Articles
Diagnosa Penyakit Rubella Menggunakan Metode Fuzzy Tsukamoto
Febriani, Widya;
Nurcahyo, Gunadi Widi;
Sumijan, Sumijan
Jurnal Sistim Informasi dan Teknologi 2019, Vol. 1, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang
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DOI: 10.35134/jsisfotek.v1i3.4
Rubella or better known as German measles is a viral infection characterized by a red rash on the skin. Lack of general public understanding of this disease makes the number of patients with Rubella increasing. So Fuzzy Tsukamoto's method is used to detect Rubella disease. The purpose of this study is to facilitate the public in understanding about Rubella disease so as to reduce the number of sufferers of this disease. The first step to detecting Rubella disease is to determine the fuzzy set and domain that includes 3 variables: red rash, swollen lymph nodes, and fever. The output of fuzzy calculations is someone experiencing Rubella or normal symptoms. The value obtained from the calculation process using the Tsukamoto method is 6.00. If the value is smaller than 6.00 then Rubella has no potential, if the value is greater than 6.00 then Rubella will be potential.
Analisis Perkiraan Jumlah Produksi Tahu Menggunakan Metode Fuzzy Sugeno
Nurdini, Siti;
Nurcahyo, Gunadi Widi;
Santony, Julius
Jurnal Sistim Informasi dan Teknologi 2019, Vol. 1, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang
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DOI: 10.35134/jsisfotek.v1i3.5
Tofu industry XYZ is a small industry that is managed in the form of a home industry, where the process of estimating the amount to be produced is still manual. For that, a calculation process is needed that can be used to save or buy. Of the existing problems used in the Sugeno Fueno Method. In this method uses three variables, namely, demand variables, purchase variables and production variables. Each variable has three sets of Fuzzy, the demand variable consists of down, medium and up. Variables consist of few, medium and many. And the production variable consists of reduction, tolerable and increasing. From the results of the test data conducted by the Sugeno Method there is a difference of error of 2.148% means that the truth level is 97,852%. Determining this method can be applied to the tofu industry XYZ in estimating the amount of tofu production for the next period.
Algoritma K-Means untuk Klasterisasi Tugas Akhir Mahasiswa Berdasarkan Keahlian
Sirait, Weri;
Defit, Sarjon;
Nurcahyo, Gunadi Widi
Jurnal Sistim Informasi dan Teknologi 2019, Vol. 1, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang
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DOI: 10.35134/jsisfotek.v1i3.6
School of Information and Computer Management (STMIK) Indonesia Padang is a private university under the auspices of the Higher Education Service Institution (LLDIKTI) Region X, producing graduates who are competent in the field of system analysts and database administrators. Requirements to meet undergraduate graduates (S1) final year students need to complete a final project or thesis.Final year students at STMIK Indonesia Padang often experience confusion in taking the final assignment topic. This is due to the fact that the final year students have not been able to direct their potential in determining the final assignment topic. In this case, researchers conducted the process of grouping final level students using the Data Mining K-means Clustering technique. The process of grouping final-level students is done by utilizing the data of course values from the field mapping system analysts and database administrators. In this grouping two clusters will be produced, namely students taking the final assignment of system analysts and database administrator. So by using this K-means Clustering method, students have direction in taking the final assignment topic. The results obtained from 40 data samples used were students who took the topic of the final project system analysts as many as 20 students and students who took the final assignment of database administrators were 20 students
Implementasi Algoritma K-Means untuk Klasterisasi Peserta Olimpiade Sains Nasional Tingkat SMA
Hasanah, Miftahul;
Defit, Sarjon;
Nurcahyo, Gunadi Widi
Jurnal Sistim Informasi dan Teknologi 2019, Vol. 1, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang
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DOI: 10.35134/jsisfotek.v1i3.7
The abundance of students causes student data in the system to also be abundant. Schools often find it difficult to manage large amounts of data manually, especially in selecting National Science Olympiad participants and decisions made are less effective. So this research was conducted with the aim of helping the school in selecting OSN participants appropriately and effectively. The method used is Clustering with K-Means algorithm on the report card grades of students majoring in Natural Sciences at SMA Negeri 5 Sijunjung. The results in this study get 3 clusters of students on the selection of OSN participants, namely students who are Very Competent, Competent and Less Competent. This research can be used as a benchmark used by schools in making decisions on the selection of OSN participants.
