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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Imam Cholissodin
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Rekomendasi Peminatan SMA Bagi Siswa Kelas IX SMP Menggunakan Metode AHP dan SMART Sari Narulita Hantari; Imam Cholissodin; Edy Santoso
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

Education has an important role in human life. Choosing the right education will have a positive impact on their future career. Based on Indonesian Education Curriculum starting from year 2013, high school major was carried out since 10th grade, at the time when new student admission is conducted. These changes have an impact on Junior High School students, who have to prepare to choose which major they they want to be in. Academic report, student interest, family's wealth, school they want to enroll, and parent's wishes are some factor that need to be considered. This study is conducted to make recommendation for 9th grade students in which major are suitable for them. The method used is Analytic Hierarcy Process (AHP) and Simple Multi Attribute Rating Technique (SMART). Criterias that being used is their study report, and their interest. AHP is used to calculate the weight of criteria, while SMART is used to determine recommendation result between IPA and IPS. Data testing is calculated 10 times using Spearman Correlation resulting in ρ=0.83458. The Spearman value (ρ) then compared to significance test table, resulting significant relationship between IPA and IPS.
Implementasi Algoritme Extreme Learning Machine (ELM) Untuk Klasifikasi Penanganan Human Papilloma Virus (HPV) Stefanus Bayu Waskito; Imam Cholissodin; Edy Santoso
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

Human Papilloma is a virus that cause warts ilness. There are several treatment methods, but Immunotherapy and Cryotherapy are considered to be the best method to treat this ilness. However, none of them can heal all patients. Therefore, research to determine which method more appropriate for a certain patient is required. This research use Extreme Learning Machine Algorithm to help classify which method are better for certain patient. A tests is conducted to determine the effects of activation function, number of hidden neuron and and data ratio toward classification accuracy. It was observed that using Binary Sigmoid activation function, 80 testing data to 20 training data ratio, and 10 hidden neuron, the classification accuraccy reach 70,8%. And the classification time spent were relatively fast that is only 0.043 seconds.
Prediksi Jumlah Permintaan Semen Menggunakan Jaringan Syaraf Tiruan Backpropagation Mahendro Agni Giri Pawoko; Imam Cholissodin; Ratih Kartika Dewi
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

Cement is an important material in the development process. Cement production in Indonesia is quite high compared to the amount of consumption. This condition results in oversupply, a condition where the amount of production is greater than the amount of consumption. This resulted in falling cement prices and warehouse full of cement that has not been sold. This makes the Indonesian Cement Association (ASI) to issue its regulation to temporary stop producting cement. This study aims to predict the amount of cement demand in the next time so that regulations can be issued more quickly, so the factory can adjust its production capacity without having to stop production. Many methods can be used to make predictions, for example is Backpropagation Neural Network which is proven to provide good results in predicting, such as predicting the amount of newspaper demand and sugar production. This research uses Backpropagation Neural Network with network architecture of 6 input neurons, 4 hidden neurons and 1 output neuron. The best parameters used are the learning rate of 0.8, the maximum iteration of 200 and the initial weight interval between -1,4 to 1,4. The MSE best predictive value is 0.049064.
Diagnosis Penyakit Ikan Mas Koki Menggunakan Metode Naive Bayes Classifier Muhammad Hasbi Wa Kafa; Nurul Hidayat; Imam Cholissodin
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

The Indonesian state as a maritime country has thousands of species of fish. Various types of fish found in Indonesia, not only fish that can be consumed alone but Indonesia also has a variety of types of ornamental fish are very popular. One of the most popular ornamental fish is the goldfish chef, so it is not surprising that the demand for goldfish is increasing. From time to time many people are looking for a goldfish chef. Its high selling price also provides its own blessing for its business. Of course the goldfish cultivation is a gold field for farmers to gain profits. Cultivating the goldfish can be said is not difficult, but there is something to note in some ways because these fish including fish that are susceptible to disease. Illness may arise due to improper maintenance of the goldfish. The number of symptoms of the disease in the goldfish often makes cultivators difficult to identify the disease, so in the handling of goldfish disease chef also experienced a mistake. Therefore, a system that can help in identifying the goldfish disease properly. By using the method of calculation Naive Bayes Classifier has obtained 90% accuracy of the system which means the system can run well because the results from the system close to the similarity with the actual field facts.
Optimasi Komposisi Pakan Burung Lovebird Menggunakan Algoritme Particle Swarm Optimization (PSO) Mauldy Putra Pratama; Imam Cholissodin; Muhammad Halim Natsir
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

