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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) SITEKIN: Jurnal Sains, Teknologi dan Industri Journal of Environmental Engineering and Sustainable Technology Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal POINTER JURNAL PENGABDIAN KEPADA MASYARAKAT Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer SISFO Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) JAST : Jurnal Aplikasi Sains dan Teknologi Indonesian Journal of Electrical Engineering and Computer Science Tri Dharma Mandiri: Diseminasi dan Hilirisasi Riset Kepada Masyarakat (Jurnal Pengabdian Kepada Masyarakat) Kohesi: Jurnal Sains dan Teknologi Journal of Information System and Application Development
Lailil Muflikhah
Fakultas Ilmu Komputer, Universita Brawijaya, Malang, Indonesia
Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Public Health Social Sciences Other

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Optimasi Penjadwalan Shift Jaga Dokter di IGD Menggunakan Algoritme Genetika (Studi Kasus Rumah Sakit di Malang) Annisaa Amalia Safitri; Imam Cholissodin; Lailil Muflikhah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Emergency room (ER) is one of the units in a hospital who the first of receiving patients in case of an emergency. In ER, there are doctors who should be available for 24 hours to deal with patient who come everytime when an emergency form happen. To keep the performance of doctors who working 24 hours in ER, then we make a schedule that use with shift system. For 1 month scheduling, 11 doctors will split into 3 shift work in a day. In order to optimize and make the best combination in doctor's schedule at ER, then made the doctor's scheduling system in a ER using genetic algorithm. Reproductive process using 2 ways, first the process of crossover by using extended intermediate crossover and second the mutation process by using a reciprocal exchange mutation, and then will use the last process of algorithm and the name is elitism selection process. Testing that is used for doctor's scheduling system in a ER is there are 3 types of testing. The first test is testing the number of popSize, with the highest fitness at a value of 40 with an average of 1,766, the second test is testing the value of generation with the highest fitness at generation value 40 with an average value of fitness 1,608, and the last test is combination of cr mr with the highest fitness value on a combination of 0,7 and 0,3 with average fitness 2,064. From those results, do more testing to compare the fitness value of fitness values of the system with real data provided by the hospital. And the results show that the value of fitness of the system = 11,111 is greater than the value of the data on real fitness given hospital = 7,692.
Prediksi Harga Batu Bara Menggunakan Support Vector Regression (SVR) Olivia Bonita; Lailil Muflikhah; Ratih Kartika Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Coal price prediction is needed as support for coal user industrial to buy coal. Prediction result can be used to make next budgeting. This research uses Support Vector Regression (SVR) method to predict coal price. SVR is applied through data normalization, hessian matrix calculation, α searching through sequential learning, and regression function calculation. Kernel for hessian matrix stage can determine accuracy of prediction, so in this research Gaussian RBF kernel and ANOVA kernel are used and analyzed the effects. To obtain predictive results with good accuracy, testing of each parameter is performed and evaluated by mean absolute percentage error (MAPE). The average of MAPE for testing are 9,64% with Gaussian RBF kernel and 8,38% with ANOVA kernel, which are categorized good, on 48 training data for 12 testing data and optimal parameters are ε 0,00001; cLR 0.01; C 0.5; λ 0.5 with Gaussian RBF kernel and 1 with ANOVA kernel. SVR gives the most optimal result when predicting the next month price. The predicted results of the two kernels are not too different, but the ANOVA kernel works better on this coal price data.
Implementasi Fuzzy k-Nearest Neighbor (Fk-NN) untuk Klasifikasi Jenis Kanker berdasarkan Susunan Protein Tahtri Nadia Utami; Marji Marji; Lailil Muflikhah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Cancer is the most deadly disease besides heart disease. A common cause of cancer is gene mutation in protein 53 that serves to control the replication of DNA as a regulator of the cell function resulting in the wrong protein sequence. The protein sequences is used as a basis to classifying the types of cancer and then it can ease in determining the right handling or therapeutics method. The classification of cancer using the Fuzzy k-Nearest Neighbor (Fk-NN) method. The data used are 752 protein sequences with 393 sequence length on every sequence. The classification class includes non-cancer, breast cancer, collorectal cancer and lung cancer. The Fk-NN method calculates the degree of membership of each class at the k smallest distances generated from k-Nearest Neighbor method. The highest average accuracy rate is 52.56% of the test results using k-fold-validation. The optimal k value of the Fk-NN method is k = 5 with the average accuracy rate of 54.99%. The large variation in the amount of training data that is 90% of the dataset results in the highest accuracy rate of 55.33%.