Akurasi Keputusan dalam Penentuan Guru Berprestasi Dengan Menggunakan Metode Simple Additive Weighting (Studi Kasus Sekolah Menengah Kejuruan Muhammadiyah Batam)
Wahyudi, Wahyudi;
Santony, Julius;
Nurcahyo, Gunadi Widi
Jurnal Sistim Informasi dan Teknologi 2020, Vol. 2, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang
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DOI: 10.37034/jsisfotek.v2i1.27
This study aims to obtain decision accuracy in determining teacher achievement using the Simple Additive Weighting method. Problems in Batam Muhammadiyah Vocational High School in determining the achievement of teachers using assessment criteria with the weight of educational qualifications, discipline, neatness, character, personality and teaching methods. The ranking process stage determines the alternatives of selected teacher achievement using the input of criteria weights. The results of this study get an accuracy rate of 80% with an accurate, fast, objective value. In the future, this research will be used as a new standard in determining teacher achievement.
Identifikasi Karakteristik Anak Berkebutuhan Khusus Menggunakan Metode Case Based Reasoning (Studi Kasus di Sekolah Luar Biasa Negeri 1 Linggo Sari Baganti)
Vratiwi, Septiana;
Yunus, Yuhandri;
Nurcahyo, Gunadi Widi
Jurnal Sistim Informasi dan Teknologi 2020, Vol. 2, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang
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DOI: 10.37034/jsisfotek.v2i1.28
Children with special needs are children who have different characteristics and limitations in ability. This child with special needs is called Tunagrahita. Developmental impairment is classified into three categories namely mild, moderate and severe. This study aims to help the process of identifying the characteristics of mental retardation experienced by children. This study uses the Case Based Reasoning (CBR) method to identify children with special needs using the data of the mentally disabled children in SLBN 1 Linggo Sari Baganti. Similarity results were 51.92% for moderate developmental impairment, 17.5% for mild developmental impairment and 8% for severe developmental impairment. Calculations are performed using Visual Basic Net 2010.
PENERAPAN JARINGAN SYARAF TIRUAN UNTUK PENENTUAN SALAK UNGGUL DENGAN MENGGUNAKAN METODE LEARNING VECTOR QUANTIZATION
Fimawahib, Luth;
Lidya, Leony;
Nurcahyo, Gunadi Widi
Riau Journal Of Computer Science Vol. 5 No. 2 (2019): Riau Journal of Computer Science
Publisher : Riau Journal Of Computer Science
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Rokan Hulu is one of district in Riau Province that cultivated Snake Fruit plant. Recently, the cultivation of this plant doesn’t conducted maximally because of the lack of farmer’s knowledge. The varieties of high quality Snake Fruit takes effect toward the productivity of Snake Fruit. Because of that, it needs evaluation in determining high quality Snake Fruit. Artificial Neural Network with Learning Vector Quantization in this research is used to train high quality Snake Fruit plant based on it’s class, namely High Quality I and High Quality II. The testing of this method is conducted by using Matlab in order to obtain classification accuracy level. This research uses 60 training dataset and 40 testing dataset of Snake Fruit plant. These data are obtained by using observation at Snake Fruit Plantation located in Desa Rambah Muda Kecamatan Rambah Hilir Kabupaten Rokan Hulu. The result of this research shows that the highest accuracy percentage of training and testing data are respectively 91.66% and 92.50%.
