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Akurasi dalam Mengidentifikasi Talenta Siswa Lanjutan Menggunakan Metode Multifactor Evaluation Process (MFEP) Riski Randa Hidayatullah; Sumijan Sumijan; Yuhandri Yunus
Jurnal Informasi dan Teknologi 2020, Vol. 2, No. 4
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v2i4.112

Abstract

Talent is a natural ability to acquire knowledge and skills, both general and specific. Basically, each individual has different talents. moreover supported by the appropriate talents, will bring passion and give pleasure in learning or living it. Providing an overview to students of who they are through their talents and interests so that what job opportunities they can initiate after graduating from school are qualitative data related to the research focus, namely the process of identifying student talents in the Educator Room of SMAN 1 Linggo Sari Baganti . There are at least nine intelligences or talents that a person may possess, namely logical mathematical, linguistic / verbal, visual spatial, musical, bodily-kinesthetic, interpersonal, intrapersonal, natural, and moral / spiritual. Sources of data in the study were obtained from primary data, namely data obtained directly from data sources, namely the people involved in the process of identifying talents in the Educator Room of SMAN 1 Linggo Sari Baganti. In addition, the data source in this study is in the form of secondary sources, for example in the form of documents related to curriculum implementation. Furthermore, the data is processed using the Multifactor Evaluation Process (MFEP) method. MFEP is a quantitative method that uses a 'weighting system' and this study uses the VB.NET 2017 language program and MySQL. The processing stages are determining criteria, calculations and processes so as to produce decisions. The sum above results, there are 10 students whose data is processed and produces a total calculation or accuracy of 86.51%. So that this research can be a reference in making the right decision at SMAN 1 Linggo Sari Baganti School.
Prediksi dan Klasifikasi Buku Menggunakan Metode Backpropagation R Rahmiyanti; Sarjon Defit; Yuhandri Yunus
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i3.116

Abstract

Students of SMP Negeri 2 Lengayang have different interests in determining the books they are interested in, so that the library often has difficulty determining the books that are most entered by students, this is because they have not used the right system in determining the type and number of books, only based on the estimated number. Students and subjects only, as a result school students stock books of the books they want to borrow. Based on the above, a method is needed to predict and classify the amount of book stock in the future. The data used is a recap of monthly book lending, from 2018 to 2020 in the third month, with a total of 1653 transactions and 5 types of books processed, then the data is analyzed using the Backpropogation method. The results obtained are using a 5-3-1 pattern with a learning rate of 0.01, a goal of 0.01, the number of input units for the Weapon layer 5, the number of units in the hidden layer and the number of output layer units that are placed on 1 layer, and to carry out training using two phases namely feedforward and backpropagation phases. It is removed from this research that the backpropagation method can provide a classification prediction of the number of books that must be provided in the following year based on the number of data entered or the number of data entered.
Sistem Pakar dalam Mendiagnosis Penyakit Mata dengan Menggunakan Metode Forward Chaining Budi Permana Putra; Yuhandri Yunus; Sumijan
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i3.122

Abstract

The eye is one of the organs in the body that has an important role in human life, because the eye is one of the organs that has a function as vision in carrying out every activity. Eye health really needs to be maintained by diligently consulting or having your eyes checked by a doctor so that vision remains clear and there are no eye problems when looking at objects around us. However, eye health is often neglected, so that many various diseases can attack the eye. If not handled properly, diseases that attack the eye can cause visual disturbances and lead to blindness. Therefore, the eye must be kept healthy and kept clean because it is a very important organ of the human body. The purpose of building this expert system is to assist the public in diagnosing eye diseases from the symptoms that are being felt. This expert system will be a way out of eye problems that are suffered by the community, In this way people no longer have trouble going to the doctor. All data and facts to be processed are obtained from an expert, the method used in diagnosing this eye disease is the forward chaining method to apply the rules of the 28 symptoms and 8 diseases described by the expert. The results of the diagnosis using the Forward Chaining method is a very good level of accuracy in determining the type of eye disease that is suffered by the community and can provide early prevention for users who use this expert system.
Prioritas Pengadaan Buku Berdasarkan Data Kerusakan dan Kehilangan Menggunakan Metode Simple Additive Weighting Syahid Hakam Abdul Halim; Yuhandri Yunus; Sumijan
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i3.128

