of 13,430 and rice production increases by an average of 8,254. Therefore, it can be seen that the estimated paddy and rice production in North Sumatra Province for 2023-2024 has increased.
Implementation of the Multi-Objective Optimization Method on the Basic of Ratio Analysis (MOORA) and Entropy Weighting in New Employee Recruitment Karim, Abdul
Journal of Information System Research (JOSH) Vol 5 No 2 (2024): Januari 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i2.4859

Abstract

The problems faced by the company in managing the selection of new employees must be done in the right way so that it can help a good work cycle. The employee recruitment process still uses manual methods so the Human Resource Development (HDR) division has to sort, select and select applicants one by one. The large number of applicants means that the Human Resource Development division often experiences difficulty in selecting prospective employees and there is subjectivity when deciding which employees fit the established criteria. To overcome the problem of making employee recruitment decisions, we will use the Multi-Objective Optimization method based on ratio analysis (MOORA) and weighting using Entropy. In research, data is collected based on the position of prospective employees. The results obtained in this research determine each position that will be accepted by 3 prospective employees, namely Sales Position, Position, Graphic Design, Accounting Staff, IT Support position, Sales Project.
Influence Analysis of the Teacher Ratio and Facilities on Failure to Pass the Class Using Multiple Linear Regression Suni, Eugenius Kau; Sutresno, Stephen Aprius; Christanto, Henoch Juli; Singgalen, Yerik Afrianto
Journal of Information System Research (JOSH) Vol 5 No 3 (2024): April 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i3.4989

Abstract

The quality of education needs to be observed and maintained in building an effective teaching and learning environment. There are several factors that can affect the quality of education in a school, such as the availability of human resources, supportive learning facilities, environmental conditions, and various other factors. The focus of this research is on the ideal number of teachers in a school, considering the number of students and the availability of facilities such as laboratories and libraries, which will be correlated with the failure to pass the class rate. Data were obtained from the official website of the Kemdikbudristek regarding educational statistics, comprising 29 districts in Tangerang Regency for the academic year 2023/2024 at the senior high school level. The analysis was conducted using multiple linear regression, and it was found that the variables "availability of laboratory" and "availability of library" did not correlate with the failure to pass the class rate, whereas the "teacher ratio" variable correlated with the failure to pass the class rate with a value of +0.46. This can be explained that for every increase of 1 unit in the teacher ratio variable, or in other words, the fewer teachers teaching in a school compared to the number of students, the failure to pass the class rate will also increase by 0.46 students. Therefore, the results of this research can provide input for schools, especially in Tangerang Regency, to pay attention to the number of teachers in each school.

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