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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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Optimasi Kebutuhan Gizi Menggunakan Algoritme Evolution Strategies Pada Balita Dan Ibu Menyusui Fahri Ariseno; Imam Cholissodin; Edy Santoso
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 7 (2020): Juli 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Parents need to pay attention on a diet of a toddler because of the food that being consumed during infancy greatly influences the growth and development of the toddler as well as the mother of the toddler who are still breastfeeding where the quality of the breast milk also greatly influences toddler growth. The lack of attention on a food that being consumed by toddler can cause various kinds of disease complication because of toddler body that still vulnerable and prone to infections, malnutrition, or obesity. This research will implement evolution strategies algorithm to obtain recommendations for the composition of the most optimal nutritional diets that can meet daily nutritional needs that did not exceed the daily limits for toddlers and breastfeeding mothers. The main cycle used in this study is the ES cycle (μ + λ) and three other ES cycles as comparison. Based on the results of tests conducted using the ES cycle (μ + λ) for a data of toddler and breastfeeding mothers on the parameters of μ = 10, λ = 100, and generation = 250, the best fitness result obtained are 0.225070 which recommendation are close to the daily nutritional needs of toddler and breastfeeding mother.
Optimasi Multiple Travelling Salesman Problem (M-TSP) pada Penentuan Rute Angkutan Sekolah menggunakan Algoritme Particle Swarm Optimization (PSO) Muhammad Hidayat; Imam Cholissodin; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 9 (2020): September 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Daarussalaam Muslim Development Foundation (YPM) is an educational foundation located on Jl. Jendral Sudirman No 1, Swarga Bara, Sangatta Utara, East Kutai Regency, East Kalimantan. In YPM Daarussalam there are several schools, namely integrated Islamic kindergartens (TKIT), integrated Islamic elementary schools (SDIT), and integrated Islamic junior high schools (SMPIT). To help the departure and return of kindergarten and elementary school students, the foundation provides school transportation services that can be used for students in need. At present the number of students using school transportation services is 160 students out of a total of 832 students. Based on this number the foundation provides 8 cars with a capacity of 20 students per cars. This study aims to determine the optimal route for the Multiple Traveling Salesman Problem (M-TSP) problem using Particle Swarm Optimization (PSO) algorithm. In this study the school route is represented as particles which are divided into 3 segments, namely departure (segment 1), return 1 for grade 1,2 students, and kindergarten and (segment 2) and return 2 for grade 3-6 students which then the particles will be update the speed of each iteration to find the route with the best fitness value. The parameters used are the number of iterations = 538, particle size = 80, C1 = 1, and C2 = 1.5. The average fitness obtained is 2,297 with the best fitness value of 2,393, and with these results the foundation can cut the distance by 210,884 Km.
Penerapan Algoritme Nearest Centroid Neighbor Classifier Based on K Local Means using Harmonic Mean Distance (LMKHNCN) untuk Klasifikasi Hasil Kinerja Pegawai Negeri Sipil (Studi Kasus Pegawai Negeri Sipil Kota Malang) Adam Syarif Hidayatullah; Fitra Abdurrachman Bachtiar; Imam Cholissodin
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 13 (2020): Publikasi Khusus Tahun 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Dipublikasikan di JTIIK pada vol 8 no 6 dengan tautan
Prediksi Price Earning Ratio Saham Menggunakan Algoritme Kernel Extreme Learning Machine (Studi Kasus: PT TELKOM) Mentari Adiza Putri Nasution; Imam Cholissodin; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 10 (2020): Oktober 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Stock investment is one of the most populer investments nowadays. This kind of investment has the "high risk high return" characteristic which come up with a threat of loss for stock investors. There are lots of paper have been implemented related to the estimation of stock price movements, but researchers focus more on technical analysis rather than fundamental analysis which is no less essential. One of the populer methods with a fundamental approach is Price Earning Ratio (PER) method. Extreme Learning Machine is a proven method of forecasting stocks with high performance and relatively low learning speed, but this method has weaknesses in determining random weights and biases that can reduce its stability. Kernel Extreme Learning Machine offers the utilization of kernel functions that can provide high stability and performance, but with relatively low learning speed. The results of this paper provide the optimal Mean Absolute Precentage Error (MAPE) is 2.78021%, with 8 features, training and testing data ratio 90%: 10%, using the Polynomial kernel function with a value of parameter 1, and using a regularization coefficient (λ) 1000. Nested Cross Validation evaluation was also performed which provide the MAPE value is 6.385713%.
