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All Journal Journal of Environmental Engineering and Sustainable Technology JURNAL PENGABDIAN KEPADA MASYARAKAT Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Indonesian Journal of Electrical Engineering and Computer Science Community Empowerment Jurnal Sistem Informasi, Teknologi Informasi, dan Edukasi Sistem Informasi (JUST-SI)
Indriati Indriati
Fakultas Ilmu Komputer, Universita Brawijaya, Malang, Indonesia
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Mechanical Engineering Public Health Social Sciences

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Penerapan Algoritma C4.5 Untuk Memprediksi Nilai Kelulusan Siswa Sekolah Menengah Berdasarkan Faktor Eksternal Rizky Haqmanullah Pambudi; Budi Darma Setiawan; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 7 (2018): Juli 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Education in the life of a country plays a very important role to ensure the survival of the state and nation. Statistics show that Portugal's education level is at the bottom of the list due to many students dropping out of school. External factors affect the failure of students in completing the field of study, especially the field of study of mathematics. Algorithm C4.5 is one method of data mining to predict students' ability in completing the field of study seen from the external factors of students. The C4.5 algorithm is used to find out the accuracy of the prediction ability of high school students. The feature selection parameters are the factors that affect the ability of high school students in the field of mathematics studies. Testing and analysis results show that the Decision Tree C4.5 algorithm is accurately applied to predict the final grade of high school students with a 60% accuracy rate.
Optimasi Fungsi Keanggotaan Fuzzy Inference System Tsukamoto dengan Particle Swarm Optimization pada Penentuan Jumlah Produksi Gula (Studi Kasus : Pabrik Gula Kebonagung Malang) Nur Intan Savitri Bromastuty; Budi Darma Setiawan; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Production is an activity that resulted in goods and services with the usage of resources called production factor. The usual factors for sugar productions is farming area, sugar cane rendement, sugar cane amount, amount of labors, mechine operations, supporting materials and grinding time. Based on previous studies, the major factors that applies to PG. Kebonagung Malang are sugar cane amount, rendement, labor, and machine operations. Studies that estimate sugar production amount already exist, but it's still not optimal. This research was meant to optimize the estimation of sugar production of PG. Kebonagung Malang with particle swarm optimization method to optimize tsukamoto fuzzy inference system. Testing was done with varying particle counts and varying iteration. Computation speed decreases when the number of iterations and particles count increases. Every test with different particle count and iterations results in different fitness value.
Optimasi Bobot Multi-Layer Perceptron Menggunakan Algoritma Genetika Untuk Klasifikasi Tingkat Resiko Penyakit Stroke Nadya Oktavia Rahardiani; Wayan Firdaus Mahmudy; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Stroke is one of a high mortality disease in Indonesia. A various ways can be done to detect stroke, such as blood test. The result is known just after a few hour. Unfortunately, in some case it took a long time to find out whether a patient at risk of stroke or not. The level of risk can be easily done with a system. Multi-layer perceptron (MLP) network is one of artificial neural network (ANN) model which has a random weight from backpropagation (BP) learning. This study is doing optimization to obtain proper weights, using genetic algorithm (GA) as a training method, so that the classification results are more accurate. Implementation, testing, and analysis are done in BP learning algorithm and GA to compare its accuracy on classifying the risk level of stroke. MSE value obtained in testing phase is 0.0122 with number of iteration = 190, number of neuron in hidden layer = 10, and learning rate = 0.9. While in testing phase of GA obtained 0.0549 with population size = 100, generation size = 400, Cr = 0.8, and Mr = 0.2. In final result, average data accuracy of BP is 88.40% with average MSE value is 0.0122 and GA is 60.60% with average MSE value 0.0549 by 10 times trial.
Implementasi Metode Naive Bayes Dengan Perbaikan Missing Value Menggunakan Metode Nearest Neighbor Imputation Studi Kasus: Penyakit Malaria Di Kabupaten Malang Riyant Fajar; Rizal Setya Perdana; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Malaria is an infectious disease that is transmitted among humans by the bites of female Anopheles mosquit. There are four types of Plasmodium that are frequently found in the case of malarial infection in Indonesia: Plasmodium vivax (Tertiana), Plasmodium malariae (Quartana), Plasmodium falcifarum (Tropica), and Plasmodium ovale (Pernisiosia). Thus far, people are having difficulty in differentiating the symptoms found in malaria and in another common cold or influenza as the laymen rely only on general knowledge without any medical facts and reviews. As a result, the patient of malaria is often mistreated. The symptoms of malaria depend on the types of malaria itself. Classic symptoms of malaria suffered by non-immune patients (patients who live in non-endemic area) are paroxysmal (sudden acute fever) preceded by chills and oversweating. On the other hand, classic symptoms of malaria suffered by immune patients are headache, nausea and vomitting, diarrhea , as well as muscle pain. Malaria is a life-threatening disease that can lead into death if not treated in an immediate manner. On that account, a computer system that can accelerate the detection is needed to help in diagnosing whether or not the patient is infected. The said system was designed using Naive Bayes method and the improvement of missing value with the usage of nearest neighbor imputation method. The verdict of the system's accurateness from two testing scenarios has been acquired with the best accuracy point of 77.14% in the first testing scenario and 64.70% in the second testing scenario.