Abstract

Supplying book which is estimated each year can fulfill the availability and requirement of books. With supplying book that has been done, it can increase the students reading interest in teaching and learning process. The frequency of using book in learning cause the book will be damaged or lost. The aim of this research is to find out the priority of supplying book based on damaged and lost data so that it can be used as a reference to determine the main priority in supplying book. If this priority can be determined, it will give the effect towards madrasah as well for librarian. The effect for madrasah is to give information about priority supplying book at school’s library. For librarian, the effect could be concluded as consideration in making decision to supplying the book at school’s library. To analyze the research, the researcher used 40 broken and lost data. Which is the broken data was obtained from the librarian of MAN 2 Kota Padang Panjang. In this research, the researcher used the Simple Additive Weighting with PHP programming and MySql database. The main concept of Simple Additive Weighting method is to find out the total rating performance for each alternative. The experiment of broken and lost data is done based on the alternative book which is normalized by attribute criteria (benefit or cost). The broken and lost data criteria was consisted of 4 criteria, they are 1 book’s stock criteria, 2. Book’s sheets criteria, 3. Book’s cover criteria, and 4. Book’s code criteria. The result ranking towards Simple Additive Weighting method based on 40 experiment data was found that 3 alternative books was obtained as priority in supplying book, they are Akidah Akhlak XI, Al Quran Hadist XI, and Ushul Fikih XI, which the Akidah Akhlak XI is the main priority.
Klasterisasi Penempatan Siswa yang Optimal untuk Meningkatkan Nilai Rata-Rata Kelas Menggunakan K-Means Yusma Elda; Sarjon Defit; Yuhandri Yunus; Raemon Syaljumairi
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i3.130

Abstract

The implementation of learning by teachers can measure the quality of schools and students. Schools with diverse student backgrounds need to take strategic steps in managing learning to get optimal learning outcomes. Good learning designs and techniques can motivate students' interest in learning. The teacher's role is very important in managing learning to create an effective teaching and learning process. Data Mining or also known as Knowledge Discovery in Database (KDD) is the process of extracting knowledge from large data to find new patterns to get new knowledge and information. Data Mining technology is used to explore existing knowledge in the database. One of the methods used in data mining is clustering with the K-Means algorithm. This study aims to conduct student clustering to obtain a balanced class composition in order to improve the quality and student learning outcomes as seen in the increasing in the class average score. The data processed in this study came from the main school data as many as 90 students of the XI class of Computer Network Engineering Skills Competency at SMKN Negeri 2 Padang Panjang in the 2020/2021 school year. The variables used in data processing are student scores, parents' income and the distance from where students live to school. The student clustering calculation using K-Means succeeded in grouping 90 students into 3 clusters where cluster 1 totaled 47 students, cluster 2 totaled 10 students and cluster 3 totaled 33 students. Each member of the cluster will be divided evenly into 3 groups studying to get a balanced class composition. This research can be used as a basis for decision making by schools in clustering student placements to improve learning outcomes. By the increasing in the grade point average, the school average score will also increased.
Sistem Pakar Dalam Menganalisa Penyakit Perut Dengan Menggunakan Metode Certainty Factor Annisa Amalia; Gunadi Widi Nurcahyo; Y Yuhandri
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i4.159

Abstract

Food technology that is increasingly advanced makes people tend to consume fast food, as well as foods that contain chemicals. This causes the tendency of an unhealthy lifestyle and becomes one of the factors that cause stomach disease. Stomach disease can be experienced at the age of children to adulthood. Unhealthy lifestyle means eating patterns that are initially consumptive on healthy foods and then turn into consumptive foods that are less healthy. Not only food, rarely exercise is also likely to cause pain in the stomach. Diagnosing stomach disease is still carried out by conducting face-to-face consultations with health workers, which can take a long time and cost a lot of money. Lack of information on stomach disease sufferers about the symptoms of stomach disease, causes patients not to know the type of stomach disease they are experiencing. This is the goal of research that will build an expert system software that is expected to be able to analyze stomach diseases and help the community, stomach sufferers and health workers in diagnosing types of stomach diseases. The method used in this study is Certainty Factor (CF) or the certainty value of a disease. Expert system software development is done by analyzing software requirements, system user needs. The dataset of this study is the symptoms and types of stomach diseases that occur at the Salido Health Center. The result of the system built is the result of the diagnosis of stomach disease with the percentage of certainty value from the calculation using Certainty Factor. The system will also provide information about the description, causes and prevention of the types of stomach diseases diagnosed. With the construction of an expert system of stomach diseases, it is hoped that this research can be a reference for users in diagnosing stomach diseases. The accuracy results obtained after testing the system is 80%.
Identifikasi Objek pada Citra Thorax X-Ray Pasien COVID-19 dengan Metode Contrast Limited Adaptive Histogram Equalization (CLAHE) Dodi Andre Putra; Jufriadif Na` am; Yuhandri
Jurnal Informasi dan Teknologi 2022, Vol. 4, No. 1
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v4i1.184