Pelatihan Feedforward Neural Network Menggunakan Particle Swarm Optimization untuk Peramalan Harga Saham Fildzah Amalia; Imam Cholissodin; Arief Andy Soebroto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 10 (2020): Oktober 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Stock is a promising investment and very flexible, investors can sell their stock at any time either part or all of their stock. The high potential yield offered is what makes the stock so famous among the investors. However, the level of participation of the Indonesian people in investing in the stock market is still very low. Fluctuating stock prices are also one of the factors people are reluctant to become stock investors. Therefore, investment in stocks requires a good analysis so that investors can increase profits, one of them is by predicting stock prices from time to time so that future stock prices can be predicted by conducting technical analysis. In this study, forecasting is done using one of the artificial neural network methods, namely Feedforward Neural Network (FFNN) which is trained using the Particle Swarm Optimization (PSO) method. PSO algorithm is considered capable of replacing the Backpropagation algorithm in training networks. The error rate from forecasting results is calculated using Mean Absolute Percentage Error (MAPE). In the test the smallest MAPE value is 1,793% and fitness value is 0.98239 with 4 input layers, 2 hidden layers, and 1 output layer on the network architecture.
Penerapan Metode Fuzzy K-Nearest Neighbor pada Klasifikasi Penyakit Menular Seksual Pria Nadia Siburian; Imam Cholissodin; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 11 (2020): November 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

sexually transmitted diseases is one of the dangerous diseases that spreads every year, especially in the city of Malang. One of these educational cities has a growing human population each year so that it can be a trigger for the spread of the sexually transmitted diseases, especially for people who have sex. Based on information from the Malang Health Service, most people are exposed to sexually transmitted diseases without being aware of the symptoms that arise in them. Compared with women, more men who have a sexually transmitted infection. Sexually transmitted diseases in men such as Syphilis, HIV, Gonorrhea, Herpes and Warts have symptoms that have similarities in each disease so it is difficult to distinguish. To find out and reduce errors in predicting a disease, the Fuzzy k-Nearest Neighbor method is used in this study to help classify sexually transmitted diseases. The classification process consists of three processes are the fuzzy initialization process. The kNN algorithm process and the kNN fuzzy algorithm process. In the research test used the influence of K value testing, K-Fold Cross Validation test using 60 data divided into 10-fold and obtained the highest accuracy results of 91.67% with K = 5 then inter-class performance testing using confusion matrix to determine Precision and Recall values ​​on 30 test data.
Penerapan Metode Modified K-Nearest Neighbor pada Klasifikasi Penyakit Menular Seksual Pria Yoseansi Mantharora Siahaan; Imam Cholissodin; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 11 (2020): November 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Sexually transmitted diseasse are a type of disease that spreads quite quickly. According to a World Health Organization (WHO) report, cases of infection that spread through sexual contact can be found every day with sexually active populations, namely adults and adolescents, especially men. The similarity in symptoms for each disease and patients are generally less familiar with the initial symptoms so they cannot provide early help. By developing the Modified K-Nearest Neighbor algorithm and using the asymmetric binary distance, the test result obtained on the effect of the K values of 100% in the 9th test. The K-Fold = 10 gets 91,67% results by using K = 9. And the Precision value = 1for Gonorrhea and HIV classes, and Recall value = 1 for the Warts and HIV classes.
