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Scientific Journal of Informatics
Published by Universitas Negeri Semarang
ISSN : 24077658     EISSN : 24600040     DOI : -
Core Subject : Science,
Computer Science & IT
Scientific Journal of Informatics published by the Department of Computer Science, Semarang State University, a scientific journal of Information Systems and Information Technology which includes scholarly writings on pure research and applied research in the field of information systems and information technology as well as a review-general review of the development of the theory, methods, and related applied sciences.
Arjuna Subject : -
Articles 564 Documents
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Simulation Study of Imbalanced Classification on High-Dimensional Gene Expression Data Masithoh Yessi Rochayani; Umu Sa'adah; Ani Budi Astuti
Scientific Journal of Informatics Vol 10, No 1 (2023): February 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i1.40589

Abstract

Purpose: Classification of gene expression helps study disease. However, it faces two obstacles: an imbalanced class and a high dimension. The motivation of this study is to examine the effectiveness of undersampling before feature selection on high-dimensional data with imbalanced classes.Methods: Least Absolute Shrinkage and Selection Operator (Lasso), which can select features, can handle high-dimensional data modeling. Random undersampling (RUS) can be used to deal with imbalanced classes. The Classification and Decision Tree (CART) algorithm is used to construct a classification model because it can produce an interpretable model. Thirty simulated datasets with varying imbalance ratios are used to test the proposed approaches, which are Lasso-CART and RUS-Lasso-CART. The simulated data are generated from parameters of real gene expression data.Results: The simulation study results show that when the minority class accounts for more than 25% of the observation size, the Lasso-CART method is appropriate. Meanwhile, RUS-Lasso-CART is effective when the minority class size is at least 20 observations.Novelty: The novelty of this simulation study is using the RUS-Lasso-CART hybrid method to address the classification problem of high-dimensional gene expression data with imbalanced classes.
Developing a Digital Scales System using Internet of Things Technology on Indonesia Digital Farm Kusrini Kusrini; Banu Santoso; Eko Pramono; Muhammad Koprawi; Jeki Kuswanto; Elik Hari Muktafin; Ichsan Wasiso
Scientific Journal of Informatics Vol 10, No 1 (2023): February 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i1.40956

Abstract

Purpose: This research aims to develop a digital scales system using internet of things technology on Indonesia digital farm.Methods: The stages of the research were carried out starting from literature studies, system requirements analysis, digital scales system design, system testing, and analysis of system test results. This model consists of hardware and software. The hardware consists of sensors for data collection in the field or using cameras, data input devices, data senders to data centers, data centers, and data processors, and data output that can be accessed on a laptop or a smartphone in real-time.Result: The results of the study show that IoT-based digital scales can be used to read goat weighing results based on RFID data input and camera image capture. The average body weight of a goat that has been weighed is 106.5 pounds, while the average body height of a goat is 150.7 cm.Novelty: The IoT-based digital scales system (IoT-DSS) can be used to measure the weight and height of goats so that the weighing process is more efficient.
Hybrid Water Feedback Solutions Using Internet of Thing (IoT) Enabled Water Pumps Powered by Solar Panels Achmad Buchori; Adhi Kusmantoro; Aan Burhanuddin; Takashi Hiyama
Scientific Journal of Informatics Vol 10, No 1 (2023): February 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i1.41007

Abstract

Purpose: Renewable energy in Indonesia is very abundant, one of which is solar energy. With Indonesia's location on the equator, the abundant potential of solar energy can be utilized as an environmentally friendly source of electricity. To increase the potential of solar energy as a source of electricity, it is equipped with a battery storage system. The most widely used electrical energy storage system is the battery. The purpose of this study is the use of solar energy for DC water pumps. The proposed system is also equipped with power, voltage and current monitoring on the solar panel side and on the load side (water pump).Methods/Study design/approach: The method used is to conduct a literature review to study and find out the development of a power monitoring system using solar panels. The next step is to measure solar radiation, calculate PV capacity and SCC. Furthermore, designing, modeling, simulating, analyzing, and implementing the optimal topology for water pump control using solar panels.Result/Findings: The results of the research are water pump control coordination devices using Sonoff with an IoT-based monitoring system. This device is capable of controlling PV and battery power flow. A prototype of a solar water pump has been produced which has been validated by experts in the field of appropriate technology with feasible results and received a positive response from farmers in Demak to be immediately implemented in the fields to help with the water crisis in agricultural landNovelty/Originality/Value: the advantage of this solar water pump is that the product is equipped with the internet of things (IoT) which can control the use of water pumps in the fields with our android devices wherever we are, this makes it easy for farmers to apply them, then the water pumps also do not use electricity which makes this water pump not harmful to farmers, because in the past many farmers were electrocuted and died.
S-box Construction on AES Algorithm using Affine Matrix Modification to Improve Image Encryption Security Alamsyah Alamsyah; Budi Prasetiyo; Yusuf Muhammad
Scientific Journal of Informatics Vol 10, No 2 (2023): May 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i2.42305