Klasifikasi Penyakit Kambing Dengan Menggunakan Algoritme Support Vector Machine (SVM) Ardiza Dwi Septian; Lailil Muflikhah; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Indonesian's rural communities really familiar with goat cattling, that's because the fund for it's nurturing more cheaper and they breed faster.The main factor to nurturing is the health of the goat itself if the goat get sick, it will become disadvantage for them. So that's why health issues become the main factor.If there's disease indications exist, the early handling must be done soon. A disease diagnose is first thing to do.But, the awareness to diagnose the disease are still unknown. That's make the cattleman feel uneasy to handle it.Therefore, it need a system to help them to clasify the disease.This goat disease's research used algoritme support vector machine with one againts all strategy. The data that used are 148 datas with 11 disease classes, there are wormy, endometritis, paralizing, bloated, poisoning, Masistis, Myasis, Orf, Pink Eye, Pneumonia and Scabies.The accuracy result that get from this system is 90% with using the best parameter that called k-fold cross validation 10 , λ= 0.1, C = 0,1, iterasi = 500 and σ = 1.
Penerapan Algoritme Genetika untuk Optimasi Penjadwalan Jam Kerja Part-Time Studi Kasus Cafe Bingsoo Malang Yogi Suwandy; Lailil Muflikhah; Tibyani Tibyani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Part-Time working hours or often called part-time working hours are a group of workers who alternately replace the other group after the work has ended. Part-time working hours are applied in an agency usually divide it in 3 shifts work, morning shift, day shift and night shift. Not a few students who choose Part-Time work for college while working to fill in the empty time in college because by working they can add pocket money and their experience. A manager or division chairman who plays a role in organizing work schedules should be meticulous in the distribution of employee shifts so that all employees get the same number of working hours. Scheduling is an activity to find the solution of a problem which will result in the optimal schedule of the schedule. Genetic algorithm is a method that has been applied by many researchers to get a solution of the problem scheduling. Genetic Algorithm used can provide accuracy value of 100% with a fitness value of 1 to 9 employees division waiters at Cafe Bingsoo Malang, the tests were performed using some of the best parameter values ​​such as population number 70, number of generation 70, crossover rate 0.6 and mutation rate 0.5 with fitness value obtained at 1.
Implementasi Algoritme K-Means Clustering Dan Naive Bayes Classifier Untuk Klasifikasi Diagnosa Penyakit Pada Kucing Puji Indah Lestari; Dian Eka Ratnawati; Lailil Muflikhah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

At this time cat has become a popular pet community. This is because there are many benefits that exist from cats, such as an entertainer, and now developed countries many cats contested in the show cat. Treatment for cats is mainly because some of the cat's disease can spread to humans. The limitations of dentists in diagnosing diseases with a pattern of having the same symptoms as some diseases, are important in making a diagnosis. Therefore there need a system that can diagnose diseases that can be accessed by the cat owners and be dealt immediately. In this study can use K-Means Naive Bayes (KMNB) method for diagnosis in cats. The KMNB approach is formed by the incorporation of clustering and classification techniques. In the beginning Clustering on K-Means was used to group the same data. Further classification of data by category using Naive Bayes method. The data that have errors in the first stage are then organized by the second category. Identify data with the same character or data that shows similar characteristics from the start. Based on the results of tests that have been done by comparing the results of grouping on conventional K-Means proves that KMNB can produce the highest average of 90% while conventional K-Means has the highest average of 71, 379%.
Implementasi Metode Learning Vector Quantization Untuk Klasifikasi Penyakit Demam Nurhidayati Desiani; Lailil Muflikhah; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Fever is an early symptom of various diseases that have been experienced by almost everyone. Some of the diseases include typhoid fever, malarial fever and dengue fever. These three diseases have similar early symptoms. Similar symptoms of each disease often cause difficulty in obtaining anamnese (temporary diagnosis) so that patients get the initial handling is less precise and further worsen the condition of the patient. To overcome this required a system that can facilitate in identifying the disease based on the symptoms felt by the patient. In this study using Learning Vector Quantization method which is a method of classification. The system works with the training and testing phases that will result in classes of typhoid fever classes, malarial fever and dengue fever. The parameters used are 15 parameters of symptoms of febrile illness. The best average accuracy result is 100% using comparison of test data and training data of 10:90, learning rate 0,1, learning rate reduction constant 0,1, minimum learning rate 10-5, and maximum number of iteration 10.