Lovebird is a type of bird that many people have as a pet or for a competition. This bird needs adequate nutrients for survival. In reality, there are many of them that over or low nutrients. This study will discuss about how to optimized the composition feeds of lovebird and minimize the costs without reducing the nutrition. Particle Swarm Optimization (PSO) is one of the optimization methods that used for the formulation process and the composition to keep fulfilling the nutrient needs with minimal cost. The PSO algorithm process starts with the initialization process for position, velocity, pBest values as much as the particles and gBest. Then proceed to update the velocity, position, pBest and gBest as much as the iteration that has been determined. Based on the results of the test that have been done in this study, the writer obtains the optimal parameters such as the number of particles as much as 60, the number of iterations is 600 and the value of coefficient k is 0.3. By using these parameters, the price difference is Rp 5,540.00.
Optimasi Pakan Bibit Unggul Sapi Jantan Menggunakan Particle Swarm Optimization (PSO) (Studi Kasus pada Balai Besar Inseminasi Buatan Singosari) Daniel Agara Siregar; Imam Cholissodin; Bayu Rahayudi
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

Cows are one of the staple food items needed to meet consumption needs in Indonesia. To produce a quality cow required good quality seed of cow. Based on data from Artificial Insemination Center (BBIB) Singosari, fluctuation in the value of the amount of frozen semen production due to decrease in the number of cow population and reduced production of fresh cement with good quality. Cattle feed is one of the factors that affect the quality of cement in cow. Provision of feed with good nutritional content and the right composition can improve the quality of cow. The Particle Swarm Optimization algorithm is chosen for optimization as it is easy to implement and faster in finding the optimum solution compared to other optimization methods. This problem uses initialization of particles, initial velovity, velocity updates, position updates, finding the fitness value of personal best ​​and global best. After conducting the experiment using the weight of the cow of 1114 kg, in obtaining the most optimal parameter result that is on the swarm size of 180, the number of iterations of 45, the inertia weight of of 0,4 and of 0,5, and the acceleration coefficient and respectively 2,5 and 0,5 and the values ​​of and respectively 0,5 and 2,5. Feed recommendation result by system can retrench fund as much as 32,104% compared to recommendation of feed at BBIB.
Rekomendasi Rumah Makan Malang Menggunakan Metode Fuzzy Analytical Hierarchy Process dan Technique For Order Preference by Similarity to Ideal Solution Mohammad Toriq; Imam Cholissodin; Putra Pandu Adikara
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

Indonesia is one country with a large population increasing every year in the culinary business. Then a system is needed that can recommend restaurants to customers. This problem can be solved by using Fuzzy Analytical Hierarchy Process and Technique for Order Preference methods by Similarity to Ideal Solution (F-AHP and TOPSIS). The criteria are the number of food menus, restaurant ratings, food menu prices, distance of restaurants and length of time open. This method is divided into 2 stages. The first phase of FAHP is the comparison of criteria matrix, normalization of comparison criteria matrix, weight vector, priority weight, consistency ratio, TFN matrix conversion, fuzzy synthesis matrix, defuzzification vector and ordinate and fuzzy vector normalization. The second stage is TOPSIS from decision making matrix, normalization of decision matrix, weighted normalization matrix, search for positive-negative ideal solution, distance search for ideal positive-negative solution and preference value. The results of the preference value are sorted to produce the recommended restaurant ratings. In this study involved 3 customers who had visited a restaurant. The test uses the Spearman correlation test method in determining the proximity of the results of the ranking system to the manual rating by each customer. The results of testing the level of accuracy of the system rating on customers is low, namely 0.3352, -0.1538 and third -0.3205. This shows a lack of conformity between expert choices on the system because the results of expert ratings are still not based on the specified criteria.
Optimasi Komposisi Makanan Untuk Keluarga Penderita Diabetes Melitus Menggunakan Algoritme Genetika Azmi Makarima Yattaqillah; Imam Cholissodin; Budi Darma Setiawan
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

Indonesia ranks 6th in the number of people with diabetes mellitus in the world. Of the 10.3 million Indonesians who have diabetes only 36.3 percent are diagnosed. As a result, many people do not have the right diet. The family of people with diabetes mellitus means a family with at least one member suffering from diabetes mellitus. This family is one of the factors that can increase the risk of suffering from diabetes mellitus by two to six times. Unhealthy lifestyles are also a cause of diabetes mellitus which makes diabetes a disease that can be prevented by consuming the right food starting from daily food in the family. Things that need to be considered in the right diet is to determine the composition of the right food, namely how to optimize nutrition in foods consumed by people with diabetes mellitus. Genetic algorithms that have reliability in producing optimal output, can be utilized in the preparation of daily food composition. In this study used integer chromosome representation, extended intermediate crossover method, reciprocal exchange mutation method, and elitism selection method. The best solution is obtained using max generation of 709 generation; population size of 250 individual; crossover rate of 0,4; and mutation rate of 0,6. The results of the global analysis show the calorie content of the food composition of the system meets expert tolerance standards and on average system can save costs by 27,27%.
Implementasi Algoritme Genetika Untuk Optimasi Komposisi Gizi Menu Makanan Bagi penderita Stroke Hemoragik Sofi Hidyah Anggraini; Imam Cholissodin; Bayu Rahayudi
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

