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

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Implementasi Modified K-Nearest Neighbor Dengan Otomatisasi Nilai K Pada Pengklasifikasian Penyakit Tanaman Kedelai Tri Halomoan Simanjuntak; Wayan Firdaus Mahmudy; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 2 (2017): Februari 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Various diseases and pest attacks can cause serious problems to the soybean crop. One threat to the soybean crop development research centers and is the developer of the plant pests. Pests can reduce soybean yields by 80 % even if no serious control. Classification is needed to determine the types of diseases that attack soybean plants. This research use of Soybean Disease Data Set consisting of 266 training data and desktop-based applications to be built by implementing the algorithm Modified K - Nearest Neighbor, the parameter value of K is determined by the system using brute force methods to find the best K value. Each value of K with accuracy the best results will be recorded and used as the parameter value of K in the process of testing new data. K values in this method to define the number of nearest neighbors used for the classification process. The test results showed that the value of the parameter K affects the classification results and the accuracy result. Average accuracy tends to decrease with the addition of the value of k , while increasing the number of training data also accompanied by an increase in the accuracy of the results, for training data with imbalanced class accuracy values decreased with increasing amount of data. The results of the highest accuracy on the test at 100 % with a value of k = 1 and an average accuracy of 5 times the experimental is 98.83 %.
Penerapan Algoritma Genetika untuk Optimasi Vehicle Routing Problem with Time Window (VRPTW) Studi Kasus Air Minum Kemasan Dita Sundarningsih; Wayan Firdaus Mahmudy; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 2 (2017): Februari 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Salah satu permasalahannya dalam bidang optimasi yaitu penentuan rute distribusi air minum kemasan. Air merupakan salah satu kebutuhan pokok bagi manuasia, sehingga banyak sekali permintaan untuk pemasokan air minum kemasan . Penentuan rute terpendek sangat penting karena pengiriman barang harus dilakukan dengan singkat dan tepat waktu dengan memaksimalkan penggunaan alat transportasi untuk mengurangi biaya transportasi. Vehicle Routing Problem (VRP) cenderung menyelsaikan permasalahan dengan meminimalkan biaya yang direpresentasikan oleh total jarak tempuh dan jumlah kendaraan yang digunakan. Oleh karena itu untuk menyelsaikan masalah lebih tepat menggunkan (Vehicle Routing Problem With Time Window) VRPTW, dengan tujuan menentukan optimasi rute yang dipengaruhi dengan Time window. Time window yang merupakan waktu pelayanan khusus yang disediakan oleh pelanggan. Algoritma Genetika merupakan salah satu algoritma yang dapat diterapkan untuk menyelesaikan Optimasi Distribusi Air Minum Kemasan dengan mendapatkan rute terbaik. Pencarian Solusi dilakukan dengan mengkombinasikan kromosom kemudian diproses dengan operator genetika (crossover, mutasi dan seleksi) dengan menginisialisasi parameter genetika (ukuran Populasi, probabilitas crossover, probabilitas mutasi dan jumlah generasi). Dari hasil pengujian diperoleh hasil terbaik dengan nilai fitness tertinggi pada ukuran populasi 100, jumlah generasi 2500 nilai probabilitasi crossover 0,3 dan probabilitas mutasi 0,7.
Penentuan Siswa Berprestasi Menggunakan Metode K-Nearest Neighbor dan Weighted Product (Studi Kasus : SMP Negeri 3 Mejayan) Jodi Irjaya Kartika; Edy Santoso; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 5 (2017): Mei 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Education has an important role to develop this country. The school as an educational institution must develop a variety of guidance systems that are motivating and developing potential of the student. One of them with the selection of student achievement.However, the general election student achievement is more focused in academic achievement. As in JHS 3 Mejayan, has no balance in election of student achievement because in the process of selecting student achievement weight voting greater than the value of the non-academic. So there a rises of a problem in determining the best weighting of each criterion both of them and it really takes time to selection of student achievement. To make it come true, needs to be made for a system that able to work fast and objectively in decision making so that the result were correct and could be called as student achievement. In manufacturing of a system is necessary to suppor the methods used. The methods used are K-Nearest Neighbor as a classifier and Weighted Product as to sorting. Based on the comparison between data expert with manually calculation from the school and output data system for K-Nearest Neighbor's method has an accuracy continuesly 56.67 % and 76.67%. Then, ranked comparison between data expert with manually calculation from the school and output data system for Weighted Product's method has an accuracy continuesly 11,1 % and 100%.
