Jurnal Buana Informatika最新文献

{"title":"Pembangunan Aplikasi Identifikasi Waktu Kawin Ternak Babi dengan Alihragam Wavelet dan Backpropagation","authors":"B. Y. Dwiandiyanta, Marcellinus Pratama W Putra, E. Ernawati, Martinus Maslim","doi":"10.24002/JBI.V10I1.1832","DOIUrl":"https://doi.org/10.24002/JBI.V10I1.1832","url":null,"abstract":"Babi merupakan salah satu hewan yang biasa diternakkan untuk dimanfaatkan dagingnya. Agar produksi daging babi dapat memenuhi tingkat konsumsi yang tinggi, diperlukan penanganan waktu kawin untuk proses pembibitan agar babi dapat kawin pada waktu yang tepat sehingga menghindari permasalahan seperti kegagalan kebuntingan. Penentuan waktu kawin yang tepat pada babi terlihat pada bentuk dan warna vulva babi betina yang terlihat terbuka dan berlendir. Keunikan vulva pada musim kawin ini dapat dianalisis dan dikenali polanya menggunakan alihragam Haar Wavelet dan jaringan syaraf tiruan Backpropagation. Wavelet digunakan untuk melakukan pengambilan ciri citra, sedangkan jaringan syaraf tiruan Backpropagation digunakan untuk membuat basis pengetahuan untuk mengkategorikan karakter apa yang membuat babi dinyatakan berada dalam waktu kawin yang tepat. Aplikasi ini merupakan sebuah aplikasi web yang dibangun framework MVC5 Visual Studio 2015 dengan bahasa pemrograman C#. Pengguna dapat menggunakan aplikasi ini dengan menggunakan aplikasi android. Dibangunnya aplikasi ini bertujuan agar peternak babi dapat mendapatkan waktu yang tepat untuk mengawinkan ternaknya agar produksi babi dapat meningkat. Aplikasi ini juga akan dibuatkan viewnya pada perangkat ponsel pintar agar dapat membuat proses pendeteksian dengan aplikasi ini menjadi lebih efisien","PeriodicalId":381749,"journal":{"name":"Jurnal Buana Informatika","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123620038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pengenalan Personal Menggunakan Citra Tampak Atas pada Lingkungan Cashierless Strore","authors":"B. Prastowo, Nur Achmad Sulistyo Putro, Oktaf Agni Dhewa, Achwan Yusuf","doi":"10.24002/JBI.V10I1.1779","DOIUrl":"https://doi.org/10.24002/JBI.V10I1.1779","url":null,"abstract":"Personal recognition with image processing techniques from the side view has the disadvantage of being applied to the cashierless store environment, namely inaccurate recognition or identification when personal collisions occur. To overcome this, the image capture method is used from the top-view. Personal recognition method through the top-view image using the Haar Cascade Classifier method. 1420 positive images and 2170 negative images are used to find features that are considered suitable for recognizing objects using the Adaptive Boosting (Adaboost) method. Tests were carried out on 100 test data by varying the parameters of min_neighbors (3.4, and 5) and the size of the dataset window (25x25, 35x35, 45x45 pixels). Personal recognition testing gets the highest accuracy of 89.9% with the parameters used are min_neighbors 5 and the size of the 25x25 pixel dataset in the detection parameter size of min_size 140x140 pixels.","PeriodicalId":381749,"journal":{"name":"Jurnal Buana Informatika","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130000980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perencanaan Arsitektur SI/TI menggunakan Framework TOGAF (Studi Kasus : Dinas Perpustakaan dan Kearsipan Daerah Kota Tasikmalaya)","authors":"Silvia Dwi Oktalia, Rahmi Nur Shofa, Rianto Rianto","doi":"10.24002/JBI.V10I1.1842","DOIUrl":"https://doi.org/10.24002/JBI.V10I1.1842","url":null,"abstract":"The planning of system and information technology architecture is one effort which is needed by the organization so that the IS/IT which applied are fitting the needs of business organization. The Tasikmalaya City Department of Library and Archive has not done the IS/IT architecture planning nor fully applied the IS/IT. Therefore, a system and information technology planning is required to identify what system and technology which needed by the Tasikmalaya City Department of Archive and Library. The framework used  in composing the IS/IT planning was TOGAF with the ADM as the architecture development method. The TOGAF's stages used in this research were started from Preliminary Phase to Phase E: Opportunities and Solutions. The result of this IS/IT architecture planning is a blueprint which in sync with the business needs for Tasikmalaya City Department of Archive and Library which consisted of business architecture, information system architecture and technology architecture.","PeriodicalId":381749,"journal":{"name":"Jurnal Buana Informatika","volume":"283 