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Nurul Hidayat
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Implementasi Metode Analytical Hierarchy Process dengan Weighted Product untuk Rekomendasi Penentuan Pegawai Terbaik berdasarkan Kinerja (Studi Kasus Divisi CCRD Bank BTN Kantor Pusat Jakarta) Irvan Windy Prastyo; Nurul Hidayat; Tibyani Tibyani
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 is a factor that influences the results to be achieved by a company. The effort are made to achieve the target of the Bank Tabungan Negara (BTN) Consumer Collection & Remedial Division (CCRD) division on employee performance is to assess employee performance. This study aims to apply the algorithm Analytic Hierarchy Process with Weighted Product method, and test the accuracy of recommendations for determining the best employee of the BTN CCRD division. The basic method used in this research is the AHP-WP method. The Analytic Hierarchy Process (AHP) method in this study will be used for weighting criteria and followed by the Weighted Product (WP) method to calculate the alternative value of each of the criteria and provide a sequence of recommendations for employees. This system uses 60 data which form the basis of calculations with 10 test data in each position with as many as 6 positions, namely ST, STC, AFC, TLFC, CS, and BC. The application of the AHP-WP method is to determine the recommendations of the best employees of the BTN bank by using assessment criteria such as shifting, damming, restructuring, ICOLL input, assessment 1, assessment 2 and assessment 3, and each position has different criteria. The results of this study indicate that the design of employee recommendation systems using the Analytic Hierarchy Process with Weighted Product method with the system java programming language running well, with the results in accordance with the manualization calculation and obtained the highest correlation closeness which is 1, which means perfect correlation and the lowest 0.5, which means a quite thightly correlation with each of the 5 top ranking and 5 lastly data in testing.
Sistem Diagnosis Penyakit Jantung Menggunakan Metode Modified K-Nearest Neighbor Kholif Beryl Gibran; Nurul Hidayat; Tibyani Tibyani
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

Cardia is included in the unit which is very crucial for human physical. As a blood pump to each limb is the main function of the cardia. Loss of the function of the cardia tissue and abnormalities of the cardia regulator and infection can be caused by cardia failure occurs when the cardia is no longer able to meet the level of nutrition and oxygen needs of the body. Based on the report of the World Health Unit (WHO) caused by cardia disease one third of the 58 million people who died in 2005 (Afriansyah 2009). The cause of death number 1 in the world for now is cardia. Cardia disease causes at least 30% of deaths in almost the entire world or about 17 and a half million in 2005. According to the World Health Organization (WHO), while coronary cardia disease itself causes 60% of deaths due to cardia (WHO, 2007). While 26.4 percent of deaths are due to cardiovascular disease including coronary cardia, it is based on the National Census conducted in 2001 (MOH RI, 2003). According to the explanation of the problem that has been described and also according to the exposure of previous studies, therefore the appropriate title for this research is "Diagnosis System for Heart Disease Using the Modified K-NN (MKNN) Method".