Abstract

Chest X-Ray radiography produces digital radiographic images of the chest area such as the lungs, heart, and ribs. This image can visualize the lung condition of COVID-19 patients. Examination of the lung condition of COVID-19 patients with X-Ray is easier, cheaper, and widely available in hospitals than other radiographic techniques. However, the results of the X-Ray radiography digital image have poor quality, so they need to be improved. Low image contrast is a factor in the difficulty of identifying thorax images of COVID-19 patients. Increase the contrast of the low thorax image of COVID-19 patients with Contrast Limited Adaptive Histogram Equalization (CLAHE) so that it is easier to observe concretely and more clearly. The images that were processed in this study were 100 thorax images of COVID-19 patients sourced from the radiology department of Bhayangkara Hospital, Padang Indonesia. Furthermore, the image is processed using digital image processing using Matlab software. The processing stages of the thorax image are converted into grayscale form. The resulting grayscale image is continued with contrast processing using the CLAHE method with Uniform, Rayleigh and Exponential distribution types. The calculation of the Peak Signal to Noise Ratio (PNSR) and Mean Square Error (MSE) values of the image results from the processing of each type of CLAHE was continued. The results of testing all images can be visually improved in contrast quality. The average MSE CLAHE Uniform, Rayleigh and Exponential results were 27.68, 25.86 and 26.33, respectively. The average values of CLAHE Uniform, Rayleigh and Exponential PNSR > 30 dB are 112.32 dB, 171.95 dB and 151.90 dB, which means the CLAHE image is similar to the original image. CLAHE Rayleigh gives the best results in terms of quality and quantity with a total of 85 images or an accuracy value of 85%, while CLAHE Exponential and CLAHE Uniform are 15% and 0%, respectively.
Prediksi Harga Emas dengan Menggunakan Metode Naïve Bayes dalam Investasi untuk Meminimalisasi Resiko Mohammad Guntur; Julius Santony; Yuhandri Yuhandri
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 2 No 1 (2018): April 2018
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (502.687 KB) | DOI: 10.29207/resti.v2i1.276

Abstract

The high low price of gold influenced by many factors such as economic conditions, inflation rate, supply and demand and much more. The Naïve Bayes algorithm is capable of generating a classification that is used to predict future opportunities. By using the Naïve Bayes Classifier algorithm obtained a prediction of gold prices that can help decision makers in determining whether to sell or buy gold. By using the Naïve Bayes Classifier algorithm obtained a prediction of gold prices that can help decision makers in determining whether to sell or buy gold. Gold data will be processed using Rapidminer software. Stages of processing are reading training data, calculating the mean and standard deviation, entering the test data and finding the density value of gauss and then looking for probability value. Based on the calculation that has been done, Naïve Bayes Classifier method is able to predict the price of gold for 1 day ahead or every day. With the results of this calculation is expected to help gold investment actors in increasing accuracy to predict gold prices for decision making.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN GURU PRODUKTIF PESERTA PELATIHAN ASESOR KOMPETENSI LSP P1 SMK SWASTA DWIWARNA MEDAN MENGGUNAKAN METODE THE EXTENDED PROMETHEE II (EXPROM II) Dwika Assrani; Mesran Mesran; Ronda Deli Sianturi; Yuhandri Yuhandri; Akbar Iskandar
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 2, No 1 (2018): Peranan Teknologi dan Informasi Terhadap Peningkatan Sumber Daya Manusia di Era
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v2i1.922