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120865168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mengukur Tingkat Keselarasan Information Technology dan Bisnis (Studi Kasus Perusahaan Start-up Digital Wilayah Jawa)","authors":"Gregorius Airlangga","doi":"10.24002/jbi.v9i2.1485","DOIUrl":"https://doi.org/10.24002/jbi.v9i2.1485","url":null,"abstract":"Abstract. The alignment between information technology (IT) and business becomes a main issue for a digital start-up which adopts technology as a support for the business activities. As one of the growing business in Indonesia, this organization gets special attention from the government that it will be able to become the backbone of the nation's economy. This has led to a necessity of measuring the alignment level between IT and business at digital start-ups in order to describe the conditions for developing strategies to increase competitive benefits. According to that necessity, the research on the assessment of the alignment between IT and business is conducted by using the Luftman SAM (Strategic Alignment Maturity) model to 30 samples of IT start-up companies from various business fields in Java where the center of digital start-up exists in Indonesia. Based on the results of this study, it was found that the average digital start-up has a pretty good alignment level of 3.45. This shows that the strategic alignment between IT and business is starting to integrate in all functional units. Keywords: alignment maturity, Luftman, SAM, start-up.Abstrak. Keselarasan teknologi informasi (IT) dan bisnis telah menjadi masalah utama start-up digital yang memanfaatkan teknologi sebagai penunjang dalam kegiatan bisnis. Sebagai salah satu organisasi yang marak berkembang di Indonesia, organisasi ini mendapatkan perhatian khusus dari pemerintah untuk mampu menjadi tulang punggung perekonomian bangsa. Hal ini menyebabkan perlunya pengukuran tingkat keselarasan IT dan bisnis pada start-up digital agar dapat menggambarkan kondisi keselarasan yang terjadi sehingga mampu menyusun strategi untuk semakin meningkatkan keuntungan kompetitif. Berdasarkan kebutuhan ini peneliti melakukan penilaian keselarasan antara IT dan bisnis dengan menggunakan model Luftman SAM (Strategic Alignment Maturity) terhadap 30 sampel perusahaan start-up IT dari berbagai bidang bisnis yang berada di wilayah Jawa dimana pusat pertumbuhan start-up digital di Indonesia berada. Berdasarkan hasil penelitian ini didapatkan bahwa rata-rata start-up digital memiliki tingkat keselarasan yang cukup baik yakni sebesar 3,45. Hal ini menunjukkan bahwa keselarasan strategis antara IT dan bisnis mulai terbentuk dan terintegrasi di seluruh unit fungsional. Kata Kunci: keselarasan IT dan bisnis, Luftman, SAM, start-up.","PeriodicalId":381749,"journal":{"name":"Jurnal Buana Informatika","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134275525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analisa Tingkat Keharmonisan Suami Istri Pengguna Vasektomi Dengan Algoritma C4.5","authors":"Salamun, Wita Yulianti","doi":"10.24002/JBI.V9I2.1655","DOIUrl":"https://doi.org/10.24002/JBI.V9I2.1655","url":null,"abstract":"Abstract. Vasectomy may cause a strained relationship between a husband and wife. There are some causal factors such as communication, social, sexual, and economical factors. Male participation is an indicator of a successful family planning program (KB). The relevance of the participation of a male doing vasectomy is in his knowledge, behavior of vasectomy and the support from family. The purpose of this research is to reveal the relationship among the knowledge, attitude of KB male participant about vasectomy and the role of family support for vasectomy patient. This study is one way to observe the outcomes of government programs to reduce the number of the population Indonesia. The program may be considered as a way that can strain husband and wife relationship caused by various factors, such as communication, social, sexual and economic factors. In this study, the data is obtained from the official department of demography and national family planning (BKKBN) and based on the immediate observation of some couples who become the vasectomy patients. The data is then examined using C4.5 algorithms which will later make a decision tree which decide whether the couples will be fit or not for doing the vasectomy for family planning program.Keywords: KB, Vasectomy, C4.5 Algorithm.Abstrak. Vasektomi bisa mengakibatkan renggangnya suatu hubungan suami istri. Hal ini disebabkan oleh berbagai faktor seperti faktor komunikasi, sosial, seksual, dan ekonomi. Partisipasi pria menjadi indikator keberhasilan program Keluarga Berencana (KB). Keterkaitan