Implementasi Naive Bayes Classifier untuk Klasifikasi Emosi Tweet Berbahasa Indonesia pada Spark Rizal Aditya Nugroho; Imam Cholissodin; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 1 (2021): Januari 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Emotion is a natural thing that every human being has because it is a response to an event. Because emotions are owned by every human being, classifying emotions has many benefits, for example, for identifying customer complaints. Emotions can be found in textual sources such as tweets. Tweet data on Twitter itself has a size that is growing every year and a system that classifies emotions on tweets is needed that can handle the growing data quickly and accurately. In this study the classification is carried out using the Naive Bayes Classifier algorithm and also the Spark framework with the process starting from preprocessing, training to find prior and likelihood values, ​​then testing to find posterior values ​​and performing classification, and finally calculating accuracy. The Spark framework itself is used to do work in parallel for faster computing time. Based on the test results from tweet data on June 1, 2018 to June 14, 2018, the accuracy of the Naive Bayes Classifier method for the classification of Indonesian tweets on Spark has the highest average value of 0,892 when the percentage is 90% training data and 10% test data. Then the highest average value is 0,880 when using smoothing. And finally, the highest average value is 0.888 when using constant priors. Comparison of execution times from using Spark and sequentially has a very large difference that it is almost 165 times faster on Spark. In Spark, the execution time takes an average of 0,525 seconds, while in the sequential method it takes 86,564 seconds on average.
Optimasi Penjadwalan Pada Layanan Kursus dengan Algoritme Genetika (Studi Kasus: Unit Pengembangan Bahasa Universitas Brawijaya) Rio Cahyo Anggono; Imam Cholissodin; Edy Santoso
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 2 (2021): Februari 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Language Development Unit Universitas Brawijaya or Brawijaya Language Center (BLC)'s course service is one of the services most in demand by many people. The relatively cheap price and the schedule selection by each participant are the main factors why many people choose BLC. The lack in the BLC course service is from an administrative perspective. The course scheduling system is still done manually by the course administration. Therefore, it is necessary to conduct research related to course scheduling. In the future, this research can assist BLC in course scheduling. The method that will be used in this research is Genetic Algorithm. In this research, the genetic algorithm process includes initial population formation and chromosome representation, parent selection, crossover and mutation, calculation of fitness values, population replacement selection, and chromosome derepresentation. Based on the test results, the best parameter values are found in the population number 700, Cr 0.5, Mr 0.4, and the number of generations of 900 with a fitness value of 0.98182.
Pengelompokan Sentimen Pada Twitter Tentang Pendapat Masyarakat Terhadap Karantina Selama Pandemi COVID-19 Menggunakan Metode DBSCAN Noerhayati Djumaah Manis; Yuita Arum Sari; Imam Cholissodin
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 2 (2021): Februari 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Corona Virus 2019 (COVID-19) has now spread rapidly throughout the world since December 2019, so quarantine is carried out to limit the spread of the disease. The implementation of quarantine raises pros and cons from the public which makes the public express all their opinions and criticisms via Twitter. However, every tweet uploaded by the public does not contain the appropriate meaning so a sentiment analysis is necessary. The classification mechanism can be used to determine the polarity of sentiments but classification has its drawbacks. In the classification there is an unsupervised classification or clustering. The K-Means method is often used for clustering, but it still has weaknesses. Therefore, this study conducted a sentiment clustering on Twitter about public opinion of quarantine during COVID-19 pandemic using the DBSCAN method. Based on the results of tests carried out with 200 data, the best silhouette coefficient value is 0.32 at an epsilon value of 20 and a minPts value of 15, while the best davies bouldin index value is 0.10 at an epsilon value of 15 and a minPts value of 15. This research also gets more analysis results on neutral sentiment, which means that the public is of a neutral opinion towards quarantine during the COVID-19 pandemic.
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