Komparasi Metode Data Mining Support Vector Machine dengan Naive Bayes untuk Klasifikasi Status Kualitas Air Ricky Marten Sahalatua Tumangger; Nurul Hidayat; Marji Marji
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

Water is a chemical compound that is very important for every living thing for survival on this earth. On earth water has a very large area compared to the mainland this compound has an area of ​​almost 71% around the land. The water also consists of sea water, rivers, lakes, ground water, swamp water, snow and steam which are in the air layer that contains mineral substances that are recruited in water. To determine the classification of water quality status using the Support Vector Machine and Naive Bayes methods. This method was chosen because previous studies get high accuracy results for classification. The parameters used are the degree of acidity (pH), TDS, NO2, NO3, hardness, chloride, manganese. The Vector Machine and Naive Bayes Suppord method will provide the results of the comparison of the accuracy of the two methods. Testing on the system is done using the K-Fold Cross Valadation test with the highest accuracy results when K = 9 for the Support Vector Machine method and K = 5 for the Naive Bayes method. Testing parameters for the Support Vector Machine method gets the highest accuracy when the threshold value is , C = 3, γ = 0.01, λ = 2.5, maximum iteration value = 1, σ = 0.1. From these tests the accuracy of the Support Vector Machine method was 78.70% and the Naive Bayes method was 85.78%. The best results obtained by the classification of water quality status are the Naive Bayes method compared to using the Support Vector Machine method because the average accuracy of the Naive Bayes method is higher. Water is a chemical compound that is very important for every living thing for survival on this earth. On earth water has a very large area compared to the mainland this compound has an area of ​​almost 71% around the land. The water also consists of sea water, rivers, lakes, ground water, swamp water, snow and steam which are in the air layer that contains mineral substances that are recruited in water. To determine the classification of water quality status using the Support Vector Machine and Naive Bayes methods. This method was chosen because previous studies get high accuracy results for classification. The parameters used are the degree of acidity (pH), TDS, NO2, NO3, hardness, chloride, manganese. The Vector Machine and Naive Bayes Suppord method will provide the results of the comparison of the accuracy of the two methods. Testing on the system is done using the K-Fold Cross Valadation test with the highest accuracy results when K = 9 for the Support Vector Machine method and K = 5 for the Naive Bayes method. Testing parameters for the Support Vector Machine method gets the highest accuracy when the threshold value is , C = 3, γ = 0.01, λ = 2.5, maximum iteration value = 1, σ = 0.1. From these tests the accuracy of the Support Vector Machine method was 78.70% and the Naive Bayes method was 85.78%. The best results obtained by the classification of water quality status are the Naive Bayes method compared to using the Support Vector Machine method because the average accuracy of the Naive Bayes method is higher.
Diagnosis Penyakit pada Anjing Menggunakan Metode Promethee Aditya Purwa Pangestu; Nurul Hidayat; Ratih Kartika Dewi
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

Dogs are one of the animals that are often found as pets. The interaction between humans and dogs has many health benefits such as helping reduce stress and making their owners have a more active lifestyle. However, the health of the pet itself must be considered. Dogs that are at risk of developing a disease have the effect of being able to transmit it to other pets or even humans, the condition becomes a little difficult if the new owner realizes that his dog is in an unhealthy condition outside working hours. The limited number of veterinary clinics that can handle patients outside of working hours makes dog owners must be able to provide early treatment immediately. To deal with the problems that arise, a system is needed to help diagnose dog disease by utilizing the Promethee method to help dog owners to detect early dog ​​diseases so that early treatment can be carried out immediately. The system is implemented using the Java programming language. There are 10 types of diseases with symptoms as many as 46. Based on the accuracy testing carried out, the average maximum accuracy is 98%.
Implementasi Algoritme Fuzzy Tsukamoto untuk Penilaian Kinerja Pegawai PT. Bank Tabungan Negara (Persero) Divisi CCRD (Consumer Collection & Remedial Division) Muhammad Resna; Nurul Hidayat; Tibyani Tibyani
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

Employees are people who work in a company by getting a salary (wage) from the company. The employees performance is the work of quality and quantity achieved by an employee in carrying out his duties in accordance with the responsibilities given to him. So that every company needs assessment of performance for the company to evaluate the performance of each employee in every month. At Bank Tabungan Negara (Persero) company, the CCRD division (Consumer Collection & Remedial Division) still uses the Microsoft Excel scoring system so that a system that can facilitate leaders to assess employee performance and provide a more accurate assessment are needed. The solution for making this system is by using the Fuzzy Tsukamoto method. Fuzzy Tsukamoto is used to calculate the rating of each employee in each position. Based on the accuracy testing that has been done, from 50 Skip Tracer position test data, 30 Assistant Field Collector position test data, 10 Field Collector position test data, 8 Skip Tracer Coordinator position test data, 10 Team Leader Field Collector position test data, 5 Collective Staff position test data, and 5 Branch Coordinator position test data. So from the test data, Branch Coordinator positions get accuracy of 86%, Branch Coordinator positions by 76%, Field Collector positions by 70%, Skip Tracer Coordinator positions by 75%, Team Leader Field Collector positions by 90%, Team Leader Field Collector positions by 60%, and Branch Coordinator positions by 80%.
