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Register: Jurnal Ilmiah Teknologi Sistem Informasi
Published by Universitas Pesantren Tinggi Darul ulum
ISSN : 25030477     EISSN : 25023357     DOI : https://doi.org/10.26594/register
Core Subject : Science,
Computer Science & IT
Register: Scientific Journals of Information System Technology is an international, peer-reviewed journal that publishes the latest research results in Information and Communication Technology (ICT). The journal covers a wide range of topics, including Enterprise Systems, Information Systems Management, Data Acquisition and Information Dissemination, Data Engineering and Business Intelligence, and IT Infrastructure and Security. The journal has been indexed on Scopus (reputated international indexed) and accredited with grade “SINTA 1” by the Director Decree (1438/E5/DT.05.00/2024) as a recognition of its excellent quality in management and publication for international indexed journal.
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Articles 7 Documents
 1 
Search results for , issue "Vol 7, No 1 (2021): January" : 7 Documents clear
TOPSIS for mobile based group and personal decision support system Dewi, Ratih Kartika; Jonemaro, Eriq Muhammad Adams; Kharisma, Agi Putra; Farah, Najla Alia; Dewantoro, Mury Fajar
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 7, No 1 (2021): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v7i1.2140

Abstract

Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is an algorithm that can be used for alternative design in a decision support system (DSS). TOPSIS provides recommendation so that users can get information that support their decision, for example a tourist wants to visit a tourist destination in Malang, then TOPSIS provides recommendations of tourist destinations in the form of ranking recommendation, with the highest rank is the most recommended recommendation. TOPSIS-based Mobile Decision Support System (DSS) has relatively low algorithm complexity. However, there are some cases that require development from personal DSS to group DSS, for example tourists rarely come alone, in which case most of them invite friends or family. For users who are more than 1 person, the TOPSIS algorithm can be combined with the BORDA algorithm. This study explains about the implementation & testing of TOPSIS and TOPSIS-BORDA as algorithms for personal and group DSS in mobile-based tourism recommendation system in Malang. Correlation testing was conducted to test the effectiveness of TOPSIS in mobile-based recommendation system. In previous study, correlation testing for personal DSS showed that there was a relationship between the recommendation and user choice, with correlation value of 0.770769231. In this study, correlation testing for group DSS showed there is a positive correlation of 0.88 between the recommendations of the group produced by TOPSIS-BORDA and personal recommendations for each user produced by TOPSIS.
Identifying Degree-of-Concern on COVID-19 topics with text classification of Twitters Hasanah, Novrindah Alvi; Suciati, Nanik; Purwitasari, Diana
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 7, No 1 (2021): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v7i1.2234

Abstract

The COVID-19 pandemic has various impacts on changing people’s behavior socially and individually. This study identifies the Degree-of-Concern topic of COVID-19 through citizen conversations on Twitter. It aims to help related parties make policies for developing appropriate emergency response strategies in dealing with changes in people’s behavior due to the pandemic. The object of research is 12,000 data from verified Twitter accounts in Surabaya. The varied nature of Twitter needs to be classified to address specific COVID-19 topics. The first stage of classification is to separate Twitter data into COVID-19 and non-COVID-19. The second stage is to classify the COVID-19 data into seven classes: warnings and suggestions, notification of information, donations, emotional support, seeking help, criticism, and hoaxes. Classification is carried out using a combination of word embedding (Word2Vec and fastText) and deep learning methods (CNN, RNN, and LSTM). The trial was carried out with three scenarios with different numbers of train data for each scenario. The classification results show the highest accuracy is 97.3% and 99.4% for the first and second stage classification obtained from the combination of fastText and LSTM. The results show that the classification of the COVID-19 topic can be used to identify Degree-of-Concern properly. The results of the Degree-of-Concern identification based on the classification can be used as a basis for related parties in making policies to formulate appropriate emergency response strategies in dealing with changes in public behavior due to a pandemic.
An in-depth performance analysis of the oversampling techniques for high-class imbalanced dataset Wibowo, Prasetyo; Fatichah, Chastine
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 7, No 1 (2021): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v7i1.2206

Abstract

Class imbalance occurs when the distribution of classes between the majority and the minority classes is not the same. The data on imbalanced classes may vary from mild to severe. The effect of high-class imbalance may affect the overall classification accuracy since the model is most likely to predict most of the data that fall within the majority class.  Such a model will give biased results, and the performance predictions for the minority class often have no impact on the model. The use of the oversampling technique is one way to deal with high-class imbalance, but only a few are used to solve data imbalance. This study aims for an in-depth performance analysis of the oversampling techniques to address the high-class imbalance problem. The addition of the oversampling technique will balance each class’s data to provide unbiased evaluation results in modeling. We compared the performance of Random Oversampling (ROS), ADASYN, SMOTE, and Borderline-SMOTE techniques. All oversampling techniques will be combined with machine learning methods such as Random Forest, Logistic Regression, and k-Nearest Neighbor (KNN). The test results show that Random Forest with Borderline-SMOTE gives the best value with an accuracy value of 0.9997, 0.9474 precision, 0.8571 recall, 0.9000 F1-score, 0.9388 ROC-AUC, and 0.8581 PRAUC of the overall oversampling technique.
Analysis of e-learning readiness level of public and private universities in Central Java, Indonesia Saintika, Yudha; Astiti, Sarah; Kusuma, Dwi Januarita Ardianing; Muhammad, Arif Wirawan
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 7, No 1 (2021): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v7i1.2042