partisipasi pria pengguna vasektomi adalah pengetahuan, tingkah laku partisipan KB pria tentang vasektomi, serta dukungan keluarga. Tujuan dari penelitian ini adalah untuk mengetahui hubungan pengetahuan, sikap akseptor/partisipan KB pria tentang vasektomi, serta peranan dukungan keluarga pengguna vasektomi. Penelitian ini merupakan salah satu cara untuk melihat hasil dari program pemerintah untuk mengurangi jumlah penduduk di Indonesia. Dalam penelitian ini, data didapatkan dari sebuah lembaga resmi KB yaitu Badan Kependudukan dan Keluarga Berencana Nasional (BKKBN) dan observasi lapangan secara langsung kepada beberapa pasangan suami istri yang menggunakan vasektomi. Data selanjutnya diolah menggunakan algoritma C4.5 yang hasilnya nanti akan menghasilkan pohon keputusan yang dapat menjawab apakah pasangan tersebut bisa mengikuti program KB vasektomi. Kata Kunci: KB, Vasektomi, Algoritma C4.5. ","PeriodicalId":381749,"journal":{"name":"Jurnal Buana Informatika","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124685140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analisis Pengaruh Citra Gelap, Normal, Terang Terhadap Wavelet Orthogonal","authors":"Novera Kristianti, N. Purnawati, B. Rolando","doi":"10.24002/JBI.V9I2.1698","DOIUrl":"https://doi.org/10.24002/JBI.V9I2.1698","url":null,"abstract":"Abstract. An image is classified into dark, normal, and bright image. The images are grouped in the dark images according to the histogram and the mu value. An image consists of information and redundancies. The use of wavelet is considered effective in image compression and it does not only cut down the memory usage but also it makes devices work faster. In this study, an analysis in conducted on the influence of dark, normal, and bright images on the orthogonal wavelet. Peak Signal to Noise Ratio (PSNR) is used to compare 17 functions of wavelet orthogonal in the image compression of dark, normal, and bright images. PSNR is a measurement parameter commonly used for measuring the quality of image reconstruction which is then compared with the original image. Compression ratio is used to measure the reduction of the data size after the compression process. Based on the research on the dark, normal, and bright image, the findings reveal that bright image has got the lowest PNSR value at all image testing while the normal image has the highest PSNR value at the wavelet orthogonal application. Keywords : Image compression, Orthogonal wavelet, PSNR, compression ratio.Abstrak. Suatu citra dikelompokkan menjadi citra gelap, citra normal, dan citra terang. Pengelompokan citra menjadi warna gelap terlihat dari histogram dan nilai rerata intensitas (mu). Citra terdiri atas informasi dan redudansi. Penggunaan wavelet dinilai efektif dalam kompresi citra dan menurunkan penggunaan memori serta membuat perangkat menjadi lebih cepat. Pada penelitian ini, dilakukan analisis pengaruh citra gelap, citra normal, dan citra terang terhadap wavelet orthogonal. Peak Signal to Noise Ratio (PSNR) digunakan untuk membandingkan 17 fungsi wavelet orthogonal dalam kompresi citra gelap, citra normal, dan citra terang. PSNR adalah parameter ukur yang sering digunakan untuk pengukuran kualitas gambar rekonstruksi, yang lalu dibandingkan dengan gambar asli. Rasio kompresi digunakan untuk mengukur pengurangan ukuran data setelah proses kompresi. Berdasarkan penelitian pada citra gelap, citra normal, dan citra terang diperoleh bahwa citra terang menghasilkan nilai PSNR paling kecil untuk seluruh citra uji dan citra normal menghasilkan nilai PSNR paling besar dalam penerapan wavelet orthogonal. Kata kunci : Kompresi citra, Wavelet orthogonal, PSNR, rasio kompresi.","PeriodicalId":381749,"journal":{"name":"Jurnal Buana Informatika","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124837519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Kombinasi Algoritma Spatial Autocorrelation G* dan Algoritma C5.0 untuk Deteksi Daerah Rawan Longsor di Pulau Jawa","authors":"Yerymia Alfa Susetyo","doi":"10.24002/JBI.V9I2.1706","DOIUrl":"https://doi.org/10.24002/JBI.V9I2.1706","url":null,"abstract":"Abstract. Java Island is also an island with a high frequency of landslide natural disaster. Various efforts have been made to minimize the disaster risk, including the model compilation of early disaster detection at the areas with landslide potential. This research aims to develop an early warning model for landslide potential areas using Spatial Autocorrelation combined with Machine Learning Algorithm based on attributes of landslide causes. The first step is to classify areas in Java Island into a landslide hotspot and landslide coldspot using spatial