Article Per Year (5 Year)
p-Index From 2021 - 2026
7.48
P-Index
This Author published in this journals
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

Published : 179 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 179 Documents
Search

 14   15   16   17   18 
Pengembangan Sistem Informasi Penjualan Sayuran berbasis Web dengan menggunakan Metode Waterfall Studi Kasus : (Agro Techno Park Universitas Brawijaya) Riski Ida Agustiyan; Imam Cholissodin; Arief Andy Soebroto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 12 (2021): Desember 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Agro Techno Park is a place for the development of agricultural products that are managed for agricultural entrepreneurship and a place for agricultural technology services. the purpose of the Agro Techno Park is as a center for the application of technology in agriculture, fisheries, and animal husbandry. One example of an Agro Techno Park located in East Java is owned by Brawijaya University which is located in Cangar and Jatikerto. In the marketing of Agro Techno Park products, UB still uses the manual method, namely by marketing products through the social network WhatsApp. By using this method, Agro Techo Park UB faces certain difficulties when receiving orders from customers. Because customers sometimes order products at the time of delivery, Agro Techno Park UB will come back again to take orders that have been added. In this case, of course, it takes a lot of time to make buying and selling transactions. People don't even know that Agro Tecno Park UB's vegetable products can be sold with quality vegetables. To solve this problem, the authors developed a Vegetable Sales Information System in Agro Techno Park UB. This system was developed to facilitate buying and selling transactions at Agro Techno Park UB and to expand the marketing segment of the vegetable products being sold. System development is carried out on a-based website and using the model waterfall using theprogramming PHP language on the Laravel framework. The system will be tested using the method white box, black box, integration testing, validation testing, and compatibility testing.
Optimasi Rute Pendistribusian Obat Pedagang Besar Farmasi di Apotek Kota Kediri menggunakan Algoritma K-Means dan Artificial Bee Colony (ABCKM) Cindy Cynthia Nurkholis; Imam Cholissodin; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 2 (2022): Februari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Pharmaceutical wholesaler is a business that already has a license to distribute pharmaceutical products. In product distribution, there are pharmacies that are close by, no delivery is made, so the courier returns again and gets a larger total distance. Thus, pharmaceutical wholesalers need an optimal route for distributing pharmaceutical products. This problem is a Multi Traveling Salesman Problem (MTSP). The K-Means and Artificial Bee Colony algorithms were chosen to solve the MTSP problem because the K-Means algorithm can be used to share data with the best sources. The solution used in K-Means is the closest neighbor coordinate solution only. So that an artificial bee colony algorithm is needed to help avoid being trapped in the local optima. The artificial bee colony algorithm will be used in finding the optimal route in the problem of optimizing the distribution route of pharmaceutical products at the Kediri City Pharmacy. From the research conducted, it is proven that the ABCKM algorithm is proven to be better than the ABC algorithm and better than using the distribution route carried out by the current courier. From the research, the artificial bee colony algorithm achieves convergence in finding the best solution with a popsize of 70, a limit of 25, and a maximum iteration of 700. From the optimal parameters, the best fitness value is 0.012193.
Optimasi Rute Pendistribusian Produk Bebicare di Kabupaten Sidoarjo dengan Pendekatan Algoritma Genetika Ema Rosalina; Imam Cholissodin; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 2 (2022): Februari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Distribution is the process of distributing products or services to other parties. Bebicare is an organic baby food product produced by PT. ANUGERAH JAYA MANDIRI. One of the branches of this company is Bebicare Sidoarjo branch. It has 25 outlets that sell products for two and a half hours every day. In the delivery process, there is often a delay in the arrival of products to outlets which results in switching customers to competing products and decreasing sales turnover. The purpose of this study was to find the optimal distribution route for Bebicare products. The method used in the process of finding the optimal distribution route for Bebicare products is to use a genetic algorithm. First, enter the distance data, then the data will be processed using a genetic algorithm, after which the results will be obtained in the form of a distribution route for the Bebicare product. From this study, optimal parameters were obtained in the form of a population of 190, a combination of Cr 0.6 Mr. 0.4, the generations 1150, and the shortest total distance of 118.25 kilometers. The program result route is more optimal than the original route because it has a shorter distance.