Implementasi Metode FKNN (Fuzzy K-Nearest Neighbor) Untuk Diagnosis Penyakit Tanaman Kentang Jiwandani Andromeda; Nurul Hidayat; Ratih Kartika Dewi
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

Solanum taberosum (Potatoes) is one of the staple foods of humans because it is one of the tubers that has a good content. The content of protein and carbohirat can be fairly balanced so it is good for health. Potato production in Indonesia experienced a 9.82% reduction in production, from 1,176,304 tons in 2009 and in 2010 to 1,060,805 tons. Potato production in 2009 also decreased by 16.51 tons / hectare to 15.95 tons / hectare. Potato cultivation so far has several obstacles such as diseases and pests. Late blight is a major disease in potato plants. This disease has a lot of genetic heterogeneity so that plants become vulnerable to broken. Losses caused are fairly high in potato plants, especially in weather with high humidity. One of the solutions to make this plant easy to develop is by using varieties that have genetic resistance to the P. infestans race found in wild potato species. However, the genetic utilization of wild potato plants cannot be used for the development of commercial potato plants because they have different genetic makeup. To reduce failures in potato cultivation, software technology is currently needed to help detect diseases early on potatoes in order to facilitate farmers in potato cultivation.
Implementasi Metode Modified K-Nearest Neighbor untuk Klasifikasi Status Gunung Berapi Fikar Cevi Anggian; Nurul Hidayat; Muhammad Tanzil Furqon
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

Indonesia has numerous disaster-prone area, therefore, it is known as a 1001 disaster country. Natural disasters are inevitable, nevertheless, the impact can be minimized with proper anticipation. One of the disasters that often occur in Indonesia is volcanic eruption. Indonesia has 127 active volcanoes that are ready to erupt anytime. Indonesia is also known to contribute to around 30% of the world's volcanoes, and they are located near the residential areas. Casualties are often found in every volcanic eruption due to lack of anticipation from residents who live nearby the volcano. To minimize life and material loss, early warning is needed to provide quick and accurate notification of the volcano. This research used the Modified K-Nearest Neighbor method to classify volcano status. The data used are 110 data obtained from the official government agency that authorized to issue volcanic status, known as Pusat Vulkanologi dan Mitigasi Bencana Geologi (PVMBG). The test was carried out using various k values, namely 3,5,6,7, and 9. The highest accuracy obtained in this research was 86.87%, and the average accuracy was 82.87%.
Komparasi Metode K-Nearest Neighbors (K-NN) Dengan Support Vector Machine (SVM) Untuk Klasifikasi Status Kualitas Air Icha Gusti Vidiastanta; Nurul Hidayat; Ratih Kartika Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 1 (2020): Januari 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Water quality status classification for the community is divided into 2 classes namely those that meet the standards and do not meet the standards for consumption. The field of object classification research has been carried out, making it possible to create technology in the field of object classification with high accuracy. There are many classification methods, in this study discussing the comparison between K-Nearest-Neighbors (KNN) algorithm and Support vector machine (SVM). Research on the variables in the KNN and SVM algorithm to determine the best variable in classification. Testing is done by the K-Fold method with a value of K = 5 on a dataset of water quality status. Tests carried out to get the optimal parameter value KNN with K = 7 and SVM with value of the maximum iteration value = 300, = 10−12, 𝜎 = 0.07, 𝜆 = 3, 𝛾 = 1.7, and 𝐶 = 1. This research resulted in an accuracy of KNN of 88.94% and SVM of 87.71%. It was observed that the K-Nearest-Neighbors (KNN) algorithm had higher accuracy than the Support vector machine (SVM) algorithm.