Abstract

Abstract.Purpose: In this study, the AES algorithm was improved by constructing the S-box using a modified affine matrix and implementing it so that there was an increase in security in image encryption.Methods: The method used in this study starts from selecting the best irreducible polynomial based on previous studies. The irreducible polynomial chosen is . With this irreducible polynomial, an inverse multiplicative matrix is formed. The formed inverse mutiplicative matrix is implemented in the affine transformation process using the best 3 affine matrices based on previous research and 8-bit additional constants using AES S-box. This formulation produces 3 different S-boxes, i.e., S-box1, S-box2, and S-box3. Finally, the resulting S-boxes are implemented to carry out the image encryption process and are tested for their security level.Result: The test results show an increase in image encryption security compared to previous studies. The increase in security occurred at the entropy value of 7.9994 and the NPCR value of 99.6288%.Novelty: The novelty of this paper is the improvement of the S-box construction which is implemented in image encryption resulting in increased security in image encryption.
Stacking Ensemble Learning to Improve Prediction Accuracy in P2P Lending Platform
Scientific Journal of Informatics Vol 10, No 1 (2023): February 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i1.42453

Abstract

Abstract. Purpose: The purpose of this study is to improve accuracy on the prediction of default risk. Defaults on p2p lending platforms result in significant losses for lenders and pose a threat to the efficiency of the overall peer-to-peer lending system. It is then very important to have an understanding of the methods capable of managing such risks Even with only a slight improvement in the accuracy of the model's ability to anticipate default significant losses can be avoided.Methods: The method used to make predictions is a combination method of stacking ensemble models with the LightGBM metalearner as the final estimator. While the base-learner algorithms used are Multi Layer Perceptron (MLP), Support Vector Machine (SVM) and Random Forest (RF).Result: The PPDai dataset used in this study is P2P lending data from the PPDai platform from China. The data split process uses the 10-fold cross validation method. Evaluate the model using a confusion matrix that generates accuracy values. The evaluation results showed that Stacking-LightGBM as the best model in the PPDai dataset received an accuracy of 87.18%.Novelty: This research shows that the accuracy of the peer-to-peer lending default prediction model  can be improved using the Stacking-LightGBM method. The stacking ensemble method can beat the accuracy of a single classification algorithm in terms of making predictions.  The use of meta-learners can improve the performance of ensemble stacking models.
Enterprise Digital Payment Trends Survey Post COVID-19 Situation Leon A. Abdillah; Dhea K Putri; Anggy Artavi
Scientific Journal of Informatics Vol 10, No 2 (2023): May 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i2.43068

Abstract

Purpose: This research article presents the results of a survey on digital payment transactions using mobile Fintech applications. The target users are from the tenant or seller side. The research locations were conducted in 2 (two) of the biggest malls in Palembang, namely Palembang Square (PS) and Palembang Trade Center (PTC).Methods: The research method applied is a survey involving online questionnaires using Google Forms.Result: The observed Fintech mobile applications are OVO and ShopeePay. The research collected data on 105 tenants of Small and Medium Enterprises (SMEs). The results show that the Fintech ShopeePay application (62%) is used more than OVO (38%). SME business actors are dominated by women (57%) compared to men (43%). These tenants are mainly in the Gen Z category (73%). Meanwhile, many of the business types of tenants are engaged in the culinary sector (42%). Most of the tenants' turnover range is in the range of 0-5 million (Rupiah) per month (38%). but there are 2% who have a turnover of more than 25 million (Rupiah).Novelty: This research enriches the survey on the use of the Fintech platform from the side of tenants who open their businesses in modern shopping places after COVID-19.
Analysis of Digital Supply Chain Management in E-procurement Service Usage Using Decision Making Trial Method and Evaluation Laboratory in National Public Procurement Agency Anggar Jati Saesario; Devi Ajeng Efrilianda
Scientific Journal of Informatics Vol 10, No 2 (2023): May 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i2.42224

Abstract

This study aimed to identify the implementation of the digital supply chain and its priority in the National Public Procurement Agency’s e-procurement service. To this end, a quantitative study with Decision-Making Trial and Evaluation Laboratory (DEMATEL) method using Matlab R2105a. DEMATEL result showed that eight criteria in the dispatcher group became the main priority in DSCM implementation in LKPP’s e-procurement process. In comparison, the other eight criteria in the receiver group serve as the advanced criteria in DSCM implementation. The planning criterion was the most prioritized and the most influential DSCM criterion in LKPP’s e-procurement service, which covers the distribution requirement process. The three most important DSCM criteria in LKPP’s e-procurement service were the distribution requirement process, delivery and inspection, and transportation management. The analysis showed that some DSCM criteria in LKPP’s e-procurement had met the DSCM principle. Further studies using other methods like Analytic Hierarchy Process (AHP) and Analytical Network Process (ANP) are needed.
Automatic Scoring Using Term Frequency Inverse Document Frequency Document Frequency and Cosine Similarity Winda Yulita; Meida Cahyo Untoro; Mugi Praseptiawan; Ilham Firman Ashari; Aidil Afriansyah; Ahmad Naim Bin Che Pee
Scientific Journal of Informatics Vol 10, No 2 (2023): May 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i2.42209