Stroke is one of the leading causes of death in the world. Hemorrhagic stroke becomes the most dangerous stroke because it can kill directly or even can leave a defect for the patient due to leakage or rupture of blood vessels in the brain. Thus, nutrition adjusment becomes one of the most important thing in preventing the recurrence of stroke and can recover the patient. Preparing a diet food menu for people with hemorrhagic stroke is not easy, because the preparation involves the equilibirum amount of nutritional menu and nutritional needs of patients. In this study, genetic algorithm implemented to solve the problem of diet food preparation for patients with hemorrhagic stroke. The data used as many as 42 data includes 12 carbohydrate, 15 animal protein, and 15 vegetable protein. The reproduction process uses the method of Extended Intermediate Crossover and Reciprocal Exchange Mutation by using permutation representation. The optimal parameter values of genetic algorithm based on the testing and analysis results are 0.1 and 0.9 for Crossover rate and mutation rate, 1000 for the population size, and 700 for the iteration amount on the convergence test.
Rekomendasi Pemberian Kredit Pemilikan Rumah (KPR) Pada Nasabah Bank Menggunakan Metode AHP - Topsis (Studi Kasus: PT. Bank Negara Indonesia. Tbk) Andriko Hedi Prasetyo; Imam Cholissodin; Edy Santoso
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

