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Jurnal Sisfokom (Sistem Informasi dan Komputer)
Published by Sekolah Tinggi Manajemen Informatika dan Komputer Atma Luhur
ISSN : 23017988     EISSN : 25810588     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management
Jurnal Sisfokom merupakan singkatan dari Jurnal Sistem Informasi dan Komputer. Jurnal ini merupakan kolaborasi antara sivitas akademika STMIK Atma Luhur dengan perguruan tinggi maupun universitas di Indonesia. Jurnal ini berisi artikel ilmiah dari peneliti, akademisi, serta para pemerhati TI. Jurnal Sisfokom diterbitkan 2 kali dalam setahun yaitu pada bulan Maret dan September. Jurnal ini menyajikan makalah dalam bidang ilmu sistem informasi dan komputer.
Arjuna Subject : -
Articles 669 Documents
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Classification of Final Project Titles Using Bidirectional Long Short Term Memory at the Faculty of Engineering Nurul Jadid University Warda, Faridatul; Fajri, Fathorazi Nur; Tholib, Abu
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 12, No 3 (2023): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i3.1723

Abstract

Every year, the Faculty of Engineering at Nurul Jadid University forms a committee to manage the process of students' final projects from the title selection stage to the final examination process until graduation. The process of selecting the final project title is still done manually, namely by checking the titles one by one, which takes a long time and allows errors because there is a lot of data to check, so human errors can also occur. Therefore, this research proposes to use the Bidirectional Long Short Term Memory (BiLSTM) method to classify the final project title based on its grade category. Several experiments were conducted to generate the most appropriate labels. The first experiment produced 4 labels and the second experiment produced 2 labels. From the results of several experiments, it was concluded that the second experiment had the best accuracy results with the 'good enough' and 'good' classes. The oversampling technique was then applied to overcome overlapping data, and the turning process was then performed on several parameters that could re-optimize the previous accuracy result of 75.24% to 91.15%. With a configuration of 10 random state parameters, using 64 batch sizes and 50 epochs. In addition, model adjustments were made to the hidden layer by adding a dropout layer and relu activation.
IoT Botnet Detection Using Autoencoders and Decision Trees Susanto, Susanto; Arifin, M. Agus Syamsul; Wijaya, Harma Oktafia Lingga
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 12, No 3 (2023): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i3.1693

Abstract

The use of IoT devices has grown rapidly, leading to an increase in cyber attacks that pose greater security and privacy threats than ever before. One such threat is botnet attacks on IoT devices. An IoT botnet is a group of Internet-connected IoT devices infected with malware and remotely controlled by an attacker. Machine learning techniques can be employed to detect botnet attacks. The use of machine learning-based detection methods has been shown to be effective in identifying cyber attacks. The performance of the detection system in machine learning can be improved by utilizing data reduction methods. The data reduction process in classification is used to overcome the problem of scalability and computation resources in the IoT. This paper proposes a detection system using the Autoencoder reduction method and the Decision tree classification method. The test results demonstrate that the Deep Autoencoder algorithm can reduce data and memory usage from 1.62 GB to 75.9 MB, while also improving the performance of decision tree classification, resulting in a high level of accuracy up to 100%. The Autoencoder approach in conjunction with the Decision Tree exhibits superior capabilities compared to previous studies.
Prediction of Graduation for Students at the ISB Atma Luhur Faculty of Information Technology Using the C4.5 Algorithm Putri, Ine Widyaningrum Mustama; Rusdah, Rusdah; Suryadi, Lis; Anubhakti, Dian
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 12, No 3 (2023): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i3.1731

Abstract

Higher Education is a level of education after secondary education which includes diploma programs, undergraduate programs, master programs, doctoral programs, professional programs, and specialist programs organized based on the culture of the Indonesian nation. Student graduation is one of the important factors to improve university accreditation. Students who graduate above 5 years and the number of students who drop out are important indicators in determining accreditation which then causes the difficulty of accrediting a college to rise. This research aims as an early warning for students who graduate on time and graduate late from the Faculty of Information Technology, Institute of Science and Business Atma Luhur using the C4.5 decision tree algorithm by implementing the Cross-Industry Standard Process for Data Mining (CRISP- DM) method. The initial data of this research amounted to 1,015 which was taken through a query in the database of the Atma Luhur Institute of Science and Business. However, the data that will be used becomes 694 after preprocessing due to the large number of record contents that do not have a graduation year, with a total of 641 graduates graduating on time and 53 graduates graduating late. Based on the application of the model using the C4.5 decision tree algorithm and the Confusion Matrix method, the accuracy is 93.94%, Recall is 98.59%, and Precision is 95.03%. So it can be concluded that the C4.5 decision tree algorithm is the most effective algorithm for predicting student graduation, because it has a high level of accuracy.
Image Restoration Using Deep Learning Based Image Completion Chyan, Phie; Saptadi, Tri
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 12, No 3 (2023): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i3.1699

