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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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Implementasi Algoritme Genetika Dalam Penjadwalan Akademik Sekolah Menengah Atas Brawijaya Smart School Tobing Setyawan; Imam Cholissodin; Tibyani Tibyani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 7 (2019): Juli 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Scheduling is one of the most needed requirement for high school. Scheduling at brawijaya smart school senior high school(BSS SHS) had some problems like processing time, schedule size, Musyawarah Guru Mata Pelajaran(MGMP), and managing variety subjects. Scheduling took 3 days to be done. Problem space's size is 834 hours of subject. Teacher's schedule cannot crashed with MGMP. Variations of teachers and subjects cannot be the same within a day from those problems above researcher will use genetic algorithm to solve them. Genetic algorithm is an algorithm that can be used to get the solution that closed to optimum from the wide possibility solution area. In this research, researcher used partially-mapped crossover, reciprocal exchange mutation, and elitism selection. The result gets that the 233rd generation, 150 population size, 0,7 crossover ratio, and 0,3 mutation ratio are the most optimum solution parameter in BSS SHS scheduling case. This research has its disadvantage in early convergence that happened at 233rd generation so random injection is needed to be applied. Global and local search aren't effective because searching ratio is always the same. Population size was too big that difficults the searching for the best parent so parent selection needed to be applied.
Optimasi Multiple Travelling Salesman Problem (M-TSP) Pada Angkutan Sekolah Dengan Algoritme Genetika (Studi Kasus: Yayasan Pembina Muslim Daarussalaam Sangatta) Ageng Wibowo; Imam Cholissodin; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 7 (2019): Juli 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Pembina Muslim Daarussalaam Foundation is an educational institution located in Swarga Bara, North Sangatta, East Kutai Regency, East Kalimantan. The Foundation provides 8 school transports which are used to provide shuttle services for 160 Daarussalaam Islamic Kindergarten and Elementary students. The route for the shuttle is determined by the school transport driver. This research is conducted to determine the optimal shuttle route that will help school transport driver. The problem of this research is Multiple Traveling Salesman Problem (M-TSP) and one of the optimization methods that can help solve this problem is genetic algorithm. This research use a permutation representation, chromosome representation divided into 3 clusters, penjemputan (cluster 1), pengantaran 1 (cluster 2), and pengantaran 2 (cluster 3). Then the reproductive process is done by crossover with ordered crossover method and mutation with swap mutation method then the selection process is done by elitism selection method. With genetic algorithm that are 10.000 generations, population size 90, and combination of cr value = 0,6 and mr value = 0,4. The average fitness value in this research is 3,047. With the result of this research, Pembina Muslim Daarussalam Foundation can reduce the mileage by 400,82 KM and travel time around 877 minutes.
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.
Pengembangan Sistem Informasi Penilaian dan Evaluasi Kinerja Karyawan Dengan Metode Weighted Product Berbasis Web (Studi Kasus: UB Guest House) Brendy Oscar Munthe; Faizatul Amalia; 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

Employee performance assessment and evaluation at UB Guest House is used to determine the level of employee performance achievement. The assessment process is still done manually starting from the preparation of forms, assessing employees, calculating the results by each assessor who can provide opportunities for miscalculation, recapitulation in making reports to determine the best employees only done for 3 days Timelines that are not proportional to work and the possibility of red dates result in no re-checking so that they do not exceed the set time limit. The assessment report is used to find out the progress every month to be evaluated together with the Employee Performance Evaluation Form to make employee awards. This is inefficient because it makes it difficult to choose employees to evaluate and discard paper that supports the UB Guest House costs. A web-based employee performance assessment and evaluation information system was built to overcome these problems. System development applies the weighted product method used to provide recommendations in determining the best employees and is carried out using a waterfall development model. Unit tests show that cyclomatic complexity ≤ 10 with all test case statuses is valid. Integration testing obtained for all test case statuses is valid. Validation testing obtained valid status for all test cases. Testing accuracy using the weighted product method obtained an accuracy of an average of 92%. System compatibility tests are obtained which can be run on various browsers.
Klasifikasi Gangguan Jiwa Skizofrenia Menggunakan Algoritme Decision Tree C5.0 Febriyani Riyanda; Imam Cholissodin; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 10 (2019): Oktober 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Schizophrenia is one of psychiatric disorders which gets much concern all over the world. Schizophrenia requires a quick and precise treatment due to its chronic tendency. However, the insufficient service on mental disorder can cause patients are not addressed immediately and the height subjectivity amongst psychiatrists in determining the type of schizophrenia has similar symtoms can lead to schizophrenia classification errors. In this classification of mental disorders use the C5.0 decision tree algorithm, which has additional functions such as boosting. The data used were 106 data taken from the Dr. Radjiman Wediodiningrat Lawang Psychiatric Hospital, this data consists of 89 trained data and 17 test data. The test method being used is accuracy. Based on the results of testing the C5.0 parameter, the highest average accuracy value was 85.884% with the number of data = 71 samples, the number of trials or the number of decision tree = 100.
