SISFOTENIKA
Jurnal Ilmiah SISFOTENIKA diterbitkan oleh LPPM STMIK Pontianak dan IndoCEISS. Frekuensi Terbit Tengah Tahunan (2 kali dalam setahun, yaitu bulan Januari dan Juli). Topik yang akan dipublikasikan oleh jurnal SISFOTENIKA berhubungan dengan teknologi informasi, komunikasi dan komputer yang berbentuk kumpulan/akumulasi pengetahuan baru, pengamatan empirik atau hasil penelitian, dan pengembangan gagasan atau usulan baru.
Articles
239 Documents
<![CDATA[Skin Cancer Classification Using Random Forest Algorithm ]]>
<![CDATA[Nurul Khasanah]]>;
<![CDATA[Rachman Komarudin]]>;
<![CDATA[Nurul Afni]]>;
<![CDATA[Yana Iqbal Maulana]]>;
<![CDATA[Agus Salim]]>
<![CDATA[ SISFOTENIKA Vol 11, No 2 (2021): SISFOTENIKA ]]>
Publisher : <![CDATA[STMIK PONTIANAK ]]>
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DOI: 10.30700/jst.v11i2.1122
<![CDATA[Skin cancer is an excessive lump of skin tissue that affects the skin, has an irregular structure with cell differentiation at various levels in chromatin, nucleus and cytoplasm, is expansive, infiltrative to damage the surrounding tissue, and metastasizes through blood vessels and lymph vessels. Diagnosis of skin cancer by biopsy process is considered less effective because it costs a lot and can injure human skin as a sample. For that, we need a system for classification of skin cancer types that are effective and accurate. The application of machine learning has been widely used in the health sector. One of the machine learning methods is Random Forest. In this study, the histogram color feature extraction will be carried out, the hue moment shape extraction, and the haralick texture extraction. Furthermore, the image will be classified using the Random Forest algorithm. The best accuracy value obtained from the histogram feature extraction process and classification with Random Forest is 0.850822. The novelty of this research is the use of more diverse feature extraction and better accuracy results than previous studies. Future research is expected to use deep learning algorithms with CNN (Convolutional Neural Network) architecture to get better accuracy results and add application designs for the application of models that have been formed in the study so that they can be directly applied by the medical team.]]>
<![CDATA[Implementation of Scrum Method on MVC-Based Sembakoqu Website ]]>
<![CDATA[Nifea Kusumawardhani]]>;
<![CDATA[Agung Triayudi]]>;
<![CDATA[Benrahman Benrahman]]>
<![CDATA[ SISFOTENIKA Vol 11, No 1 (2021): SISFOTENIKA ]]>
Publisher : <![CDATA[STMIK PONTIANAK ]]>
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DOI: 10.30700/jst.v11i1.1067
<![CDATA[Sembakoqu is a personal online distributor website for selling various kinds of food. With prices and foodstuffs that always go up and people's purchasing power decreases because it is necessary to come to the distributor's place. The purpose of this study is to create an online distributor website to make it easier for the public to find savings in their household and business raw material expenses. In this research, the development of the website system uses the Scrum method which is part of the agile method which can produce good quality software according to user desires. This method has a flexible nature that can be applied to the development of the Sembakoqu system by implementing a computerized payment and reporting system. The testing phase used on this website uses the blackbox method by emphasizing testing on functionality. For application development suggestions that can be carried out in further research, namely the system can be developed into a mobile application, so that consumers can order products on their smartphone devices.]]>
<![CDATA[Comparison of Machine Learning Algorithms for Classification of Drug Groups ]]>
<![CDATA[Purwono Purwono]]>;
<![CDATA[Anggit Wirasto]]>;
<![CDATA[Khoirun Nisa]]>
<![CDATA[ SISFOTENIKA Vol 11, No 2 (2021): SISFOTENIKA ]]>
Publisher : <![CDATA[STMIK PONTIANAK ]]>
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DOI: 10.30700/jst.v11i2.1134