Sistem Pendukung Keputusan Pemilihan Personel Homeband Universitas Brawijaya Menggunakan Metode Profile Matching Aditya Sudarmadi; Edy Santoso; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 12 (2017): Desember 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Brawijaya Homeband University is a part of Students Unit Activities which has 2 years of regulation. In maintaining its existence, a selection is held in every 2 years. One of the problems was faced in previous selection was unclear scoring mechanism. This problem made the duration in selecting the member of the homeband longer. Moreover, the selection result was subjective. This manual mechanism is not an efficient meachanism, moreover when the participants are more than before. Research of Decission Suport System for Members Homeband Brawijaya University selection was using profile match technique. The positions which were wanted were male Vocalist, female vocalist, guitarist, bassist, keyboardist and drummer. Every position has 6 scoring factors which consist of 4 core factors and 2 secondary factors. The result of this research shows the accuracy system was 83.8%, 5 of 6 members selected by the system are the members who also selected by the judges. Therefore, it can be concluded the result of this research can be used for assisting the Homeband of Brawijaya University member's selection.
Implementasi Metode Profile Matching untuk Seleksi Penerimaan Anggota Asisten Praktikum (Studi Kasus : Laboratorium Pembelajaran Kelompok Praktikum Basis Data FILKOM) Fran's Dwi Saputra Atmanagara; Rekyan Regasari Mardi Putri; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 12 (2017): Desember 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Practicum is a learning method that is attempted to learners to better understand about the related learning materials. With practicum activities are expected learners can be more exploration about the material being studied. One of the factors so that learners can follow practicum activities well is with the guidance of a practicum assistant who has human resources (HR) quality. The selection process at the time of admission of a practicum assistant member is needed to find qualified human resources assistant assistant. The acceptance of a practicum assistant member is not expected to be subjective so that the quality of the assistant laboratory assistant obtained can be in line with expectations, so that no one will be harmed and more easily perform the task as a member of the practicum assistant. Profile Matching is one of the most suitable decision-making methods for selecting membership acceptance according to the required criteria. Profile Matching is a decision-making mechanism by assuming that there is an ideal predictor variable level that must be owned by an individual, not a minimum level that must be met or skipped. The result of system accuracy calculation by implementation Profile Matching method shows an accuracy of 86.6% in the recruitment stages of new members and 83.3% in the division placement stages. The performance of a designed system can be used to make a member accept decision with output in the form of ranking based on the highest end value to the lowest final value.
Sistem Pakar Berbasis Web Untuk Menentukan Pembagian Harta Waris Menurut Hukum Islam Menggunakan Metode Forward Chaining dan Dempster-Shafer Dhavin Putra Alamsyah; Sutrisno Sutrisno; Suprapto Suprapto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 2 (2018): Februari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Islamic law establishes inheritance rules with a very fair form. In it is the right of ownership of property for the heirs, both men and women in a fair way. Islamic law also establishes the right of shifting of ownership of a person after passing away to his heirs from all his relatives and nasabs, without distinction between men and women, young and old alike. But in its implementation, for the Islamic community itself, most of the determination and calculation of inheritance is done in a way that is not in accordance with the prevailing law of inheritance of Islam that often leads to conflict. In solving the limited problem of experts regarding inheritance law, it is necessary to design an application that can help solve the problem according to Islamic law. This thesis provides a more accurate decision using forward chaining and dempster-shafer methods based on an expert's trust. In the Dempster-Shafer theory there is a Frame of Discernment denoted by θ. This frame is the universe of speech from a set of hypotheses θ = {A, B, D, E}. The goal is to relate the trust size of the elements θ. Not all evidences directly support each element. Based on the testing of this system that is equal to 92.67% which means this system can run well because the results of the system close to the similarity with the fact of the actual field.