Klasifikasi Penyimpangan Tumbuh Kembang Anak Menggunakan Algoritme C5.0 Dyah Ayu Wahyuning Dewi; Imam Cholissodin; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 10 (2019): Oktober 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Developmental deviation of the child's development is a disruption of the process of growth and development resulting in the child experiencing a phase that is inhibited compared to other normal children. If it is not immediately treated, it is feared that the developmental deviation of the child's growth will be increasingly difficult to handle. For that we need the awareness of parents to immediately check the condition of the child at the doctor, in order to alleviate these irregularities. However, the number of patients is not proportional to the number of doctors available. Lack of doctors can result in slow handling of patients. To deal with this, a system of diversification of child growth and development was made using the C5.0 algorithm. In this study will be classified into three types of developmental deviations of children, namely autism, down syndrome, and ADHD (Attention Deficit Hyperactivity Disorder). C5.0 algorithm is one of the decision tree algorithms and is a development of C4.5. The difference in C4.5 and C5.0 is that in the C5.0 algorithm there is a boosting process, so that it can provide better accuracy than the C4.5 algorithm. From the research that has been done, the average value of accuracy in testing the amount of training data is 95.9%, the average accuracy in testing the number of trials is 97.3%, and the comparison testing of C4.5 and C5.0 results in accuracy at C5.0 is 93.33% while the accuracy at C4.5 is 87.61%. The things that affect the accuracy value are the large amount of data, and the number of trials used.
Optimasi K-Nearest Neighbor Menggunakan Bat Algorithm Untuk Klasifikasi Penyakit Ginjal Kronis Komang Anggada Sugiarta; Imam Cholissodin; Edy Santoso
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 10 (2019): Oktober 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Chronic Kidney Disease (CKD) is deadly disease and need high cost to do hemodialysis every week. CKD can happen because acute kidney disease for long time and not do any further treatment or change lifestyle to prevent CKD. So, people need to know is that potentially suffer CKD or not for early time. One of ways to know people suffer CKD is compare pattern with people that already suffer CKD. K-Nearest Neighbor is method that can to compare and classify data to nearest similarity of CKD's data. However, CKD has many feature that can use to classify people that suffer CKD. That feature can be people health data and lifestyle. That many feature must choose only most effective feature for classify CKD and discard the other feature. The feature selected can improve KNN to better classify CKD. KNN can know the better feature with try every combination feature. If KNN do that, it will need long time to find it. KNN need to improve efficiently and short way to know most effective feature for CKD. Bat Algorithm (BA) is method that can search solution that imitate behavior of bat. BA-KNN or combination BA and KNN proposed to solve the problem.
Penerapan Metode Extreme Learning Machine Untuk Prediksi Konsumsi Batubara Sektor Pembangkit Listrik Tenaga Uap Rosintan Fatwa; Imam Cholissodin; Yuita Arum Sari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 11 (2019): November 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

PLTU is a power station that utilizes coal as fuel. The PLTU sector is a dominant sector in absorbing domestic coal. During the period 2010 - 2015, coal consumption continued to increase along with the 35,000 MW power plant project which was designed in the 2015-2019 period, 19,940 MW (56%) was a coal-fired power plant. Based on data from the Director General of Mineral and Coal at the Ministry of Energy and Mineral Resources, said that the increase in coal consumption is due to the growing PLTU and the economic development which is directly proportional to the increase in national coal consumption. Based on these problems, the prediction of coal consumption in the power plant sector is needed so that coal consumption can be controlled in accordance with its production. In this study, the prediction process is carried out in several processes, namely data normalization, prediction calculation using Extreme Learning Machine, data denormalization, and error values ​​using MAPE. Based on the results of tests conducted on daily coal consumption data for 2018 at the Tanjung Jati B PLTU Unit 1 & 2 obtained the smallest MAPE value of 6.603% with many features 2, the number of hidden neurons as much as 4, and the comparison of the percentage of training data and testing data 70 %: 30% using the Sigmoid activation function.
Prediksi Penerimaan Bea Cukai Menggunakan Metode Support Vector Regression (Studi Kasus Di KPPBC Tipe Madya Pabean C Jember) Dinda Adilfi Wirahmi; Imam Cholissodin; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 11 (2019): November 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Customs has the responsibility as a collector of state revenue. Revenue has an important role in supporting infrastructure development. To manage revenue, prediction is needed to make a good APBN planning. To control revenue, predictions are needed as a prerequisite for good planning of the National Budget (APBN). Prediction is used as an action to optimize and control reception. However, revenue prediction are difficult to do because of the revenue influenced by external factors that difficult to predict. Therefore, logical and accountable agreements are needed to to revenue prediction. Predictions are used to prevent actual are lower than predetermined targets thereby increasing revenue that can be controlled because it has an impact on economic growth in Indonesia. The prediction method used is Support Vector Regression (SVR). This algorithm has a strong performance to recognize time series dataset patterns and provides good prediction results if the parameters are well determined because their performance is very dependent on the parameters within them. SVR implementation in this study uses RBF kernel with parameter variation values, namely sigma = 0.13, lambda = 3.29, cLR = 0.02, epsilon = 0.00001 and C = 10, iteration = 15000 and using 4 data features produce the best MAPE <20% so that it can be categorized that SVR is accurate in predicting customs revenue.
Klasifikasi Pertumbuhan Penduduk Kota Malang Menggunakan Hibridasi Algoritme Genetika dan Jaringan Syaraf Tiruan Obed Manuel Silalahi; Imam Cholissodin; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 12 (2019): Desember 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Population is one of the common problems that developed into a problem for developing countries including Indonesia. Malang, which is part of Indonesia, is known as a city of education and tourism that is sufficient to increase the population. These requirements certainly need special attention for the relevant parties to carry out certain policies in order to support population turnover. One thing that can be done is the classification of population growth based on age groups that can be done by the system efficiently. Based on this, we need a system that has scientific computing capabilities in its application. Backpropagation is a method of Artificial Neural Networks which is quite popular and helps to be used in data classification. This method can be combined with genetic algorithms in the optimization process of initial weights v and w. The ideal parameters obtained from the test include: K-fold = 8, a combination of the bipolar approval function, the number of generations of 10, the population number 75, the value of Cr = 0.8 and the value of Mr = 0.2, the number of iterations used 100, alpha value of 0.1 and hidden neurons 2 with the resulting accuracy of 92.86%.
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&#039;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&#039;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&#039;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