Implementasi Fuzzy Time Series Pada Prediksi Harga Daging Di Pasar Kabupaten Malang Frans Agum Gumelar; Rekyan Regasari Mardi Putri; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Beef is one of the staples that are always consumed by the people of Indonesia. The scarcity of local beef is one of the causes of rising prices. Stabilize the price of beef is the duty of DISPERINDAG. DISPERINDAG spreads almost in every region of Indonesia, one of them is in Malang. Its population is increasing annually so that the demand of food especially beef also increasing. Rising demand of beef also affects the rise in beef prices. So DISPERINDAG should control the increase of beef prices as action to anticipate the increasing price. Therefore, one of the efforts that can be done is to forecast increasing price of beef. So that DISPERINDAG can consider the next month price based on forecast result.The forecasting process is based on historical data. This forecasting that is used is called time series data forecasting. The relations between data are emphasized in time series forecasting. The method used for forecasting is the Fuzzy Time Series (FTS). Based on the results of the test using 21 data of meat prices in Malang Regency in 2016 and 2017, the accuracy obtained from forecasting of 57%. With the smallest error value lies in june 2017 of 16,129 and the biggest error value lies in march 2016 of 65,610,000.
Penerapan Optimasi Susunan Bahan Makanan untuk Ibu Hamil Penderita Kurang Energi Kronis (KEK) Menggunakan Algoritme Evolution Strategies Firda Priatmayanti; Imam Cholissodin; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 9 (2018): September 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Maternal health during pregnancy, growth, birth, preparation of breastfeeding and infant growth is influenced by the addition of nutrients during pregnancy. The causes of Chronic Energy Deficiency or in Indonesia is Kurang Energi Kronis (KEK) in pregnant women is not sufficient to intake of energy and protein. The risk of pregnant women will experiencing KEK if the Upper Arm Circumference or in Indonesia is Lingkar Lengan Atas (LILA) have less than 23.5 cm. KEK in pregnant women can cause death indirectly and can cause Low Birth Weight or in Indonesia is Berat Badan Lahir Rendah (BBLR) in the children and BBLR can also cause to death and growing disordes of the child. Evolution Strategies used cycle of type (μ/r+ λ). Chromosome representation used real-vector, recombination used intermediate recombination and mutation used self-adaption mechanism. Based on the results test, the best solution come from the population of 100 with an average fitness value of 20.34, the number of offspring of 30 with an average fitness value of 18.53, the number of generations of 100 with an average fitness value of 19.35. The solution given is the composition of food material to the nutritional nedds of pregnant women KEK for 7 days with anaverage of adequate nutritional needs of 78.5% and an average cost saving 35.81%.
Penerapan Algoritma Support Vector Machine (SVM) Pada Pengklasifikasian Penyakit Kejiwaan Skizofrenia (Studi Kasus: RSJ. Radjiman Wediodiningrat, Lawang) Arya Perdana; Muhammad Tanzil Furqon; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 9 (2018): September 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Schizophrenia is a disease that attacks a person's psyche, and resulting in behavior with an inappropriate mindset. One of the causes of a person suffering from schizophrenia is stress and also has severe life pressures from various aspects of life. Support Vector Machine (SVM) is an algorithm that can classify types of schizophrenia. The data used in this research is as much as 11 data which is divided into 5 classes. Classes in this study represent five types of diseases in schizophrenia are paranoid, hebefrenik, catatonic, undifferentiated, and simplex. Basically SVM algorithm is a method of linear classification, so that a kernel is used to overcome nonlinear data. In this research is also used One Against All concept to solve multiclass problem. The end result of this research resulted in the highest accuracy of 50.09%, with constant value λ = 1; C = 0,1; γ = 0.1; itermax = 100; ε = 0.01; and also uses polynomial kernels. Tests in this study using K-Fold Cross Validation test, using 11 fold.