Implementasi Metode Artificial Bee Colony - Kmeans (ABCKM) Untuk Pengelompokan Biji Wijen Berdasarkan Sifat Warna Cangkang Biji Enny Trisnawati; Rekyan Regasari; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 3 (2018): Maret 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Sesame is one of the vegetable oil producers which consumption level in the world is expected to continue to increase, along with the many benefits and uses. The selling price of sesame is determined by the quality of the sesame. The indicator that can be used as a hint of the quality of sesame is the color on the seed shell. One of the efforts to produce the best quality sesame is by crossbreeding between cultivars that produce the color of the sesame seeds that vary, so it needs to be grouped by the closeness in color. Several ways that previous researchers have done to classify sesame seeds such as qualitative and quantitative methods. Currently, there are 3 models of quantitative methods for the sesame seeds grouping which are IWOKM method, PSO-K-Means and GA-KMeans which the result of data grouping is quite good. ABCKM method that were used in this research which is the combination of KMeans method (KM) and Artificial Bee Colony (ABC. The performance of ABCKM will then be compared with KM, IWOKM, PSO-K-Means and GA-KMeans methods.Based on the result of comparison test of method, ABCKM method proved better than KM method and the previous method: IWOKM, GA-KMEANS and PSO-K-Means in grouping the sesame data. This result proved by the average value of fitness and silhoutte coefficent when using ABCKM method better than KM, IWOKM, GA-KMEANS and PSO-K-Means. The result of the ABCKM method grouping is the same as the previous method C1: C2 = 233: 58, so method in this study can be used as an alternative method for sesame seed grouping based on color of seed shell.
Pengelompokan Biji Wijen Menggunakan Metode ACOKHM Berdasarkan Sifat Warna Cangkang Biji Rakhmadina Noviyanti; Rekyan Regasari Mardi Putri; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 4 (2018): April 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Wijen merupakan salah satu tumbuhan berpotensial karena menghasilkan minyak yang berguna dalam sektor industri. Identifikasi kualitas dalam tanaman wijen ditentukan dengan warna cangkang biji wijen. Sehingga perlu dilakukan persilangan benih wijen untuk menghasilkan wijen dengan kualitas baik. Hasil dari persilangan tersebut menghasilkan warna biji wijen yang beragam dan hampir mirip sehingga perlu dilakukan pengelompokan berdasarkan kedekatan warna. Beberapa penelitian terdahulu telah mengelompokan wijen secara kualitatif dengan pengamatan langsung dan kuantitatif menggunakan metode tertentu. Penelitian metode sebelumnya menggunakan 3 metode kuantitatif yaitu IWOKM, PSO-K-Means dan GA-KMEANS. Pada penelitian tersebut menggunakan data hasil pengukuran dengan alat chromameter yang menghasilkan data dengan atribut L* a* b*. Pada penelitian ini menggunakan data serupa dengan mengusulkan metode lain yaitu ACOKHM yang merupakan gabungan metode clustering (K-Harmonic Means) dan optimasi (Ant Colony Optimization). Hasil pengelompokan metode ACOKHM akan dibandingkan dengan metode terdahulu. Berdasarkan hasil pengelompokan penelitian ini akan diuji nilai fitness dan nilai kekompakan menunjukkan bahwa metode ACOKHM memiliki performa yang baik dengan nilai fitness yang mencapai 10,16899 dan nilai kekompakan kelompok mencapai 0,770765. Hasil pengelompokan data wijen juga mirip dengan penelitian sebelumnya dengan C1 : C2 adalah 233 : 58. Sehingga metode pada penelitian ini cocok dan memiliki performa yang baik dalam mengelompokan data wijen.
Implementasi Metode Ensemble K-Nearest Neighbor untuk Prediksi Nilai Tukar Rupiah Terhadap Dollar Amerika Rezza Hary Dwi Satriya; Edy Santoso; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 4 (2018): April 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The exchange rate is the currency unit price agreed by each country as a means of payment or transaction. The most used exchange rate in Indonesia is the rupiah exchange rate against the dollar. The dollar is the most stable currency in the economy. The high or low of the rupiah exchange rate is influenced by rates of interest, inflation, exports, imports, and sovereign debt. The exchange rate also has an important role in determining economic policy. In order to obtain an appropriate economic policy in the future situation and conditions, it is necessary to use a solution by using Ensemble kNN algorithm to predict the future rupiah exchange rate. The count of data was used in this research are 24 data training and 12 data testing. The data training and testing consists of 5 parameters, such as BI rate, Inflation, Export, Import, and sovereign debt. The Ensemble kNN algorithm uses a supervised learning, which the data testing is classified based on the majority of classes on kNN. The principle of kNN is to find the K variable from the data training which having closest similarity to the data testing. Ensemble technique is used to optimize kNN algorithm to get more accurate result. The result from this prediction system was evaluated by using MAE, MAPE and RMSEP. The obtained value of MAE buy = 456.56, selling MAE = 460.96, MAPE buy = 3.47%, MAPE selling = 3.47%, and RMSEP buy = 534.88, RMSEP selling = 540.07. The final result is the conformity of result and the pattern which produced between the predicted data and the actual data.