autocorrelation G * algorithm. This algorithm revealed 124 polygons of sub-district in Java as landslide hotspots. The next step is building machine learning model using C5.0 method for hotspot and coldspot areas. In this research, we utilize landslide-causing attributes i.e. rainfall, land cover, area slope, soil type, and land movement. The hotspot model showed that landslide distribution focuses on land cover attributes. Meanwhile, for the coldspot area model, there is no focus of landslide distribution on one attribute. Furthermore, the accuracy level of hotspot model are 84.61% and 71.66% for coldspot model. Keywords: Landslide, Machine Learning, Spatial Autocorrelation, C5.0, G*.Abstrak. Pulau Jawa merupakan pulau dengan frekuensi bencana alam tanah longsor yang tinggi. Untuk meminimalkan resiko bencana, dilakukan penyusunan model komputasi deteksi dini daerah potensi longsor. Tujuan dari penelitian ini adalah membangun model deteksi daerah potensi longsor menggunakan Spatial Autocorrelation yang dikombinasikan dengan algoritma Machine Learning berbasis data variabel-variabel pemicu longsor. Tahap pertama yang dilakukan adalah mengklasifikasikan daerah-daerah di Pulau Jawa sebagai daerah hotspot longsor dan coldspot longsor menggunakan algoritma spatial autocorrelation G*. Dihasilkan 124 poligon kecamatan di pulau Jawa sebagai daerah hotspot longsor. Setelah diklasifikasikan, dibangun model machine learning menggunakan metode C5.0. Atribut-atribut pemicu longsor yang digunakan untuk membangun machine learning adalah curah hujan, tutupan lahan, kelerengan, jenis tanah, dan gerakan tanah. Hasil yang diperoleh dari model hotspot terlihat distribusi longsor memusat pada atribut tutupan lahan dan menghasilkan akurasi model 84.61%. Untuk model coldspot area tidak terlihat adanya pemusatan pada satu atribut pemicu longsor, akurasi untuk model ini adalah 71.66%. Kata Kunci: Longsor, Machine Learning, Spatial Autocorrelation, C5.0, G*.","PeriodicalId":381749,"journal":{"name":"Jurnal Buana Informatika","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131773529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Autonomous Robot Path Planning Menggunakan Perbandingan Metode Particle Swarm Optimization dan Genetic Algorithm","authors":"Miftah Rahmalia Ariyati, A. Musthafa","doi":"10.24002/JBI.V9I2.1518","DOIUrl":"https://doi.org/10.24002/JBI.V9I2.1518","url":null,"abstract":"Abstract. A research on robot planning path has been widely conducted and developed. Generally, the desired path is the safe one which has no obstacles and it can be conducted in a quick process. There are several methods that can be applied in planning the path including particle swarm optimization method and genetic algorithm. Both methods are compared in this research in order to discover the best method. Particle swarm optimization method utilizes the particle population movement and genetic algorithm method explores a population consisting individuals’ solutions. The finding reveals that particle swarm optimization method is better than generic algorithm method. This is due to computation time and path required by particle swarm optimization method are shorter than genetic method algorithm. Keyword: Robot path planning, particle swarm optimization, genetic algorithm.Abstrak. Penelitian mengenai perencanaan jalur untuk robot mobil telah banyak diteliti dan dikembangkan. Pada umumnya perencanaan jalur yang diinginkan adalah jalur yang yang aman, tanpa rintangan, dan jarak tempuh yang singkat. Terdapat beberapa metode yang dapat diterapkan dalam perencanaan jalur ini diantaranya adalah metode particle swarm optimization dan genetic algorithm. Pada penelitian ini, kedua metode optimasi tersebut diterapkan. Kedua metode optimasi tersebut dibandingkan untuk didapatkan metode dengan hasil yang terbaik. Metode particle swarm optimization memanfaatkan pergerakan populasi partikel dan metode genetic algorithm melakukan pencarian pada sebuah populasi dari sejumlah individu-individu yang merupakan solusi permasalahan. Hasil penelitian yang dilakukan dengan membandingkan kedua metode optimasi ini adalah metode particle swarm optimization lebih baik daripada metode genetic algorithm. Hal ini berdasarkan pada waktu komputasi dan jalur tempuh yang dibutuhkan oleh metode particle swarm optimization lebih pendek dibandingkan metode genetic algorithm. Kata Kunci: perencanaan jalur robot, particle swarm optimization, genetic algorithm.","PeriodicalId":381749,"journal":{"name":"Jurnal Buana Informatika","volume":"1136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114550303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implemantasi Differential Evolution