<![CDATA[The stages of clinical trials need to be carried out when determining a new drug group for patient management. This stage is considered quite long and requires a lot of money. Medical record system data continues to grow all the time. The data can be analyzed to find a pattern of grouping drugs used in the treatment of patients based on their body condition. Utilization of artificial intelligence (AI) technology can be done to classify drug data used during patient care. Machine learning as a branch of science in the AI field can be a solution to deal with these problems. Machines will learn, analyze, and predict drug requirements quickly with less cost. Based on related research, we contribute to comparing the performance of the best machine learning algorithms that can be used as drug classification models. The results of this study are the accuracy of the support vector machine algorithm is 94.7% while the random forest and decission tree algorithms are 98.2%. This shows that the algorithms that can be considered as a drug classification model are random forest and decision tree. This model needs to be tested on a larger dataset to produce the best accuracy value.]]>
<![CDATA[Measuring Body Temperature Based Internet of Things (IoT) Using Esp8266 and Firebase ]]>
<![CDATA[Indra Gunawan]]>;
<![CDATA[Aris Sudianto]]>;
<![CDATA[Muhamad Sadali]]>
<![CDATA[ SISFOTENIKA Vol 11, No 1 (2021): SISFOTENIKA ]]>
Publisher : <![CDATA[STMIK PONTIANAK ]]>
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DOI: 10.30700/jst.v11i1.1060
<![CDATA[Measuring the body temperature can be the basis for determining the health level of a person which increasing the body temperature can also be a reference to find out whether a person infection early symptoms of a disease, both fever and cases as currently occurring, namely as an indicator of determining whether someone is indicated to be infected with the Covid 19 virus, which is currently a pandemic in the various countries. Initially, measurement the body temperature was carried out massively using the body temperature measuring device circulating in the community using a thermometer that was already standardized by SNI, wherein the measurement process like this some obstacles or problems occur, which the officer being infected the risk by virus covid19 and will cause increasing in the cases. In this study, a tool was made to measure human body temperature based on the internet of things technology, which then the measurement data will be sent to an Android smartphone application based monitoring via the internet. This tool uses the MLX-90614 sensor device [1] to detect temperature, after that the data will be processed by Nodemcu ESP8266 and stored on the Firebase server before the data will sent to the user's monitor. The measurement result data will be displayed with the android application and if the temperature data exceeds the normal limit or> 37.50C, the system will send a sound signal alarm via a buzzer. The results of this study can achieve an accuracy level of about 95% from value of data the measuring temperature using device standards SNI and data display to the application monitoring need about 3 seconds.]]>
<![CDATA[ClausTher VR: Claustrophobia Therapy using Virtual Reality ]]>
<![CDATA[Joe Yuan Mambu]]>;
<![CDATA[I Gede Purnawinadi]]>;
<![CDATA[Renaldy Luntungan]]>;
<![CDATA[Septian Mottoh]]>
<![CDATA[ SISFOTENIKA Vol 11, No 2 (2021): SISFOTENIKA ]]>
Publisher : <![CDATA[STMIK PONTIANAK ]]>
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DOI: 10.30700/jst.v11i2.1126
<![CDATA[Fear or anxiety about a particular situation or object is called phobia, one of the phobias that exists today is Claustrophobia which is a phobia of a closed or small room. The current Claustrophobia therapy method is still traditional, namely by placing the patient in a place that will trigger the patient’s Claustrophobia. This study aims to produce a therapeutic aid and diagnosis of Claustrophobia with Virtual Reality Exposure Therapy method that uses Android-based Virtual Reality and Photogrammetry technology that can be used by medical experts or therapist when conducting therapy to Claustrophobia patients. The research method used is prototyping model. The way to collect data that will be used is by interview and application testing. Researchers used the Unity3D Engine software to create Virtual Reality application and Agisoft Metashape software to create Photogrammetry objects. The application is expected to facilitate the Claustrophobia patients and help people to predict the level of Claustrophobia suffered. The app produced on this research was able to produce the expected virtual environment and had a limited test to user and had similar reaction to a real room. For future research additional rooms and exploration mode may be added, as well as further evaluation to see how this application can be used for therapy tools.]]>