Abstract

Purpose: In the learning process, most of the tests to assess learning achievement have been carried out by providing questions in the form of short answers or essay questions. The variety of answers given by students makes a teacher have to focus on reading them. This scoring process is difficult to guarantee quality if done manually. In addition, each class is taught by a different teacher, which can lead to unequal grades obtained by students due to the influence of differences in teacher experience. Therefore the purpose of this study is to develop an assessment of the answers. Automated short answer scoring is designed to automatically grade and evaluate students' answers based on a series of trained answer documents.Methods: This is ‘how’ you did it. Let readers know exactly what you did to reach your results. For example, did you undertake interviews? Did you carry out an experiment in the lab? What tools, methods, protocols or datasets did you use The method used is TF-IDF-DF and Similarity and scoring computation.  Theword weight used is the term Frequency-Inverse Documents Frequency -Document Frequency (TF-IDF-DF) method. The data used is 5 questions with each question answered by 30 students, while the students' answers are assessed by teachers/experts to determine the real score. The study was evaluated by Mean Absolute Error (MAE).Result: The evaluation results obtained Mean Absolute Error (MAE) with a resulting value of 0.123.Value: The word weighting method used is the Term Frequency Inverse Document Frequency DocumentFrequency (TF-IDF-DF) which is an improvement over the Term Frequency Inverse Document Frequency (TF-IDF) method. This method is a method of weighting words that will be applied before calculating the similarity of sentences between teachers and students.
Hybrid Top-K Feature Selection to Improve High-Dimensional Data Classification Using Naïve Bayes Algorithm Riska Wibowo; M. Arief Soeleman; Affandy Affandy
Scientific Journal of Informatics Vol 10, No 2 (2023): May 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i2.42818

Abstract

Abstract. Purpose: The naive bayes algorithm is one of the most popular machine learning algorithms, because it is simple, has high computational efficiency and has good accuracy. The naive bayes method assumes each attribute contributes to determining the classification result that may exist between attributes, this can interfere with the classification performance of naive bayes. The naïve bayes algorithm is sensitive to many features so this can reduce the performance of naïve bayes. Efforts to improve the performance of the naïve bayes algorithm by using a hybrid top-k feature selection method that aims to handle high-dimensional data using the naïve bayes algorithm so as to produce better accuracy.Methods: This research proposes a hybrid top-k feature selection method with stages 1. Prepare the dataset, 2. Replace the missing value with the average value of each attribute, 3. Calculate the weight of the attribute value using the weight information gain method, 4. Select attributes using the top-k feature selection method, 5. Backward Elimination with the naïve bayes algorithm, 6. Datasets that have been selected new attributes, then validated using 10 fold-cross validation where the data is divided into training data and testing data, 7. Calculate the accuracy value based on the confusion matrix table.Result: Based on the experimental results of performance and performance comparison of several methods that have been presented (Naïve Bayes, deep feature weighting naïve bayes, top-k feature selection, and hybrid top-k feature selection). The experimental results in this study show that from 5 datasets from UCI Repository that have been tested, the accuracy value of the hybrid top-k feature selection method increases from the previous method. From the accuracy comparison results that the proposed hybrid top-k feature selection method is ranked the first best method.Novelty: Thus it can be concluded that the Hybrid top-k feature selection method can be used to handle dimensional data in the Naïve Bayes algorithm. 
Factors Affecting Students' Intentions to Use the University's E-Payment System Hersatoto Listiyono; Sunardi Sunardi; Sugiyamto Sugiyamto; Agus Prasetyo Utomo
Scientific Journal of Informatics Vol 10, No 2 (2023): May 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i2.43825

Abstract

Purpose: Most universities prioritize online payment administration because_of_advances_in_information_and communicatio_ technologies, especially for online­_banking transactions. Benefits from online banking services such as  transactions via Internet banking are very convenient compared to traditional payment methods.  On other side is traditional payment methods transactions must queue and come directly to the bank. This study was done to find out what factors in Semarang City affected the adoption of university E-PS as online banking.Methods: 123 students have participated in this research. Six charactersitics were considered in a new study model that examinated how students’ intention to use E-PS was affected: convinience, perceived usefullness, risks, perceived trust and reputation. To validate the reearch model, the structural equation model approach using PLS-SEM was apllied.Result: The empirical result showed that perceived convinience, perceived usefullness and trust had e significan positive relationship with students’ intention to use the University’s E-PS.  The empirical results showed that perceived convenience, perceived usefullness, and trust had a significant_positivee_relationshipp_withhstudents’ intentions_to_use the E-PS university. Perceived convinience was also found to have a positive and significan effect on the perceived usefullness of students using E-PS. However, the perceived risks showed a non-significan negative relationship with tudents’ intentions to use E-PS.Novelty: While previous studies have explored the intentions to se E=PS. This research contributes the literature by invetigating the specific factors that influence the adoption of E-PS in the context of tertiary institutions. Additionally, this research provides empirical evidence on the relationhip between perceived convinience and perceived convience and perceived usefullness of using E-PS in univerities. Overall, this research offers a new perspective on the adoption of E-PS in tertiary institutions and contributes to the development of strategies to improve the adoption and use E-PS in universities.

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