Jurnal Sistem Komputer dan Informatika (JSON)
The Jurnal Sistem Komputer dan Informatika (JSON) is a journal to managed of STMIK Budi Darma, for aims to serve as a medium of information and exchange of scientific articles between practitioners and observers of science in computer. Focus and Scope Jurnal Sistem Komputer dan Informatika (JSON) journal: Embedded System Microcontroller Artificial Neural Networks Decision Support System Computer System Informatics Computer Science Artificial Intelligence Expert System Information System, Management Informatics Data Mining Cryptography Model and Simulation Computer Network Computation Image Processing etc (related to informatics and computer science)
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<![CDATA[Penerapan Algoritma K-Means dan Decision Tree Dalam Analisis Prestasi Siswa Sekolah Menengah Kejuruan ]]>
<![CDATA[Muhammad Bari Abdul Majid]]>;
<![CDATA[Yusup Mad Cani]]>;
<![CDATA[Ultach Enri]]>
<![CDATA[ Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 2 (2022): Desember 2022 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/json.v4i2.5299
<![CDATA[This study aims to determine how much influence parents' income and the distance from a student's home to school have on student achievement at SMK Tarbiyatul Ulum. Because if you know the factors that influence student achievement, steps or actions can be taken to improve student achievement. The method used in this study includes the use of clustering using K-Means and then classifying it using the Decision Tree method with a total of 157 datasets used as research material. After conducting the classification modeling using the decision tree algorithm, it was found that parents' income did not affect student achievement, but the distance from home to school did affect student achievement. Then at the evaluation stage, the decision tree algorithm is not suitable for use in predicting student achievement, because the accuracy and AUC values of this algorithm are 68% and 0.561, where these values fall into the failure category.]]>
<![CDATA[Analisis Sentimen Tindakan Pemerintah Indonesia Dalam Penanganan Covid-19 Menggunakan Metode Support Vector Machine ]]>
<![CDATA[Ariesta Damayanti]]>;
<![CDATA[Helda Ludya Safitri]]>;
<![CDATA[Rudy Cahyadi]]>
<![CDATA[ Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 2 (2022): Desember 2022 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/json.v4i2.5341
<![CDATA[Corona Virus Disease 2019 (Covid-19) which has hit the world including Indonesia since the beginning of 2020 is an outbreak that has become a serious threat to world health. The Indonesian government is taking various actions to deal with this problem, while the public, with the existence of social media, has provided many responses to these government policies. Twitter is one of the social media that is widely used by the public to convey comments in the form of responses, suggestions, to criticism of the government regarding the handling of Covid-19. The comments that appear should be used by the government as part of the reference in evaluating a policy or action taken in handling Covid-19. So that one way that can be used to deal with this is one of the methods that exist in the domain of text mining, namely sentiment analysis. This research was conducted by analyzing sentiment using the Support Vector Machine (SVM) method with the Kernel Radial Basis Function (RBF). Tweets will be classified into positive, negative and neutral sentiments, so that the percentage of each opinion category can be known. This study uses data of 600 tweets obtained from the results of scraping using a Twitter scraper. The result of this study is that the training accuracy rate is 77% in classifying positive, negative, and neutral sentiments. From the results of the data classification, it was found that most of the tweets consisted of negative sentiments.]]>
<![CDATA[Penerapan Framework Bootstrap Dalam Sistem Informasi Rekam Medis Data Posyandu dengan Metode Waterfall ]]>
<![CDATA[Yunus Anis]]>;
<![CDATA[Purwatiningtyas Purwatiningtyas]]>;
<![CDATA[Retnowati Retnowati]]>;
<![CDATA[Elsa Awalin Nur Fajrina]]>
<![CDATA[ Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 2 (2022): Desember 2022 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/json.v4i2.4833
<![CDATA[Bootstrap is a combined framework of CSS and JavaScript that is offered as an alternative among other frameworks with the intention of providing consistency to the interface development stage in building a website, one of which is the website at the Posyandu Kemuning Gajah Village. The problems that arise are related to recording visitor data manually in the register book, which is often done because there are so many things that must be recorded such as weight, developmental data for mothers, children under five, maternal development data, other personality data related to pregnant women and toddlers visiting posyandu. . For this reason, it is necessary to support an information system for recording participant activities so that the number of participants does not need to be developed in data processing and re-accessing so that data redundancy does not arise. The system that will be created using the bootstrap framework includes the participant registration process and data processing for posyandu participants, so that they are able to manage data and generate data reports in a valid and correct manner. Testing with the blackbox method shows that the entire system built from the implementation of the login form to the print report shows that everything has been successfully implemented in the system.]]>
<![CDATA[Sistem Pendukung Keputusan Rekomendasi Dalam Pemilihan Pemeliharaan Ikan Air Tawar Ekonomis Menerapkan Metode Additive Ratio Assesment (ARAS) ]]>