Peramalan Indeks Harga Konsumen Indonesia menggunakan Metode Jaringan Saraf Tiruan Backpropagation Elan Putra Madani; Muhammad Tanzil Furqon; Nurul Hidayat
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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Abstract

One of the focus of the government in the 2020 macroeconomic strategy is the realization of controlled inflation, an indicator often used to measure inflation, namely the Consumer Price Index (CPI). The movement of prices of goods and services consumed by the public causes changes in the value of the CPI, when unstable price movements can cause inflation. Forecasting is used to help policy makers to be taken into consideration in order to avoid inflation instability. This research used IHK as data inputs which will be formed the pattern then did data normalization process and processed using Backpropagation Neural Network method for the forecasting of CPI, return value with data denormalization and lastly using Mean Absolute Percentage Error (MAPE) for evaluation of forecasting results. The smallest MAPE value obtained from this research is 0.463% with the value of neuron input = 6, hidden neuron value = 10, initial weight range value in the range -1 to 1, learning rate value = 0.1, and epoch value = 5000
Identifikasi Tingkat Stress Pada Manusia Menggunakan Metode K-NN (K-Nearest Neighbour) Vicky Robi Wirayudha; Nurul Hidayat; Ratih Kartika Dewi
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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Abstract

Stress is a condition caused by interactions between individuals and the environment, giving rise to the perception of demands that originate from situations in a person's biological, psychological and social systems. The field of object classification research has been carried out, making it possible to create technology in the field of object classification with high accuracy. There are many objects classification methods, in this study mainly discuss the K-NN (K-Nearest Neighbor) method. Research on each variable in the K-NN algorithm to determine the best variable in classification. This study will examine the patient who is experiencing stress can be helped to identify the level of stress themselves by answering a series of questionnaires about the symptoms experienced. The accuracy testing is performed using the K-NN algorithm, that k and training data that are different each other including k= 5,8,10,15 and training data of 8,18,38,50 respectively on a patient dataset with symptoms and its weight . This research resulted a patient diagnosis and K-NN maximum accuracy of 82%
Co-Authors Achmad Affan Suprayogi Nugraha Achmad Dwi Noviyanto Achmad Igaz Falatehan Achmad Ridok Achmad Syarifudin Ade Wicaksono Adhie Indi Arsyanto Adhitya Pratama Wijayakusuma Adhiyatma Mugiprakoso Aditya Purwa Pangestu Agus Wahyu Widodo Ahmad Afif Supianto Ahmad Fuyudi Wijaya Akbar Aditya Maulana Akhmad Syururi Akhmad Wahyu Redhani Aldion Cahya Imanda Alfan Nazala Putra Alfian Himawan Alfita Nuriza Ali Syahrawardi Andi Amaliyah Maryama Andika Eka Putra Andrianto Setiawan Arief Andy Soebroto Arifandi Wahyu Widianto Arik Khusnul Khotimah Asep Ardi Herdiyanto Askia Sani Atha Milzam Ayudiya Pramisti Regitha Bambang Gunadi Barlian Henryranu Prasetio Basuki Rahmat Rialdi Bayu Febrian Putera Ammal Bayu Kusuma Pradana Bayu Rahayudi Benedict Abednego