Optimasi Rute Distribusi Gas Lpg 3 Kg dengan Integrasi Algoritma K-Means dan Ant Colony Optimization pada Multiple Travelling Salesman Problem Liwenki Jus'ma Olivia; Bayu Rahayudi; Imam Cholissodin
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 2 (2022): Februari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Multiple Traveling Salesman Problem (TSP) is a development of the Traveling Salesman Problem in which the TSP only has one salesperson, while the M-TSP can have more than one salesperson With more than one sales, the distribution process will be faster and can reduce transportation costs. PT. Tegal Ombo Makmur is one of the companies that carry out distribution activities in which each salesperson will determine the route of the agent's address to be addressed and it is not uncommon to determine the route that is not efficient or not optimal so that it is a waste of time, energy, and costs. To solve the MTSP problem, this research proposes the use of the K-Means method and the Ant Colony Optimization (K-ACO) Algorithm. The K-Means method is used for optimal city division and then the shortest route will be searched using the ACO Algorithm. The best results were obtained with 4 salesmen and 91 points at the time of iteration at K-Means of 400, parameter NcMax or iterations is 3000, the value of is 1, the value of is 0.9,the value of is 0,9, and the value of is 0.04. Then the total distance generated by the system is 207.94 km, while the total route distance from the company is 466.45 km. Multiple Traveling Salesman Problem (TSP) is a development of the Traveling Salesman Problem in which the TSP only has one salesperson, while the M-TSP can have more than one salesperson With more than one sales, the distribution process will be faster and can reduce transportation costs. PT. Tegal Ombo Makmur is one of the companies that carry out distribution activities in which each salesperson will determine the route of the agent's address to be addressed and it is not uncommon to determine the route that is not efficient or not optimal so that it is a waste of time, energy, and costs. To solve the MTSP problem, this research proposes the use of the K-Means method and the Ant Colony Optimization (K-ACO) Algorithm. The K-Means method is used for optimal city division and then the shortest route will be searched using the ACO Algorithm. The best results were obtained with 4 salesmen and 91 points at the time of iteration at K-Means of 400, parameter NcMax or iterations is 3000, the value of is 1, the value of is 0.9,the value of is 0,9, and the value of is 0.04. Then the total distance generated by the system is 207.94 km, while the total route distance from the company is 466.45 km.
Optimasi Pendistribusian Air Mineral menggunakan Algoritma Genetika Arsti Syadzwina Fauziah; Imam Cholissodin; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 2 (2022): Februari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Distribution is one of the marketing activities carried out with the aim of distributing products from producers to consumers. This distribution is very important in marketing activities, if there is no distribution activity then the goods will not reach consumers from less affordable areas. Mineral water products almost dominate the beverage industry market and with population growth it is possible that the need for mineral water will continue to increase. At the point when the interest for mineral water expands, the job of distribution turns out to be important. In this distribution interaction, a method is needed that can handle the problems, this research was carried out using the Genetic Algorithm method in finding the optimization value contained in the Traveling Salesman Problem (TSP) to find the optimal total distance value in this distribution activity. Based on this research, the parameters are the cr 0.1, the mr 0.9, the popsize is 1000th population. The maximum iteration is 100th generation, the average fitnesss is 0.006438, and the total distance generated is more optimal than the route made by the courier of 35.3 km on the first courier, 35.8 km on the second courier and 34.9 km on the third courier.
Optimasi Rute Multiple Travelling Salesman Problem Distribusi Produk PT Indomarco Adi Prima (Stock Point Nganjuk) menggunakan Algoritme Ant Colony Optimization dan Algoritme Genetika Bisma Anassuka; Imam Cholissodin; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 3 (2022): Mei 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

PT. Indomarco Adi prima (Stock Point Nganjuk) is a company engaged in the distribution sector. Good transportation and distribution are important in a distribution company, where products can be delivered to consumers in good conditions, at the designated place and on time. Product distribution from PT. Indomarco Adi Prima (Stock Point Nganjuk) to consumers through stores on a large scale is a fairly complex problem, because there are many locations that must be visited. This problem and involves many sales called the Multiple Traveling Salesman Problem. Inappropriate route selection can reduce efficiency in the distribution process. So, it is necessary to make optimization to get the optimal route. This research is an attempt to optimize the route using the hybrid ant colony optimization (ACO) algorithm and genetic algorithm, so that it can determine the shortest route that will be passed by sales to retail stores. The test results show that the hybrid ant colony optimization (ACO) algorithm and genetic algorithm are able to produce a 74,3% better route than the previous route with a total distance difference of 709.219km. The optimal parameters obtained are the maximum ACO iteration of 100, the number of GA generations of 20, the number of ants is equal to the point of each salesman, a combination of α= 0.4 and β= 0.8, a combination of Cr= 1, and Mr= 0.6, so that the total distance average is 244.849 km and the fitness value is 0.040841.