Abstract

The development of information technology has reached into various fields, such as education. The emergence of e-learning is one manifestation of information and communication technology (ICT) in education. Until recently, only a few universities (6%) have implemented e-learning in Indonesia. Those that have implemented e-learning are still not optimally utilized. Some experts have also warned all organizations that will adopt e-learning to be concerned with thorough preparation to avoid overruns in costs. There is a method that consists of factors to measure the level of readiness of tertiary institutions towards the implementation of e-learning. The level of readiness is obtained through the distribution of questionnaires using 5 Likert scales. This research proposed a framework that produces four factors from the university, which covers the lecturer’s characteristics, e-learning facilities, learning environment, learning management, and four factors from the student’s side, namely, self-learning, motivation, learner’s control, student’s characteristic. The measurement results show the level of readiness for e-learning implementation in tertiary institutions in Central Java Province reaches level 3 or ready but needs a few improvements. Improvements that must be made includes (1) Designing exciting learning content through interactive multimedia; (2) Increasing the frequency of e-workshops or e-training related to technological developments, especially to e-learning; (3) encouraging students to be more active in discussions and giving opinions; (4) Developing plans related to infrastructure such as servers related to their capacities; (5) strengthening the role of IT units in serving e-learning users.
Optimizing costs for vaccine control using the reorder point approach Huizen, Lenny Margaretta; Handayani, Titis; Cholil, Saifur Rohman; Faradilah, Yanti
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 7, No 1 (2021): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v7i1.2099

Abstract

Vaccines are biological products that have an important role in human immunity. In Indonesia, some vaccines are categorized as compulsory vaccines and additional vaccines. The demand for additional vaccines is less predictable because they are not mandatory for use. This of course makes the amount of demand for vaccines less predictable. Also, the price of additional vaccines is not cheap when compared to the price of mandatory vaccines. So that the management of vaccines in the pharmacy warehouse is needed so that the amount of supply and demand is balanced so that the costs incurred will be more optimal. The information system regarding vaccine reordering is carried out using a reorder point so that the pharmacy warehouse can order according to the right need and at the right time.  The data used are demand data, prices, storage costs, and message costs. The results of calculations using reorder points within four months with a total purchase for the Rotavirus vaccine was 62 for IDR 28,274,948 and 70 for the hospital of IDR 31,801,500 with a difference of IDR 3,528,552. The calculation result using the reorder point for the Hexaxim vaccine with a total purchase for 4 months was 61 with a nominal value of IDR 58,380,060 while the calculation in the hospital was 67 with a nominal value of IDR 63,971,000 so that a nominal difference of IDR 5,590,940 was obtained.  Use of the return point can be used to alarm when and how many vaccines to order. This can be seen from the cost difference between the pharmacy warehouse and the calculation using the reorder point for the Hexaxim vaccine and the Rotavirus vaccine.
Movie recommender systems using hybrid model based on graphs with co-rated, genre, and closed caption features Adikara, Putra Pandu; Sari, Yuita Arum; Adinugroho, Sigit; Setiawan, Budi Darma
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 7, No 1 (2021): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v7i1.2081

Abstract

A movie recommendation is a long-standing challenge. Figuring out the viewer’s interest in movies is still a problem since a huge number of movies are released in no time. In the meantime, people cannot enjoy all available new releases or unseen movies due to their limited time. They also still need to choose which movies to watch when they have spare time. This situation is not good for the movie business too. In order to satisfy people in choosing what movies to watch and to boost movie sales, a system that can recommend suitable movies is required, either unseen in the past or new releases. This paper focuses on the hybrid approach, a combination of content-based and collaborative filtering, using a graph-based model. This hybrid approach is proposed to overcome the drawbacks of combination in the content-based and collaborative filtering. The graph database, Neo4j is used to store the collaborative features, such as movies with its genres, and ratings. Since the movie’s closed caption is rarely considered to be used in a recommendation, the proposed method evaluates the impact of using this syntactic feature. From the early test, the combination of collaborative filtering and content-based using closed caption gives a slightly better result than without closed caption, especially in finding similar movies such as sequel or prequel.
Land-use suitability evaluation for organic rice cultivation using fuzzy-AHP ELECTRE method Ali, Ircham; Gunawan, Vincensius; Adi, Kusworo
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 7, No 1 (2021): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v7i1.2080

Abstract

Land conversion to organic agriculture is the answer to land degradation problems that interfere with land resources sustainability. An evaluation of land-use suitability is crucial to measure the appropriateness of land for agricultural cultivation. Specifically, organic rice cultivation has some particular standard criteria such as temperature, rainfall, soil depth, pH, c-organic, slope, erosion level, a transition period that influence ranking results, and land suitability classes. Eight organic farmlands were used as alternatives, namely Sawangan, Mangunsari, Tirtosari, Podosoko, Butuh, Krogowanan, Kapuhan, and Jati. Fuzzy Analytic Hierarchy process is used to determine the level of importance of the criteria based on weight assessments by three agricultural experts. The ELECTRE method is applied to rank the most suitable land from several alternatives for organic rice cultivation. The combination of these two multi-criteria decision-making methods complements each other to solve problems in land suitability evaluation. A web-based decision support system (DSS) was created to accelerate data processing integration and present factual information from the land suitability selection process. The implementation of DSS with fuzzy-AHP ELECTRE for evaluating land-use suitability in organic rice cultivation provided the best score for Tirtosari with Ekl=4 and spearman rank correlation the system comparison results with actual data rs=0.95. This study's results indicate that integrating the web with fuzzy-AHP ELECTRE is quite effectively applied for decision-making in organic farming.

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