Abstract

Vocational schools that have been licensed from BNSP to LSP P1 (first party professional certification institute) are schools that have been able to carry out their own competency certification exams for their students and later a competency assessor who will test and declare the eligibility of the students, competency assessors are productive teachers who have participated in and been given training by the government, in that training the schools choose from the number of productive teachers from each department to become competency assessor trainees in accordance with predetermined criteria so a decision support system is needed so there is no gap in the selection of productive teacher assessor training participants, a vocational school that has become a P1 LSP must have a competency assessor and is a requirement to be a P1 LSP. one of the solutions to the problem is the right one by using the Decision Support System (SPK). Decision Support System (DSS) can help the school in making the decision to choose the productive teacher of the appropriate assessor training and improve the efficiency of the decision. The Extended Promethee II (EXPROM II) is a development of the Promethee II method based on the ideal and anti-ideal solution. Promethee II itself is a method of making decisions on the function of preferences with problems through an outranking approach (ranking) or is a multicriteria analysis, comparing one alternative to another and calculating the alternative gap in pairs so as to produce an output that is alternative ranking based on the highest value.Keywords: Competitive Assessor LSP P1, SPK, The Extended Promethee II
Satisfaction Level of BPJS Kesehatan Participants Using the C4.5 Algorithm Irvan Okta Mazhona; Yuhandri
SYSTEMATICS Vol 2 No 3 (2020): December 2020
Publisher : Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Patient satisfaction is an important thing in a hospital service. The level of patient satisfaction can be a reference for improving service to patients. Satisfaction is the level of feelings that arise as a result of the performance of the service received after comparing it with what is expected. This study aims to measure the level of satisfaction of inpatient BPJS Kesehatan participants with the services provided by the Special Hospital for Mother and Children (RSKIA) Annisa Payakumbuh in terms of five attributes, namely Tangibles (Real Form), Reliability, Assurance, Responsiveness (Responsiveness) and Empathy (Empathy). To measure the level of patient satisfaction at RSKIA Annisa Payakumbuh used data mining method of Classification Algorithm C4.5 which is one of the most effective Decision tree algorithms for classification. The data were obtained from the summary of the results of the BPJS Kesehatan inpatient patient satisfaction survey at RSKIA Annisa Payakumbuh. Furthermore, the data will be processed using the C4.5 algorithm which will produce rules and Decision trees. The results of data processing using the C4.5 Algorithm obtained Responsiveness as the root variable and resulted in 8 rules with 3 satisfied rules and 5 unsatisfied rules. Based on the results of this study, it can be concluded that the use of the C 4.5 Algorithm Decision tree can be used to measure the level of satisfaction of BPJS Kesehatan inpatients at RSKIA Annisa Payakumbuh. The results of this study are expected to help the RSKIA Annisa in making policies to improve services for patients.
Co-Authors - Hendrick AA Sudharmawan, AA Abdul Azis Said Agung Ramadhanu Akbar Iskandar Alifcha Ghazian Alifia Restu Selvanda Allans Prima Aulia Angga Putra Juledi Arika Juwita Z Ayu Prima Siska Bobi Heri Yanto Budi Jaya Budi Permana Putra Chairul Imam Darnis, Rahmi Dendi Ferdinal Deno Yulfa Ardian Desi Laidawati Dodi Andre Putra DWI JULISA UTARI Dwika Assrani Dzaki Al Fikri Eka Naufaldi Novri Eka Sofianti Fahmi Firzada Fajri Ilhami Andrean Fhajri Arye Gemilang Gunadi Widi Nurcahyo Hasanatul Iftitah Hendro Zalmadani Henky Andema Hermanto Heru Rahmat Wibawa Putra Indah Dwi Putri Irvan Okta Mazhona Ismail Virgo Jefdy Kurniawan Johan Danu Wijaya Jufriadif Na`am, Jufriadif Julius Santony Julius Santony K Kadrahman Lc Granadi Suhaidir Lidia K Simanjuntak Lova Endriani Zen Lusi Kestina M Ilham Aldyno M Mutia Malik, Rio Andika Mardison Mesran, Mesran Mohammad Guntur Montesna Muhammad Arif Zikir Risky Muhammad Ihksan Muhammad Ikhlas Musli Yanto Nandra Sunaryo Nasma Yeni Nasution, Annio Indah Lestari Nuning Kurniasih R Rahmiyanti Rafi Septiawan Putra Ragil Ardiansyah Rahmad Dian Riski Randa Hidayatullah Rivo Stephano Roby Nurbahri Romi Hardianto Ronda Deli Sianturi Rovidatul S Salmiati S Sumijan Sahat Sonang Sitanggang Salman Alfarisi Salimu Sarjo Defit Sarjon Defit Sarjon Defit Septiana Vratiwi Setiawan, Adil Silfia Andini Sri Amalia Harahap Sri Dewi Stefani Hardiyanti Putri Subrianto Chandra Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Syahid Hakam Abdul Halim Syaljumairi, Raemon Teddy Winanda Teguh Junaidi Tessa Y M Sihite Wenni Afrodita Willy Eka Septian Yendi Putra Yosua Ade Pohan Yundari, Yundari Yuniko Fauzan Yusma Elda Zupri Henra Hartomi