Simulasi Algoritma Monte Carlo Dalam Memprediksi Tingkat Hafalan Al-Qur’an Santri
M, Mutia;
Nurcahyo, Gunadi Widi;
Yunus, Yuhandri
Jurnal Sistim Informasi dan Teknologi 2020, Vol. 2, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang
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DOI: 10.37034/jsisfotek.v2i4.72
Islamic boarding schools are known to be able to give birth to the Qur'an's tahfidz. With the memorization program, the halaqah about the basic text of the religion makes the Islamic boarding schools increasingly known to the community as an educational institution and a strong milestone of religious knowledge that can bring blessings. The purpose of this study was to predict the level of rote learning of the students at the Tahfiz Lan Tabur Pagaralam Islamic Boarding School. Thus, it is easier for Islamic boarding schools to take strategies to improve the quality of students themselves. The data processed in this study are data sourced from the Natural Boarding School of Tahfiz Al-Qur’an Lan Tabur Pagaralam. Based on the number of students who memorized the Al-Qur'an or Tahfidz in the 2017 to 2019 class which is processed by Monte Carlo algorithm simulation. The processing step is to bring up a random number from the sampling data that has been taken. The results of testing on this method found that the system used to predict the level of memorization of the Al-Qur'an with an average accuracy of 84% in 2018 and an average accuracy of 88% in 2019. With a high degree of accuracy, simulations performed using the Monte Carlo algorithm can predict the number of students memorized by the Qur'an, making it easier for Islamic boarding schools to obtain information about the likelihood of future events at the level of memorization of students at Islamic boarding schools Alam Tahfiz Al-Qur’an Lan Tabur Pagaralam.
Sistem Pakar dengan Metode Forward Chaining untuk Diagnosis Penyakit dan Hama Tanaman Semangka
Pati, Muhammad Ibnu;
Defit, Sarjon;
Nurcahyo, Gunadi Widi
Jurnal Sistim Informasi dan Teknologi 2020, Vol. 2, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang
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DOI: 10.37034/jsisfotek.v2i4.74
Watermelon crops are in demand by farmers to cultivate. Diseases and Pests are not separated from watermelon crops experienced by farmers. To overcome this, farmers rely solely on rough living and getting information from others, this is ineffective because watermelon plant experts are very limited. An expert system is the solution to the limitations of an expert in their field. In this expert system use advanced chain methods and website-based applications. This expert system can be accessed online for users who need information, consultation of diseases and pests on watermelon plants. The expert system will diagnose the symptoms that will be answered by the user of the application and will produce conclusions along with solutions from diseases and pests of watermelon plants. With expert limitations online system is no longer an obstacle for watermelon plant farmers. Information and consultation of diseases and pests of watermelon plants biased online without having to meet with experts.
Sistem Pakar Menggunakan Metode Certainty Factor dalam Akurasi Identifikasi Penyakit Panleukopenia Pada Kucing
Putra, Dyan Mardinata;
Nurcahyo, Gunadi Widi
Jurnal Sistim Informasi dan Teknologi 2020, Vol. 2, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang
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DOI: 10.37034/jsisfotek.v2i4.75
Feline Panleukopenia is a disorder caused by inflammation of Feline Parvovirus. This viral inflammation can trigger inflammation of the digestive system in cats and can also attack the cat's bone marrow, and the total white blood cells in the cat's body will decrease. At this time, many people do not know how to accurately identify the disease Feline Panleukopenia in cats and as a result of that cats who suffer from it experience illness and even death. This study aims to determine the level of accuracy in identifying Panleukopenia in cats. There are several types of symptoms that refer to Feline Panleukopenia. Furthermore, the data is processed manually with the Certainty Factor method and continued by using a website-based expert system software. The processing stages are rule solving, determining the weight value of each symptom and calculating the Certainty Factor value with the rule formula. The results of the data processing are continued with the calculation of the level of accuracy. The result of testing this method is that there are 100% of the 5 test data. Based on the accuracy of the identification results of this system, this study is very precise in the level of identifying the level of accuracy of feline panleukopenia. Expert testing systems have been able to specifically identify Feline Panleukopenia. Through the Certainty Factor method, the level of accuracy that can be obtained is quite accurate and can help veterinarians improve their accuracy to identify Feline Panleukopenia in cats.