Aplikasi Penentuan Lokasi untuk Usaha Lapangan Futsal di Kecamatan Bangil Menggunakan Metode Fuzzy Tsukamoto Muhammad Alfian Nuris Shobah; Edy Santoso; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 7 (2018): Juli 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The system is built with the aim to help predict the results of operations of futsal in Bangil. In futsal open businesses have competitor input, the number of residents, the facilities, the size of the field. And this system produces an output stratification business opportunities, namely the village suitable for open futsal field. These systems are processed using fuzzy logic reasoning method Tsukamoto. The purpose application made to function as expected that is able to help resolve problems that arise and are difficult to solve because of an uncertainty which is very thin difference. From the data obtained will be an Tsukamoto fuzzy calculation that produces an output to be able to predict the circumstances that will occur from the input-input affecting. From the test results the decision-making system of determining the right location to open futsal in Kecematan Bangil with Tsukamoto method to 7 futsal some courts have precisely select locations, but the majority is still not right.
Co-Authors Abas Saritua Gultom Achmad Dwi Noviyanto Adinugroho, Sigit Aditya Negara Aditya Sudarmadi Agi Putra Kharisma Ahmad Galang Satria Anandita Azharunisa Sasmito Andi Amaliyah Maryama Arthur Julio Risa Ashshiddiqi Axel Iskandar Budi Darma Setiawan Candra Dewi Chalid Ahmad Aulia Chindy Putri Beauty Cindy Inka Sari Danastri Ramya Mehaninda Deby Chintya Dewi Syafira Dhavin Putra Alamsyah Dhimas Tungga Satya Dina Dahniawati Dita Sundarningsih Dyah Ayu Wahyuning Dewi Edy Santoso Endah Utik Wahyuningtyas Enny Trisnawati Fajar Pradana Faraz Dhia Alkadri Febriyani Riyanda Filan Maula Andini Firhad Rinaldi Saputra Fran's Dwi Saputra Atmanagara Galih Aulia Rahmadanu Heru Budiyanto Ian Lord Perdana Imam Cholissodin Imam Farouqi Faisal Inas Nabila Indri Monika Parapat Indriati Indriati Jeowandha Ria Wiyani Jodi Irjaya Kartika Karuniawan Susanto Kukuh Wicaksono Wahyuditomo M. Ali Fauzi Mahardhika Hendra Bagaskara Marji Marji Miracle Fachrunnisa Almas Mochamad Ali Fahmi Mochamad Rafli Andriansyah Mohamad Yusuf Arrahman Muhammad Abdan Mulia Muhammad Alfian Nuris Shobah Muhammad Hafidzullah Muhammad Tanzil Furqon Nanda Firizki Ananta Nurul Hidayat Putra Pandu Adikara Putri Indhira Utami Paudi Rachmad Faqih Santoso Rachmad Ridlo Baihaqi Rahmatsyah Rahmatsyah Rakhmadina Noviyanti Randy Cahya Wihandika Ratih Kartika Dewi Rayindita Siwie Mazayantri Rekyan Regasari Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Retno Indah Rokhmawati Rezza Hary Dwi Satriya Rich Juniadi Domitri Simamora Riski Adam Elimade Rizal Maulana Sabrina Nurfadilla Safira Dyah Karina Siti Utami Fhylayli Supraptoa Supraptoa Thariq Muhammad Firdausy Tibyani Tibyani Tri Halomoan Simanjuntak Tunggul Prastyo Sriatmoko Wayan Firdaus Mahmudy Widya Amala Sholikhah Yose Parman Putra Sinamo Yuita Arum Sari