<![CDATA[Agus Iskandar]]>
<![CDATA[ Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 2 (2022): Desember 2022 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/json.v4i2.5176
<![CDATA[Developing a business in fresh water is a promising business, because food ingredients such as fresh water fish are always needed by every community. Freshwater fish are fish that live in fresh water, such as living in lakes, rivers and so on. if someone wants to build a freshwater business, then the type of freshwater fish that is suitable and the easiest to maintain must be chosen. The many types of freshwater fish make prospective business owners confused in choosing which type of water fish is suitable for business. In helping the owner solve these problems, a decision support system is needed. A decision support system is a system developed on a computer, where the development uses computer-based steps or methods. SPK requires a method in its application. The method used in this study is the ARAS method. The ARAS method is an acronym for the Additive Ratio Assessment Method (ARAS). The ARAS method is the method used in ranking each alternative by using the reference, namely the criteria as the calculation material. By using the SPK using the ARAS method, the result is that by using the ARAS method, the selection of freshwater fish that is highly recommended to be kept is Alternative A1 with the type of fish, namely catfish as the best alternative.]]>
<![CDATA[Sistem Pendukung Keputusan Seleksi Tenaga Fasilitator Lapangan BSPS Menggunakan Metode Multi Factor Evaluation Process ]]>
<![CDATA[Nur Oktavin Idris]]>;
<![CDATA[A. Mulawati Mas Pratama]]>;
<![CDATA[Muliati Badaruddin]]>
<![CDATA[ Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 2 (2022): Desember 2022 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/json.v4i2.5303
<![CDATA[Field facilitator workers shall guide the Self-Help Housing Stimulant Assistance Program (BSPS) recipients intensively, either in technical matters or the fund use realization process during construction terms. Guidance is given from planning, implementing a construction, and forming an assistance recipient community group that can construct decent housing independently. Accordingly, field facilitator workers are imperative to guide the BSPS recipient community. Public Works and Spatial Planning Office in Gorontalo is still selecting field facilitator workers manually, bringing on assessment errors in the selection process, e.g., selecting field facilitator workers that do not fulfill the requirement. Additionally, the sheer number of applicants overwhelms staff as they have to face off piling files of applicants. It brings about a longer selection process. As such, a systematic selection process based on the determined criteria is important. Later, it can act as a reference. It is called a decision-supporting system. Our decision-supporting system aims to help make decisions to select field facilitator workers guiding the BSPS recipient community using the Multi-Factor Evaluation Process (MFEP) method. The results point out Bambang achieved the highest final score of 87.675. Hence, MFEP in the supporting system is a recommended method to make decisions to select field facilitator workers guiding the BSPS recipient community in building decent housing.]]>
<![CDATA[Analisis Sentimen Komentar Youtube Tentang Relawan Patwal Ambulance Menggunakan Algoritma Naïve Bayes dan Decision Tree ]]>
<![CDATA[Abd Wahid]]>;
<![CDATA[Galuh Saputri]]>
<![CDATA[ Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 2 (2022): Desember 2022 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/json.v4i2.4941
<![CDATA[The presence of the ambulance patrol is sometimes considered disturbing by the community, many people's opinions are still pro and contra about the actions carried out by civilian ambulance patrol volunteers because they are considered illegal and sometimes also arrogant. In this study. the researchers wanted to know the opinions and responses of the public about the actions taken by civilian ambulance patrol volunteers. The method used in this study is to perform sentiment analysis with data mining techniques to find the polarity of sentences in a document using the Naïve Bayes and Decision Tree algorithms. The initial steps in this research were collecting comment data by scraping YouTube comments using API Key Youtube V3, followed by manual data labeling, data cleaning, data preprocessing, and word weighting using TF-IDF. From the overall results of testing with 600 training data, the Naïve Bayes algorithm has a higher accuracy value of 66.72% while the Recall value is 64.98%. Testing with the Decision Tree algorithm in this study has a higher Recall compared to Naïve Bayes. %. From the results of the YouTube comment dataset used in this study, it can be concluded that the Naïve Bayes algorithm has a higher accuracy value than the Decision Tree algorithm, so it can be concluded that Naïve Bayes has the best accuracy in the YouTube comment dataset used in this study.]]>
<![CDATA[Analisis Sistem Pendukung Keputusan Dalam Rekomendasi Kenaikan Pangkat PNS Menggunakan Kombinasi Metode TOPSIS dan SAW ]]>
<![CDATA[Anisa Agustina Melani]]>;
<![CDATA[Lukman Bachtiar]]>
<![CDATA[ Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 2 (2022): Desember 2022 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/json.v4i2.4471