Klasifikasi Penerimaan Program Keluarga Harapan (PKH) Menggunakan Metode Learning Vector Quantization (Studi Kasus Desa Kedungjati) Vidya Capristyan Pamungkas; Lailil Muflikhah; Rendi Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Poverty is a condition of someone inability to fulfill basic needs for a decent life. The poverty rate is increases, especially in Jombang Regency from year to year until 2017 reaching 131.16 people, various ways have been carried out by the government to reduce poverty, one of which is Program Keluarga Harapan or PKH, Kedungjati Village officer doing survey head of family with manual method by visiting each head of family and recording one by one the criteria. Classification system of Program Keluarga Harapan using Learning vector quantization (LVQ). LVQ is a classification method that has a pattern where the output of each unit is a representation of a class or category. The weight vector of each unit's output is a vector representation to a class. Weight vector have rules during training. As a classification method, LVQ does a lot of training repeatedly process until get maximum results, so LVQ can minimize errors that occur in the process. LVQ method do training and testing process to obtain the classification results. In this case using 5 test parameters with the best results, that is learning rate 0.7, DecAlpha 0.3, Epoch 2, and MinAlpha 0.01, using 2 weight vector to represent class 0 and class 1, get the results of an accuracy of 100%.
Sistem Diagnosis Penyakit Kelamin Pada Pria Menggunakan Metode Forward Chaining Dan Dempster-Shafer Kukuh Bhaskara; Nurul Hidayat; Lailil Muflikhah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

According to the World Health Organization (WHO), more than 1 million sexually transmitted infections (STIs) occur every day. In one year there were an estimated 357 million new cases of sexually transmitted infections (STIs) worldwide. Sexually transmitted infections are all infections both bacteria, viruses, and fungi that are transmitted from one individual to another through sexual activity or through genital organs. For example, a newborn baby can contract gonorrhea from his mother as a result of passing through the vagina infected with N. Gonorrhoeae. According to WHO, more than 30 types of bacteria, viruses and parasites have been identified that can cause sexually transmitted diseases. 8 of these 30 species are known to have the greatest risk of causing sexually transmitted diseases. The purpose of this study was to implement the Forward Chaining and Dempster-Shafer method and testing the accuracy of the Forward Chaining and Dempster-Shafer method in identifying venereal disease in men. The results of the study shows that the accuracy of the expert system based on 35 data tested is 94.2% indicating that this expert system can function properly, namely the diagnosis of the system in accordance with expert diagnosis.
Optimasi Variasi Menu Makanan Sesuai Gizi Pada Anak Panti Asuhan Dengan Improved Particle Swarm Optimization Aldino Caturrahmanto; Lailil Muflikhah; Imam Cholissodin
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 9 (2019): September 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Nutrition is a compound which important to human growth and their health. Nutrition consumption is really important that they can affect health if poorly managed. Unfortunately, there are still places which have poorly managed nutrition planning, which one of them is Orphanage. Improved Particle Swarm Optimization is an Evolutionary Algorithm which is based on nature folks of birds flying in group searching for new food points. This Algorithm have great ability to search local optimum solution and also global optimum solution. In this case, a list of foods menu will be represented by a Particles which consisting indexes of number represent menu. The result of our testing found that swarm size of 70 and combination of 2,0 for C1 and C2 is the best parameter for this problem. Although giving great solution based on Nutrition, this algorithm still offer total price above our limit value.