Abstract

Digital images can experience various disturbances in acquisition and storage, one of which is a disturbance indicated by damage to certain areas of the image field and causes the loss of some of the information represented by the image. One of the ways to restore an image experiencing disturbances like this is with image completion technology. Image completion is an image restoration technology capable of filling in or completing missing or corrupted parts of an image. Various methods have been developed for this image completion, starting from those based on basic image processing to the latest relying on artificial intelligence algorithms. This study aims to develop and implement an image completion model based on deep learning with the transfer learning method from the completion.net architecture. Using the Facesrub training dataset consisting of a collection of unique facial photos allows the model to understand facial attributes better. Compared to conventional image completion based on image patches, the method developed in this study can perform image filling in image gaps with more realistic results. Based on visual tests conducted on respondents, the results obtained enable respondents to understand all the information represented by the restored image, similar to the original image.
Priority Recommendations for Residential Road Improvement Using the SMART Analysis Method Sumaryanti, Lilik; Nugraha, Syaiful; Lamalewa, Lusia
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 12, No 3 (2023): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i3.1738

Abstract

Roads are infrastructure for organizing transportation, which are places for traffic to flow both for people and goods to reach destinations safely, securely, comfortably, quickly, smoothly, orderly, and efficiently, especially roads in residential areas. Setting priorities for the road improvement program is the responsibility of the Public Housing, Settlement Areas, and Land Affairs Office, which handles technical planning, development, arrangement, supervision, and control of development in residential areas. Recommendations for road proposals for the currently running improvement program, based on an assessment of their physical condition, are carried out by experts. This prioritization certainly takes a long time because experts have to compare the physical conditions of the roads one by one to make a decision. A decision support system is specifically designed for the decision-making process that can be applied in various aspects of the decision-making field. Recommendations for alternative roads in the road improvement program were analyzed using the SMART method to find alternatives with the highest preference value and the advantage that they can be used for all weighting techniques. Accuracy testing shows that the priority recommendation output presented by the application has an accuracy rate of 80%. This value is obtained by comparing the results of recommendations from experts.
DeLone and McLean Model Analysis of Success Factors of SIDEMANG Application in Palembang City Faris, Haninda Ammar; Wedhasmara, Ari; Putra, Apriansyah; Kurnia, Rizka Dhini; Bardadi, Ali; Fitri, Shofiyah
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 13, No 2 (2024): JULY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v13i2.1894

Abstract

Indonesia is ranked 77th in the world in electronic-based government systems, especially the City of Plembang is ranked 89th regarding the evaluation of smart city improvement in Indonesia. One of the latest applications used in the past year is the SIDEMANG application, which is an information system that has the use and purpose of facilitating access to administrative services related to personal and agency licensing files online at the village and sub-district levels in Palembang city, but this is also not free from obstacles, especially internet signals. Therefore, an analysis is needed related to the implementation of Information Systems, to assess the success of applications that have been implemented, especially government digital services. DeLone and McLean Information System Success Model is used, to see the significant factors that cause the success of Information System implementation. The data analysis method used in this research is quantitative because the data collected is in the form of numbers and will be analyzed using the SmartPLS application statistical technique, using a sample size of 97 respondents. The results showed that the information quality factor was not significant to the intention or use of the application, the system quality factor was not significant to the intention or use of the application, the system quality factor was not significant to user satisfaction, the service quality factor was not significant to user satisfaction. Recommendations for the Palembang City Communication and Information Office are related to the evaluation and improvement of the SIDEMANG application using the DeLone and McLean Model analysis. In particular, improvements to the quality of information that can influence citizens to use the application, improvements to the quality of the system that can invite and satisfy users in using the application, and improvements to service quality factors on citizen satisfaction.
Comparison Of K-Means and K-Medoids Algorithm for Clustering Data UMKM in Pagar Alam City ariska, sendy; Puspita, Desi; Anggraini, Inda
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 13, No 2 (2024): JULY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v13i2.2090

Abstract

The aim of this research is clustering MSME data in Pagar Alam City using the K-Means and K-Medoids algorithms. This research is motivated by the lack of further management of MSME data collection, which can hinder the development and improvement of Pagar Alam City MSMEs. Meanwhile, this data is considered necessary for agencies to develop and improve Pagar Alam City MSMEs. Apart from agencies, this data is also useful for sub-districts, sub-districts and RT/RW to find out what interests, talents and potential the community has in what business fields. MSME data is processed using Rapid Miner and Python, the system development method in this research uses the Cross Industry Standard Process for Data Mining (CRISP-DM) method, where the stages include Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. The test method uses the Davies-bouldin index, a DBI value that is close to 0 results in good clustering. The results of this research obtained 3 clusters. In 2020 K-Means C0= 1, C1= 3 and C2= 1 sub-district, K-Medoids C0= 1, C1= 1 and C2= 3 sub-district. In 2022 K-Means C0= 1, C1= 3 and C2= 1 sub-district, K-Medoids C0= 1, C1= 3 and C2= 1 sub-districts. The results of the 2020 sub-district DBI clustering calculation are DBI k-means = 0.134 and k-medoids = 0.523. In 2022 DBI k-means = 0.277 and k-medoids = 0.496. So it can be concluded that the K-Means algorithm in the case of grouping MSMEs in Pagar Alam City has better performance, because the DBI value is close to 0. From the results of the grouping it can help provide an overview for related parties in encouraging or providing assistance to sub-districts that are included in the low cluster.
Comparative Analysis of SVM and NB Algorithms in Evaluating Public Sentiment on Supreme Court Rulings Maulidiana, Putri Dwi Rahayu; Vitianingsih, Anik Vega; Kacung, Slamet; Maukar, Anastasia Lidya; Hermansyah, David
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 13, No 2 (2024): JULY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v13i2.2116