<![CDATA[PNS promotion is an award given to Civil Servants who have met the specified requirements as well as for work performance and service to the country. a Civil Servant is required to continue to be able to apply for promotions periodically to the highest level, so that within a certain period of time every civil servant gets the opportunity to apply for promotions. Similar to the scope of the East Kotawaringin Regional Secretariat, civil servants have the right to apply for a promotion every 4 years. The Staffing of the Regional Secretariat of the Kotim has difficulties in selecting the file for promotion proposals because of the large number of employees who propose promotions and the files and provisions gathered by civil servants must be managed immediately so that they are submitted to the BKPSDM. Researchers offer a decision support system with TOPSIS and SAW methods. The combination of the two methods serves to produce optimal decisions in accordance with predetermined criteria. This study uses 5 alternatives and 4 criteria. In this study, the alternatives consisted of Kurniawan Wibowo, Idris Sugiono, Nuringsih Sujati, Meuthia Rakhmasari, and Maulana. Of the five alternatives, those with the highest final score were Idris Sugiono, Nuringsih Sujati and Meuthia Rakhmasari with a value of 0.427 or 42.7%.]]>
<![CDATA[Budidaya Tanaman Sayuran Menggunakan Sistem Pendukung Keputusan Dengan Metode Profile Matching ]]>
<![CDATA[Dhella Amelia]]>;
<![CDATA[Revi Gusriva]]>
<![CDATA[ Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 2 (2022): Desember 2022 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/json.v4i2.5338
<![CDATA[Cultivating vegetable plants is very important for farmers. In the cultivation of vegetable plants, there are problems that are often faced by farmers, one of which is the lack of information about natural conditions and limited knowledge of farmers. so it is necessary to have an auxiliary media in the form of a system that can provide solution information at any time. Selection of plants that are not suitable will get unsatisfactory results. Farmers must know that what needs to be considered in cultivating vegetable crops is compatibility with natural conditions. This research builds a web-based decision support system software regarding vegetable cultivation that meets the criteria using the profile matching method as a tool to facilitate the decision-making process with several comparison criteria, namely: temperature, sunlight, rainfall and humidity, altitude, harvest time, marketability, susceptibility to disease, and level of care. This application is made web-based using PHP as the programming language and MySQL as the data storage. The purpose of this application is to provide effective and efficient information to farmers in making decisions and alternatives that are in accordance with the natural conditions of the area. The result of making this system is that farmers make the right decisions when cultivating vegetables based on the criteria.]]>
<![CDATA[Analisis Sentimen Terhadap Program Kampus Merdeka Menggunakan Naive Bayes Dan Support Vector Machine ]]>
<![CDATA[Irma Putri Rahayu]]>;
<![CDATA[Ahmad Fauzi]]>;
<![CDATA[Jamaludin Indra]]>
<![CDATA[ Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 2 (2022): Desember 2022 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/json.v4i2.5381
<![CDATA[In order to prepare students to face the rapid development of technology, changes in work life and skills, students must be better prepared to face the progress of the times. Universities must be able to carry out innovative learning processes so that students achieve optimal learning outcomes which include aspects of knowledge, skills and attitudes. So the MBKM program was launched to answer these demands. However, MBKM has pros and cons in its implementation, so it is necessary to analyze and evaluate policies to improve performance through feedback from the public by conducting sentiment analysis of MBKM policies on twitter users from 2019 to 2022 with the hashtag #kampusmerdeka. This study used the Naïve Bayes and SVM algorithms to determine accuracy based on sentiment classification. The data used 1118 data with positive sentiment 618 data and negative sentiment 500 data. This study resulted in an accuracy of 86%, precision of 87% and recall of 80% with testing data using the Naïve Bayes algorithm. Then using the linear kernel SVM algorithm with the same testing data resulted in accuracy of 93%, precision of 100% and recall of 84%. Therefore, it is important to conduct studies to improve the MBKM program so that its implementation is clearly in accordance with existing procedures.]]>
<![CDATA[Optimasi Akurasi Klasifikasi Pada Prediksi Smokte Detection dengan Menggunakan Algoritma Adaboost ]]>
<![CDATA[Amin Nur Rais]]>;
<![CDATA[Warjiyono Warjiyono]]>
<![CDATA[ Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 2 (2022): Desember 2022 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/json.v4i2.5154
<![CDATA[The problem of fire is a threat to nature and the environment. To deal with fire incidents, a smoke detector was created and developed in combination with an IoT device so that incident data can be recorded properly where the recorded data will be used as a reference for increasing the accuracy of early detection. Increasing the accuracy of smoke detectors so that they can be combined with artificial intelligence technology. This research proposes prediction optimization using the adaboost algorithm combined with the naïve Bayes classification algorithm with a measurement matrix based on accuracy, recall, and precision. The results showed that using the adaboost algorithm could increase the resulting accuracy value with a value of 0.987. If you look at the evaluation from the precision side, it also shows that the use of the adaboost algorithm can increase the precision value with a value of 0.971. But the recall evaluation showed that without boost it got a better score with a value of 0.995]]>