Co-Authors A. Bachtiar , Fitra Abdurrachman Bachtiar, Fitra Achmad Jafar Al Kadafi, Achmad Jafar Addin Sahirah, Rafifa Adinugroho, Sigit Agung Setiyoaji Agus Ardiansyah Agus Wahyu Widodo Agus Wahyu Widodo, Agus Wahyu Ahmad Nur Royyan Ahmad Wildan Attabi' Akbar Grahadhuita Al Kautsar, Prima Daffa Aldi Bagus Sasmita Aldino Caturrahmanto Anis Zubair, Anis Annisaa Amalia Safitri Aqmal Maulana Tisno Nuryawan Ardiza Dwi Septian Arief Andy Soebroto Ashidiq, Muhammad Fihan Aulia Herdhyanti Bachtiar, Harsya Baharudin B. Baharum Baihaqi, Galih Restu Bajsair, Fath' Hani Sarli Bayu Laksana Yudha Bayu Rahayudi Bening Herwijayanti Bintang, Tulistyana Irfany Brillian Ghulam Ash Shidiq Budi Darma Setiawan Candra Dewi Candra Dewi Daneswara Jauhari Daneswara Jauhari, Daneswara Darma Setiawan, Budi Darmawan, Riski Daud, Nathan Dewi, Buana Dhimas Wida Syahputra Dian Eka Ratnawati Dimas Joko Hariyanto Dimas Joko Haryanto Duwi Purnama Sidik Edy Santoso Edy Santoso Eni Hartika Harahap Eva Agustina Ompusunggu Faris Dinar Wahyu Gunawan Fatimah Az-Zahra, Adinda Feri Eko Herman Fitra Abdurrachman Bachtiar Fitrotuzzakiyah, Shafira Puspa Gessia Faradiksi Putri HANA RATNAWATI Hanggar Wahyu Agi Prayogo Haris, Asmuni Haryanto, Dimas Joko Hinandy Nur Anisa Hoar, Wilhelmina Sonya Ichsan Achmad Fauzi Iftinan, Salsa Nabila Imam Cholissodin Imam Cholissodin Imam Cholissodin Imam Cholissodin Indriati Indriati Indriati Indriati Issa Arwani Kautsar, Ahmad Izzan Khairunnisa, Alifah Ksatria Bhuana Kukuh Bhaskara Kukuh Haryobismoko Kurnianingtyas, Diva Laily Putri Rizby Luqyana, Wanda Athira Luthfi Afrizal Ardhani M. Ali Fauzi M. Tanzil Furqon, M. Tanzil Marine Putri Dewi Yuliana Marji . Marji Marji Maulana, Muhammad Taufik Maulidiya, Afifulail Maya Nur Muh Arif Rahman Muh Hamim Fajar Muh. Arif Rahman Muhammad Abduh Muhammad Fajri Muhammad Ferian Rizky Akbari Muhammad Rafif Al Aziz MUHAMMAD SYAFIQ Muhammad Tanzil Furqon Muhammad Wafiq Mukhrodi, Dillah Lyra Nashi Widodo Nisa, Lisa N. Novanto Yudistira Nurfansepta, Amira Ghina Nurhidayati Desiani Nurul Dyah Mentari Nurul Hidayat Nurul Hidayat Olivia Bonita Puji Indah Lestari Puspita Sari Putra Pandu Adikara Putri, Rania Aprilia Dwi Setya Rachmad Indrianto Rachmatika, Isnayni Sugma Rafifah Nawawi, Danisha Ramadhan, Galang Gilang Randi Pratama Nugraha Randy Cahya Wihandika Ratih Kartika Dewi Rekyan Regarsari Mardhi Putri Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Rendi Cahya Wihandika Rheza Raditya Andrianto Ria Ine Pristiyanti Rika Raudhotul Rizqiyah Riski Darmawan Riyanarto Sarno Rizal Setya Perdana Rizal Setya Perdana Robbiyatul Munawarah Rowan Rowan Rusydi Hanan, Muhammad Satrio Hadi Wijoyo Setiana, Maya Setya Perdana, Rizal Shalsadilla, Shafatyra Reditha Sholeh, Mahrus Sukma, Lintang Cahyaning Supraptoa Supraptoa Surya Dermawan Susanto, Dominicus Christian Bagus Sutrisna, Naufal Putra Sutrisno Sutrisno Sutrisno, Sutrisno Syafruddin Agustian Putra Syarif Hidayatulloh Tahtri Nadia Utami Tibyani Tibyani Tirana Noor Fatyanosa, Tirana Noor Tri Fadilah, Ghina Utaminingrum, Fitri Vianti Mala Anggraeni Kusuma Vidya Capristyan Pamungkas Wahyu Rizki Ferdiansyah Wardana, Dzaky Ahmadin Berkah Warut, Gregorius Batara De Wibowo, Dhimas Bagus Bimasena Wijaya, Nicholas Yobel Leonardo Tampubolon Yogi Suwandy Yulian Ekananta Yunita, W. Lisa Zakiyyah, Rizka Husnun Zanna Annisa Nur Azizah Fareza