Abstract

The legal events that happened to Ferdy Sambo and the Supreme Court’s decision in the cassation triggered emotional reactions and various opinions among the public, especially on social media sites such as Xapps. Some comments reflect people’s concerns about fairness in the legal system. They doubted the integrity of legal institutions or believed that decisions were unfair or in line with vested interests. This research aims to analyze public perceptions of Supreme Court decisions. The research process includes data collection, preprocessing, labeling, weighting, classification using Support Vector Machine and Naïve Bayes, and performance evaluation using a confusion matrix. A dataset of 624 was taken from X apps using the Twitter scraping technique. The lexicon method is used for data labeling, dividing the data into positive, negative, and neutral classes. The analysis results show 46 tweets categorized as positive sentiment, 133 tweets categorized as negative sentiment, and 422 tweets categorized as neutral sentiment. Based on testing with a data ratio of 80:20, both SVM and NB methods show good performance. The SVM criteria showed an accuracy of 0.84, precision of 0.61, recall of 0.78, and f1-score of 0.66, while the NB criteria showed an accuracy of 0.73, precision of 0.37, recall of 0.57, and f1-score of 0.35.
Decision Support System for Ranking Active Waste Bank in Makassar City Using TOPSIS and VIKOR Methods Papua, Ahmad Ruslandia; Hasanuddin, Tasrif; Hasnawi, Mardiyyah
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 13, No 2 (2024): JULY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v13i2.2158

Abstract

In the city of Makassar, there were initially around 1000 waste banks, but this number has decreased significantly, and by 2023 only 381 waste banks remain active. The decline in the number of waste banks is primarily due to the society's lack of knowledge regarding the utilization of waste banks. This research aims to rank active waste banks in Makassar using the MCDM (Multi-Criteria Decision Making) technique. Two MCDM methods will be utilized in this study: the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method and the VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) method. Both methods share a common goal of finding the closest value to the ideal solution, but they differ in their normalization and aggregation functions. TOPSIS calculates the criteria weight values first, followed by the criteria values, whereas VIKOR starts with the highest criteria values and then calculates the criteria weights. The results of this research indicate that some alternatives received the same ranking using TOPSIS and VIKOR methods. The criteria used to calculate data for Waste Banks are Operational Hours, Operational Schedule, Total Customers, Total Employees, and Amount of Collected Waste. These criteria are determined based on Regulation Minister of Environment and Forestry Republic of Indonesia Number 14 of 2021 concerning Waste Management at Waste Banks.
Comparison Analysis of Graph Theory Algorithms for Shortest Path Problem Riti, Yosefina Finsensia; Iskandar, Jonathan Steven; Hendra, Hendra
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 12, No 3 (2023): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i3.1756

Abstract

The Sumba region, Indonesia, is known for its extraordinary natural beauty and unique cultural richness. There are 19 interesting tourist attractions spread throughout the area, but tourists often face difficulties in planning efficient visiting routes. From this case, it can be solved by applying graph theory in terms of searching for the shortest distance which is completed using the shortest path search algorithm. Then these 19 tourist objects are used to build a weighted graph, where the nodes represent the tourist objects and the edges of the graph describe the distance or travel time between these objects. Therefore, this research aims to compare the shortest path search algorithm with parameters to compare the shortest distance results, algorithm complexity and execution time for tourism in the Sumba area. The results of this research involve a comparison of several shortest path search algorithms, with the aim of finding the shortest distance results, algorithm complexity, and execution time for tourism in the Sumba area. Based on the test results of the five algorithms with the parameters that have been prepared, and the findings show that each algorithm has its own characteristics, the results are as follows: Dijkstra's algorithm can be used to calculate the shortest route for single-source and single-destination types. This resembles the Bellman-Ford algorithm, only the Bellman-Ford algorithm can be used simultaneously on graphs that have negative weight values. Meanwhile, the Floyd-Warshall algorithm is suitable for use on the all-pairs type. Then, the Johnson Algorithm can be used to determine the shortest path from all pairs of paths where the destination node is located in the graph. Finally, the Ant Colony algorithm to compute from a node to each pair of destination nodes.

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