<![CDATA[Designing a Visual Novel Game in Nusantara Folklore 'The Origin of Lake Toba' using Renpy Visual Novel Engine ]]>
<![CDATA[Noprita Elisabeth S]]>;
<![CDATA[Rani Hermita]]>
<![CDATA[ SISFOTENIKA Vol 11, No 1 (2021): SISFOTENIKA ]]>
Publisher : <![CDATA[STMIK PONTIANAK ]]>
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DOI: 10.30700/jst.v11i1.1054
<![CDATA[Public knows about the folklore of the archipelago in Indonesia through stories told directly by parents and their families, passed down orally from parents to children and their ancestors to future generations. Likewise, the folklore of the origin of Lake Toba. The folklore of the archipelago seems to be slowly disappearing because it is only passed down orally and is less desirable and does not rule out being forgotten and extinct. This is what makes the writer decide to conduct research on the folklore of the archipelago through the media of games, namely visual novels with the story of the origin of Lake Toba as the object. The researcher wants to make an application in the form of animation with the help of a program that wants to be enjoyed by many people and can also be used as a learning medium.The game application that will be produced will later be made using the Ren'Py Novel Visual Engine application and the research method that the author will use is an extreme programming as a management system with the following stages: Exploration Phase, Planning Phase, Iteration Phase, Production Phase, Maintenance Phase and Final Publication Stage ( Death Phase), with the existing tools can make the application of the story of the origin of Lake Toba well, then for future research to make it in a 3-dimension version]]>
<![CDATA[Cluster Evaluation Weighing Intercomparison Data with Self Organizing Maps Algorithm ]]>
<![CDATA[Arif Fajar Solikin]]>;
<![CDATA[Kusrini Kusrini]]>;
<![CDATA[Ferry Wahyu Wibowo]]>
<![CDATA[ SISFOTENIKA Vol 11, No 2 (2021): SISFOTENIKA ]]>
Publisher : <![CDATA[STMIK PONTIANAK ]]>
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DOI: 10.30700/jst.v11i2.1153
<![CDATA[Laboratory intercomparison is one of method to determine the ability and assess the performance of a laboratory. Laboratory performance can be seen from the evaluation of the En ratio’s value, which is a comparison between the difference in the value test of the participant's laboratory with reference’s laboratory and the difference in the square root of the uncertainty value form participant's laboratory and reference’s laboratory. The laboratory is declared equivalent if the En value is in the range of En ≤|1|. Intercomparisons evaluation can also be done by utilizing one of the data mining technologies in the form of clustering. Clustering is done by using self-organizing maps algorithm, which is an unsupervised learning algorithm. The advantage of clustering in evaluating intercomparation data lies in its ability to group data into several clusters that have closeness or similarity in characteristics / traits / characters of data, making it easier for intercomparation organizers to provide analytical recommendations for improving laboratory performance. Intercomparation data are grouped based on the homogeneity between members in one cluster and heterogeneity among the clusters. To get the best number of clusters, evaluation is carried out through three testing methods, pseudo-F statistic, icdrate and davies bouldin index. From several experiments, the largest pseudo-F statistic value was 167.53, the smallest icdrate value was 0.071 and the smallest DBI value was 0.053 for the 1000 g artifact. As for the 200 g artifact, the largest pseudo-F statistic value was 104.86, the smallest icdrate value was 0.289 and the smallest DBI value was 0.306]]>
<![CDATA[Design Web-Based Registration And Data Management Of Student Thesis Information System ]]>
<![CDATA[Rosiyati MH Thamrin]]>;
<![CDATA[Rian Andriani]]>
<![CDATA[ SISFOTENIKA Vol 11, No 1 (2021): SISFOTENIKA ]]>
Publisher : <![CDATA[STMIK PONTIANAK ]]>
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DOI: 10.30700/jst.v11i1.1111