Penerapan Algoritme Genetika pada Optimasi Fungsi Keanggotaan Sistem Inferensi Fuzzy Tsukamoto untuk Diagnosis Penyakit HIV Yobel Leonardo Tampubolon; Lailil Muflikhah; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 9 (2018): September 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

One utilization of the fuzzy inference system is to diagnose HIV disease. In fuzzy inference system there is a membership function that plays an important role in solving the problem so that the function must be determined correctly and appropriately. Based on the rules and limitations of symptoms obtained from the expert used to establish the rules required in fuzzy logic to obtain accurate diagnosis of HIV disease. To obtain the right membership function can be done restrictions using Genetic Algorithm that can provide better accuracy results than the previous limitation. Genetic algorithm used can give accuracy about 45% for 24 data tested. Tests conducted using some of the best parameter values ​​there are, population value is 60, the generation is 40, crossover rate is 0.70 and mutation rate is 0.40. The optimization performed on fuzzy logic method using Genetic Algorithm has increased the accuracy about 20%.
Peringkasan Teks Otomatis Secara Ekstraktif Pada Artikel Berita Kesehatan Berbahasa Indonesia Dengan Menggunakan Metode Latent Semantic Analysis Nurina Savanti Widya Gotami; Indriati Indriati; Ratih Karika Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 9 (2018): September 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Increasing the amount of digital data quickly each year, one of which is text data of documents that can be text news articles can make it difficult for the reader to understand all the information so as to affect the acquisition of accurate information and need a longer time to extract an information on a document. Therefore, it is necessary to have an automatic extract text extracting system in Indonesian language health articles in order to help the reader or user to facilitate the process of extraction of information in the document with a fast, concise and clear time. This study uses the latent semantic analysis (LSA) method which is a method that extracts semantic structure or hidden meaning in a sentence and produces a general or broad meaningful summary. The LSA method uses the linear value decomposition (SVD) linear algebra approach by forming a representation matrix of term associations which are words in the closely related document of the TF-IDF calculation process. The LSA cross method is used to construct a summary sequence in the summary extraction stage. Tests of this research resulted that the result of text summary with LSA method obtained the accuracy value of precision, recall and f-measure in consecutive order at compression rate 50% with value 0.668, 0.743, 0.700 and 0.690 while at compression rate 40% equal to 0.696, 0.605 , 0.642 and 0.663.
Rekomendasi Lokasi Pet Shop Di Kota Malang Menggunakan Metode Analytical Hierarchy Process (AHP) Simple Additive Weighting (SAW) Ghiffary Rizal Hamdhani; Edy Santoso; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 9 (2018): September 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Nowadays raising animals like cats is like a lifestyle, sometimes many people think of the pet as family. Therefore pet owners always give the best care to the animals. This system uses one of the methods in the Decision Support System. Decision Support System is a computer-based system that can assist a person in improving its performance in decision making. By using one of the methods in the Decision Support System, it is expected to help solve problems that are in semi-structured areas such as the above problems. In this system will use the method of Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW). Analytical Hierarchy Process (AHP) is a method used to solve an unstructured complex situation into several components within hierarchical groups, by assigning subjective values and determining which variables have the highest priority to influence the outcomes in those situations . Simple Additive Weighting (SAW) is used for ranking.. Based on the results of the test can be analyzed that the AHP and SAW method is quite effective used in the recommendation process. The result of accuracy testing on custody service is 72,72% while accuracy testing of grooming service equal to 75%.