Klasifikasi Mutu Susu Sapi menggunakan Metode Modified K-Nearest Neighbor (MKNN) Reyvaldo Aditya Pradana; Imam Cholissodin; Nurul Hidayat
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 3 (2022): Mei 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Milk is a very complex food ingredient, because milk has many ingredients needed by the human body. It is necessary to control the quality of cow's milk in order to produce high quality dairy products. With the development of food technology for cow's milk products, UPT Laboratory of Animal Health Malang by creating an application system that can classify the quality of cow's milk. This cow's milk quality application system uses input in the form of chemical composition where this composition is taken with the Julie C2 Milkscope tool. The chemical composition of milk consists of fat, lean dry matter, viscosity, lactose and protein. There are various methods used. This study uses the Modified K-Nearest Neighbor method and the dataset used is 269 cow's milk quality data with 5 parameters and 2 yield classes. Based on several studies, the Modified K-Nearest Neighbor method can be used in the classification process and obtain a fairly high level of accuracy. Based on the test results, the average test accuracy value of K value is 91.1%, then the average value of the accuracy of testing the effect of the amount of training data is 88.4%, and the average value of balanced and unbalanced class testing accuracy is 86.12%. It can be concluded that the Modified K-Nearest Neighbor method can be implemented and tested into the cow's milk quality classification system.
Klasifikasi Status Gizi Balita menggunakan Metode Optimasi Random Forest dengan Algoritme Genetika (Studi Kasus: Puskesmas Cakru) Ersya Nadia Candra; Imam Cholissodin; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 5 (2022): Mei 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Nutritional problems in the critical period of toddlers aged 0-59 years have a fatal impact on a person's growth and development in the future. Due to lack of or excess nutrition in the first 2 years of life, it causes permanent brain function impairment and degenerative diseases. In this case, the monitoring and examination of the nutritional status of children under five carried out by health workers and posyandu cadres are generally carried out by manual recording and further analysis is carried out by comparing the nutritional measurement data of children under five with nutritional status standards. The manual analysis is prone to errors of inaccuracy in identifying the nutritional status of children under five and takes a long time due to the large amount of data, so it's not practicable. Based on these problems, the authors apply the random forest method which is optimized with genetic algorithms to classify the nutritional status of toddlers accurately and quickly. After testing, the average accuracy by the random forest method optimized with genetic algorithms is 89.58%, the average precision is 74,34%, the average recall is 58,68%, and the f1-score is 65,54% with a population size parameter of 20, 3 iterations, a crossover rate value of 0,7, an mutation rate value of 0,3, and the number of features 4. From the evaluation results of accuracy, precision, recall and f1-score obtained in this study, it shows that the genetic algorithm is able to find optimal parameters from random forests so as to produce higher accuracy, precision, recall and f1-score.
Klasifikasi Pengaruh Polusi Udara di Indonesia terhadap Kesehatan menggunakan Algoritme Kernel Modified K-Nearest Neighbor Fayza Sakina Maghfira Darmawan; Imam Cholissodin; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 6 (2022): Juni 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Air pollution has many problems, one of which is health problems. The effect of air pollution on health can have a mild, severe, and even death effect. The solution to this problem is to classify so that the amount of levels that cause air pollution gives the appropriate results of influence. The method used in this study is the Kernel Modified K-Nearest Neighbor (KMKNN) algorithm. KMKNN is a modified algorithm of KNN (MKNN) that uses kernel distance. The data used is 480 data with three features and twelve classes. In the research test, the data sharing methods used were K-Fold Cross Validation and Hold-Out. The test was performed using three different kernels. The best constant of the RBF kernel is 0,97 at constants 1 through 5. The best parameter degree of polynomial kernels is 0,97 at degrees 1 and 2. The results of the K-Fold test with each kernel provide an average accuracy at 0,87. The Hold-Out test results of each kernel provide the highest average accuracy of 70%:30% split at 0,972.
Sistem Pakar untuk Diagnosis Penyakit Ayam menggunakan Metode Certainty Factor (Studi Kasus: Balai Besar Pelatihan Peternakan Batu) Ishak Panangian Sinaga; Arief Andy Soebroto; Imam Cholissodin
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 6 (2022): Juni 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Chickens are livestock that are mostly kept by the people of Indonesia, both kept in small quantities to large numbers which are developed in large-scale chicken farms. The choice of people to choose to raise chickens is none other than due to easy maintenance, high public consumption, so that raising chickens is a promising source of income. However, chicken farming itself is very at risk of experiencing a cycle of losses as happened in 2020 where there is a mass transmission of chicken diseases. This mass transmission of chicken disease occurs due to various factors. To overcome this problem, chicken farmers usually consult with experts but for this sector the number of experts is still small so the community really needs the presence of experts to help deal with this problem. To solve this problem, an expert system for diagnosis of chicken disease was built where the expert system is a computer program designed to model the problem solving ability of an expert. The application of this expert system will make it easier for chicken farmers to diagnose disease and treat the same as experts. This expert system is implemented with the Certainty Factor method where this method will provide as accurate results as possible because the certainty value obtained from the expert will always be maintained stable due to calculations To find the certainty value, only two data are used. The application of the Certainty Factor method to the expert system has several stages, from getting the MB and MD values, performing operations according to the Certainty Factor equation to get the CF value and to get the combined CF value using the combined CF equation.
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