Hasibuan Bhima Arya Tristya Haryu Niswara Bryan Pratama Jocom Budi Darma Setiawan Caesaredi Rama Raharya Chandra Tio Pasaribu Christian Herlando Indra Jaya Dayu Aprellia Dwi Putri Denis Ahmad Ryfai Desy Setya Rositasari Dhatu Kertayuga Dhimas Tungga Satya Dicky Manda Putra Sidharta Didin Wahyu Utomo Dito Rizki Pramudeka Dizka Maryam Febri Shanti Dona Adittia Donald Sihombing Donald Sihombing Dwi Prasetyo Edi Siswanto Edy Santoso Eka Hery Wijaya Elan Putra Madani Elna Diaz Pradini Eric Aji Panji Kurniawan Erwan Wahyu Andrianto Erwin Bagus Nugroho Fahmiyanto Ekajaya Fakihatin Wafiyah Faris Abdi El Hakim Fariz Andri Bakhtiar Fibriliandani Nur Pratama Fikar Cevi Anggian Firmansyah Arif Maulana Fitra Abdurrachman Bachtiar Galih Putra Suwandi Ganda Adi Khotarto Greviko Bayu Kristi Gustian Ri'pi Hadi Dwi Abdullah Hamid Haryuni Siahaan Healtho Brilian Argario Hema Prasetya Antar Nusa Herlina Devi Sirait Heru Nurwarsito Hilal Imtiyaz I Gede Adi Brahman Nugraha Icha Gusti Vidiastanta Ichwanda Hamdhani Idham Triatmaja Ikhlasul Amal Faj'r Imam Cholissodin Indriati Indriati Irfan Aprison Irvan Windy Prastyo Isnaini Isnaini Januar Dwi Amanda Jiwandani Andromeda Kholif Beryl Gibran Komang Candra Brata Krisna Andryan Syahputra Effendi Krisna Wahyu Aji Kusuma Kukuh Bhaskara Kusuma Ari Prabowo Lailil Muflikhah Lisa Septian Putri Luh Putu Novita Budiarti Luqman Hakim Harum Lutfi Fanani M. Ali Fauzi Mahardeka Tri Ananta Mahdi Fiqia Hafis Marji Marji Maskiswo Addi Puspito Maulana Aditya Rahman Meriza Nadhira Atika Surya Meutya Choirunnisa Moch Cholil Mahfud Moch. Cholil Mahfud Moch. Cholil Mahfud Mochammad Faizal Satria Rahman Mochammad Taufiqi Effendi Mohamad Yusuf Arrahman Muhamad Altof Muhamad Rendra Husein Roisdiansyah Muhammad Anang Mufid Muhammad Arif Hermawan Muhammad Atabik Usman Muhammad Burhannudin Muhammad Denny Chrisna Pujangga Muhammad Fakhri Mubarak Muhammad Hasbi Wa Kafa Muhammad Kurniawan Khamdani Muhammad Regian Siregar Muhammad Resna Muhammad Rouzikin Annur Muhammad Tanzil Furqon Muhammad Vidi Mycharoka Muhammad Zainuri Aziz Mustofa Robbani Niftah Fatiha Armin Ninda Silvia Tri Cahyani Novianto Donna Prayoga Nurudin Santoso Oktavianis Kartikasari Okvio Akbar Karuniawan Priscillia Pravina Putri Sugihartono Putra Pandu Adikara Putra, Firnanda Al Islama Achyunda Putut Abrianto Rachmad Faqih Santoso Rahmat Arbi Wicaksono Ramadhan Anindya Guna Aniwara Randy Cahya Wihandika Ratih Kartika Dewi Raymond Gunito Farandy Junior Rekyan Regarsari Mardhi Putri Renaldy Senna Hutama Reynaldi Firman Tersianto Reyvaldo Aditya Pradana Reza Andria Siregar Reza Rahardian Rhayhana Putri Justitia Rhiezky Arniansya Rhyzoma Grannata Rafsanjani Ricky Marten Sahalatua Tumangger Rihandiko Hari Romadhona Rio Arifando Risda Nur Ainum Risqi Auliatin Nisyah Risqi Nur Ifansyah Rizal Setya Perdana Rizaldy Amsyar Rizki Wulyono Propana Sodiq Robertus Santoso Aji Putro Salam Maulana Sandy Ikhsan Armita Satrio Hadi Wijoyo Siti Febrianti Ramadhani Supraptoa Supraptoa Sutrisno Sutrisno Syafruddin Agustian Putra Syailendra Orthega Syndu Pramanda Galuh Widestra Tibyani Tibyani Tri Afirianto Trio Pamujo Wicaksono Tunggul Prastyo Sriatmoko Vicky Robi Wirayudha Wahyu Dwiky Rahmadan Wildan Gita Akbari Wildansyah Maulana Rahmat William Muris Parsaoran Nainggolan Yamlikho Karma Yayuk Wiwin Nur Fitriya Yori Tri Cuswantoro Yudo Juni Hardiko Yusril Iszha Eginata Yusuf Ferdiansyah Yusuf Nurcahyo Zaiful Bahar