<![CDATA[The thesis data management process at STIMIK Sepuluh Nopember Jayapura currently still uses Microsoft Excel, so the processing takes a lot of time, another obstacle that arises is the title submission process, where students have to come to campus to submit titles then announcements still use the announcement board so that students who want to get the information must go to the STIMIK Sepuluh Nopember campus. The purpose of making the system is to solve the above problems and at the same time make it easier for students in the process of submitting titles. The design of this system uses the waterfall method, while the data collection method uses several methods such as observation, interviews and literature study. For web development using the PHP programming language. The final result of this design is a web that can be used by students to submit titles, see a list of thesis titles that have been taken and so on. While the output from the web that is made is a list of student thesis titles STIMIK Sepuluh Nopember Jayapura and announcements such as approval of titles submitted, supervisors, examiners and payment issues. ]]>
<![CDATA[Implementation of Apriori Algorithm for Determining Product Purchase Patterns ]]>
<![CDATA[Nindy Devita Sari]]>;
<![CDATA[Bambang Soedijono W A]]>;
<![CDATA[Asro Nasiri]]>
<![CDATA[ SISFOTENIKA Vol 11, No 1 (2021): SISFOTENIKA ]]>
Publisher : <![CDATA[STMIK PONTIANAK ]]>
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DOI: 10.30700/jst.v11i1.1033
<![CDATA[In this study, the implementation of Data Mining association method using Apriori algorithm to determine product purchase pattern. Data obtained from the sales transaction data in the Toko Jaya Putra Bumi Agung in the form of a purchase note that will then be implemented using Apriori algorithm. The data mining technique used is the association rule method to know the pattern between items one and other items using support and confidence. In this study of the calculation process with Apriori algorithm obtained minimum value of support 50% and minimum confidence value 70% then resulting tendency of products purchased by consumers ie if buying cooking oil then buy eggs with confidence 75%. If buying Sumendo coffee then buy sugar with confidence 77.8%. This research is expected to be helpful and useful for the owner of Toko Jaya Putra Bumi Agung to predict and analyze the combinations of what kinds of products are often purchased by consumers simultaneously. For further research need to be developed again by combining other data mining algorithms. Preferably the use of datasets that are used will be better to use larger datasets so that they can obtain higher accuracy values.]]>
<![CDATA[Decision Support System for Online Learning Media Selection During the Pandemic Period ]]>
<![CDATA[Fitriyani Fitriyani]]>;
<![CDATA[Yuyi Andrika]]>;
<![CDATA[Melati Suci Mayasari]]>;
<![CDATA[Anisah Anisah]]>
<![CDATA[ SISFOTENIKA Vol 11, No 2 (2021): SISFOTENIKA ]]>
Publisher : <![CDATA[STMIK PONTIANAK ]]>
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DOI: 10.30700/jst.v11i2.1127
<![CDATA[Online learning media is one of the uses of technology in the form of software. During the COVID-19 pandemic, the government issued a policy for distance learning, so to facilitate the teaching and learning process between teachers and students who are in different places, online learning media are needed that can be used by educators or students. For this reason, researchers conducted research on online learning media. Alternatives used by researchers include google classroom, zoom free, google meeting free, and WhatsApp group. The criteria used by the researcher are easy to access, according to purpose, time limit for access, interactivity. The method used is the SAW (Simple Additive Weighting) method. This method is a method for calculating the weights of the criteria and alternatives so that the final weight of each alternative is obtained so that it is known which alternative has the highest value weight that can be recommended to decision makers. From the research results obtained WhatsApp group with a weight of 0.75, google classroom with a weight of 0.74, google meeting free with a weight of 0.67, zoom free with a weight of 0.55. It is necessary to do further research using different methods or combining several methods so that the research conducted by this researcher is not the end of research with the same discussion.]]>