One of the important things that need or become a primary human need is a place to live or home. Many people can directly buy by credit. In this case the bank provides services for individuals who want to have a place to live or a decent house. This bank can be used as a financial institution that can ease the burden of the payment process to be able to make a home loan. In this study took a case study at PT. Bank Negara Indonesia (BNI) in the recommendation of granting KPR. With the increasingly brilliant Home Ownership Credit (KPR) program, every agency that provides a KPR program is demanded to be quick and precise in completing the families who apply for a KPR. So it requires time efficiency, accuracy of results in selecting mortgage customers and to improve the quality and service of the bank. Analytic Hierarchy Process Method - Order Preference Technique by Ideal Solution (AHP - TOPSIS) was chosen at the time of research because the AHP method has advantages in a different process from one another. And the TOPSIS method has advantages in practical decision making and the results of alternative decisions. The results of this study provide subreferences at 5 values that produce a value of λmax = 5.3351 CI = 0.0838 and CR = 0.0748 which get 85% accuracy results from 40 test data.
Co-Authors Achmad Arwan Adam Syarif Hidayatullah Adhipramana Raihan Yuthadi Adhitya Wira Castrena Adinugroho, Sigit Ageng Wibowo Agus Wahyu Widodo Aldino Caturrahmanto Alfen Hasiholan Alif Fachrony Ana Holifatun Nisa Anandita Azharunisa Sasmito Andika Eka Putra Andriko Hedi Prasetyo Anggi Novita Sari Anim Rofi'ah Annisa Alifia Annisaa Amalia Safitri Aqmal Maulana Tisno Nuryawan Ardiansyah Setiajati Arief Andy Soebroto Arina Indana Fahma Arsti Syadzwina Fauziah Atika Anggraeni Aulia Dinia Aulia Herdhyanti Aulia Jasmin Safira Azmi Makarima Yattaqillah Bahruddin El Hayat Bana Falakhi Bayu Andika Paripih Bayu Rahayudi Benita Salsabila Bisma Anassuka Bondan Sapta Prakoso Brendy Oscar Munthe Brigitta Ayu Kusuma Wardhany Budi Darma Setiawan Budi Santoso Candra Dewi Cindy Cynthia Nurkholis Citra Nadya Dwi Irianti Daisy Kurniawaty Danastri Ramya Mehaninda Daneswara Jauhari Daniel Agara Siregar Dellia Airyn Diah Priharsari Dian Eka Ratnawati Dieni Anindyasarathi Dinda Adilfi Wirahmi Diva Kurnianingtyas Dyah Ayu Wahyuning Dewi Edy Santoso Ega Ajie Kurnianto Elisa Julie Irianti Siahaan Ellita Nuryandhani Ananti Elmira Faustina Achmal Ema Agasta Ema Rosalina Eriq Muh. Adams Jonemaro Ersya Nadia Candra Fahri Ariseno Faizatul Amalia Faturrahman Muhammad Suryana Fayza Sakina Maghfira Darmawan Febriyani Riyanda Felicia Marvela Evanita Fendra Gunawan Ficry Agam Fathurrachman Fikhi Nugroho Fildzah Amalia Firda Priatmayanti Fitra Abdurrachman Bachtiar Franklid Gunawan Galih Ariwanda George Alexander Suwito Ghulam Mahmudi Al Azis Gregorius Dhanasatya Pudyakinarya Guruh Adi Purnomo Gusti Reza Maulana Heny Dwi Jayanti Heru Nurwarsito Himawat Aryadita Holiyanda Husada Husin Muhamad I Gusti Ayu Putri Diani Ibnu Rasyid Wijayanto Ichwanda Hamdhani Ika Oktaviandita Indriati Indriati Irma Lailatul Khoiriyah Ishak Panangian Sinaga Istiana Rachmi Izzatul Azizah Jeffrey Junior Tedjasulaksana Khairinnisa Rifna Khairiyyah Nur Aisyah Komang Anggada Sugiarta Kresentia Verena Septiana Toy Kukuh Wicaksono Wahyuditomo Laila Restu Setiya Wati Lailil Muflikhah Leni Istikomah Liwenki Jus'ma Olivia M. Ali Fauzi M. Khusnul Azhari Mahendro Agni Giri Pawoko Marji Marji Maulana Ahmad Maliki Maulana Putra Pambudi Mauldy Putra Pratama Mentari Adiza Putri Nasution Michael David Moch Bima Prakoso Moh. Ibnu Assayyis Mohammad Aditya Noviansyah Mohammad Angga Prasetya Askin Mohammad Toriq Muhammad Aghni Nur Lazuardy Muhammad Dio Reyhans Muhammad Fahmi Hidayatullah Muhammad Fuad Efendi Muhammad Halim Natsir Muhammad Hasbi Wa Kafa Muhammad Hidayat Muhammad Maulana Solihin Hidayatullah Muhammad Nadzir Muhammad Rizal Ma'rufi Muhammad Rois Al Haqq Muhammad Shafaat Muhammad Syafiq Muhammad Tanzil Furqon Muhammad Taufan Mukh. Mart Hans Luber Nabila Lubna Irbakanisa Nabilla Putri Sakinah Nadia Natasa Tresia Sitorus Nadia Siburian Nadiah Nur Fadillah Ramadhani Nining Nahdiah Satriani Noerhayati Djumaah Manis Novanto Yudistira Novirra Dwi Asri Nur Afifah Sugianto Nur Firra Hasjidla Nurul Hidayat Nurul Inayah Obed Manuel Silalahi Panji Husni Padhila Priscillia Vinda Gunawan Putra Pandu Adikara Putri Ratna Sari Radita Noer Pratiwi Randy Cahya Wihandika Ratih Kartika Dewi Rayhan Tsani Putra Renata Rizki Rafi` Athallah Restu Fitriawanti Reyvaldo Aditya Pradana Reza Aprilliana Fauzi Rien Difitria Rinindya Nurtiara Puteri Rio Cahyo Anggono Riski Ida Agustiyan Rizal Aditya Nugroho Rizal Setya Perdana Rizaldy Aditya Nugraha Rizky Ramadhan Rosintan Fatwa Rowan Rowan Sabrina Nurfadilla Salsabila Multazam Sandya Ratna Maruti Sari Narulita Hantari Satria Habiburrahman Fathul Hakim Sayyidah Karimah Shafira Eka Aulia Putri Shelly Puspa Ardina Shibron Arby Azizy Shinta Anggun Larasati Siti Mutdilah Sofi Hidyah Anggraini Stefanus Bayu Waskito Supraptoa Supraptoa Sutrisno Sutrisno Tara Dewanti Sukma Tibyani Tibyani Timothy Bastian Sianturi Tobing Setyawan Tony Faqih Prayogi Tusiarti Handayani Tusty Nadia Maghfira Uke Rahma Hidayah Uswatun Hasanah Utaminingrum, Fitri Vergy Ayu Kusumadewi Veronica Kristina Br Simamora Vinesia Yolanda Vivilia Putri Agustin Vivin Vidia Nurdiansyah Wahyu Bimantara Wanda Athira Luqyana Wicky Prabowo Juliastoro Windy Adira Istiqhfarani Yessica Inggir Febiola Yoseansi Mantharora Siahaan Yudha Ananda Kresna Yudo Juni Hardiko Yuita Arum Sari Yunico Ardian Pradana Yusuf Afandi Zanna Annisa Nur Azizah Fareza