Co-Authors Abdul Azis Adjie Sumanjaya Abel Filemon Haganta Kaban Achmad Arwan Achmad Burhannudin Achmad Ridok Ade Wahyu Muntizar Adella Ayu Paramitha Adinugroho, Sigit Afif Musyayyidin Aghata Agung Dwi Kusuma Wibowo Agus Wahyu Widodo Ahmad Afif Supianto Ahmad Fauzan Rahman Ahmad Nur Royyan Aisyah Awalina Alaikal Fajri Nur Alfian Alfita Nuriza Alvin Naufal Wahid Anak Agung Bagus Arisetiawan Andhika Satria Pria Anugerah Andre Rino Prasetyo Anggara Priambodo Jhohansyah Anjelika Hutapea Annisa Selma Zakia Ardhimas Ilham Bagus Pranata Arief Andy Soebroto Arifin Kurniawan Arinda Ayu Puspitasari Arthur Julio Risa Ashshiddiqi Arya Perdana Avisena Abdillah Alwi Ayu Tifany Novarina Bagus Abdan Aziz Fahriansyah Bayu Rahayudi Benita Salsabila Berlian Bidari Ratna Sari B Beta Deniarrahman Hakim Billy Sabilal Binti Najibah Agus Ratri Binti Robiyatul Musanah Brian Andrianto Budi Darma Setiawan Candra Ardiansyah Candra Dewi Chandra Ayu Anindya Putri Choirul Anam Daneswara Jauhari Dea Zakia Nathania Deny Stevefanus Chandra Deri Hendra Binawan Desy Andriani Desy Wulandari Dewi Syafira Dhaifa Farah Zhafira Dhony Lastiko Widyastomo Diajeng Ninda Armianti Dian Eka Ratnawati Dina Dahniawati Dinda Adilfi Wirahmi Durrotul Fakhiroh Dwi Suci Ariska Yanti Dyah Ayu Wulandari Edo Ergi Prayogo Edy Santoso Eka Putri Nirwandani Enggar Septrinas Erma Rafliza Fajar Pradana Faradila Puspa Wardani Fardan Ainul Yaqiin Febriana Ranta Lidya Febrina Sarito Sinaga Fera Fanesya Ferdi Alvianda Feri Angga Saputra Firda Oktaviani Putri Firda Priatmayanti Firhad Rinaldi Saputra Fitra Abdurrachman Bachtiar Frans Agum Gumelar Galuh Fadillah Grandis Ghiffary Rizal Hamdhani Guedho Augnifico Mahardika Hilmy Khairi Idris I Made Budi Surya Darma Imam Cholissodin Indah Mutia Ayudita Indriya Dewi Onantya Inosensius Karelo Hesay Jeffrey Junior Tedjasulaksana Jeowandha Ria Wiyani Joda Pahlawan Romadhona Tanjung Junda Alfiah Zulqornain Katherine Ivana Ruslim Khaira Istiqara Khalisma Frinta Kornelius Putra Aditama Ksatria Bhuana Lailil Muflikhah Liana Shanty Wato Wele Keaan Liana Shinta Dewi Liana Shinta Dewi Linda Pratiwi Ludgerus Darell Perwara Lusiyana Adetia Isadi Luthfi Mahendra M. Aasya Aldin Islamy M. Ali Fauzi Mahdarani Dwi Laxmi Mahendra Okza Pradhana Mardji Mardji Marinda Ika Dewi Sakariana Marji Marji Mentari Adiza Putri Nasution Merry Gricelya Nababan Moch Bima Prakoso Mochamad Havid Albar Purnomo Mohamad Alfi Fauzan Mohammad Birky Auliya Akbar Mohammad Fahmi Ilmi Mohammad Imron Maulana Muhammad Abdurasyid Muhammad Fauzan Ziqroh Muhammad Hakiem Muhammad Mauludin Rohman Muhammad Reza Ravi Muhammad Tanzil Furqon Muhammad Yudho Ardianto Nadya Oktavia Rahardiani Nana Nofiana Nanda Ajeng Kartini Nanda Cahyo Wirawan Ni Made Gita Dwi Purnamasari Ni Made Gita Dwi Purnamasari Nihru Nafi' Dzikrulloh Nirmala Fa'izah Saraswati Novanto Yudistira Novia Agusvina Nur Intan Savitri Bromastuty Nurdifa Febrianti Nurina Savanti Widya Gotami Nurudin Santoso Nurul Hidayat Nurul Muslimah Pengkuh Aditya Prana Prais Sarah Kayaningtias Pratitha Vidya Sakta Puteri Aulia Indrasti Putra Pandu Adikara Putri Rahma Iriani Putu Amelia Vennanda Widyaswari Putu Rama Bena Putra Rachmad Ridlo Baihaqi Rahma Chairunnisa Rahmat Arbi Wicaksono Rakhman Halim Satrio Randy Cahya Wihandika Ratih Karika Dewi Ratna Tri Utami Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Rien Difitria Rifki Akbar Siregar Rilinka Rilinka Riska Dewi Nurfarida Riski Nova Saputra Riyant Fajar Riza Cahyani Rizal Aditya Nugroho Rizal Setya Perdana Rizaldy Aditya Nugraha Rizky Haqmanullah Pambudi Rizky Nur Ariyanti Sabrina Hanifah Salsabila Rahma Yustihan Sigit Adinugroho Sinta Kusuma Wardani Siti Robbana Sutrisno Sutrisno Swandy Raja Manaek Pakpahan Tania Malik Iryana Tania Oka Sianturi Tasya Agiyola Thio Marta Elisa Yuridis Butar Butar Titus Christian Vera Rusmalawati Wayan Firdaus Mahmudy Yane Marita Febrianti Yobel Leonardo Tampubolon Yudha Ananda Kresna Yudha Irwan Syahputra Yudha Prasetya Anza Yuita Arum Sari Yulia Kurniawati Zahra Swastika Putri