untuk Optimasi Jadwal Produksi","authors":"Hendry Setiawan, Dewi Fandelia Tan, K. R. Prilianti","doi":"10.24002/jbi.v9i2.1716","DOIUrl":"https://doi.org/10.24002/jbi.v9i2.1716","url":null,"abstract":"Abstract. Scheduling is one of the important things that needs to be considered by any company. A good scheduling process can improve the effectiveness and efficiency of production systems at the company. The problem often occured in this field is a delay in working orders from the deadline and the production of defective products (afal) is still many. The limited ability of the operator to divide the job on the machine causes mistakes of scheduling. To solve that problem, an application was developed to optimize the production schedule automatically. This application was made by implementing the differential evolution algorithm. This production scheduling solution will be represented in vector form. Each vector will be calculated fitness value by the criteria of time and minimum afal. This process will achieve the best vector that provides an optimal schedule. The testing results show that the application can optimize the schedule of production with the average of accuracy rate reaching 99,54%. The scheduling results using differential evolution algorithm can reduce 8,19% of afal, and 97,51% of computing time. Keywords: afal, differential evolution, schedulling.Abstrak. Penjadwalan merupakan salah satu hal penting yang perlu diperhatikan oleh setiap perusahaan. Penjadwalan yang baik akan meningkatkan efisiensi dan efektifitas dari perusahaan tersebut. Permasalahan yang sering terjadi adalah masih sering terjadinya keterlambatan dalam pengerjaan pesanan dari batas waktu yang ditentukan dan kerusakan produksi (afal) yang dihasilkan masih sangat tinggi. Hal ini dikarenakan terbatasnya kemampuan operator dalam membagi job pada mesin, sehingga memungkinkan terjadinya kesalahan penjadwalan. Untuk memecahkan permasalahan tersebut, dibuat sebuah aplikasi yang dapat melakukan optimasi jadwal produksi secara otomatis. Aplikasi ini dibuat dengan mengimplementasikan algoritma differential evolution. Solusi penjadwalan produksi ini akan direpresentasikan dalam bentuk vektor. Setiap vektor akan dihitung nilai fitness dengan kriteria minimasi waktu dan afal. Proses ini akan dilakukan hingga mencapai vektor terbaik yang mampu memberikan jadwal yang optimal. Hasil pengujian yang dilakukan menunjukkan bahwa aplikasi dapat melakukan optimasi jadwal produksi dengan rata-rata tingkat keakuratan mencapai 99,54%. Hasil penjadwalan menggunakan algoritma differential evolution dapat menurunkan afal sebesar 8,19%, dan waktu komputasi sebesar 97,51%. Kata Kunci: afal, algoritma differential evolution, penjadwalan.","PeriodicalId":381749,"journal":{"name":"Jurnal Buana Informatika","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129782187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SISTEM CERDAS PENDUGAAN SALINITAS AIR LAUT BERDASARKAN CITRA LANDSAT MENGGUNAKAN METODE Adaptive Neuro Fuzzy Inference System ( ANFIS )","authors":"Miftahul Walid, A. Darmawan","doi":"10.24002/jbi.v9i1.1283","DOIUrl":"https://doi.org/10.24002/jbi.v9i1.1283","url":null,"abstract":"Penelitian ini merupakan salah satu tahapan untuk mengembangkan sistem dengan memanfaatkan teknologi komputasi yang diaplikasikan di bidang industri salah satunya adalah  industri garam. adapun tujuan dalam penelitian ini adalah untuk memprediksi salinitas air laut yang bisa dijadikan sebagai bahan refrensi untuk produksi garam. Salinitas adalah kadar garam terlarut dalam air, dengan salinitas yang sesuai standart dalam industri garam akan berdampak pada kualitas garam yang dihasilkan.  Metode yang digunakan dalam penelitian ini adalah Adaptive Neuro Fuzzy Inference System ( ANFIS ) yang merupakan salah satu cabang dari ilmu Artificial Intelegent ( AI ) atau kecerdasan buatan. Sistem kerja dalam penelitian ini dengan mengekstraksi citra landsat 8 sehingga menghasilkan beberapa variabel yang dijadikan sebagai dataset dalam sistem ANFIS diantaranya adalah variabel  red, green, blue, Longitude dan Latitude yang dihasilkan dari penggabungan band 2,3 dan 4, dataset tersebut akan dibagi menjadi dua bagian, yaitu Data Training dan Data Testing, Data Training digunakan untuk melatih sistem ANFIS sedangkan Data Testing digunakan untuk mengukur akurasi prediksi yang dihasilkan oleh ANFIS, untuk mengetahui tingkat akurasi akan digunakan metode pengukuran Root Means Square Error ( RMSE ). RMSE digunakan untuk membandingkan data yang dihasilkan oleh sistem ANFIS dengan nilai salinitas air laut dari lapangan., Sistem yang dibuat telah mampu melakukan prediksi dengan tingkat error rata – rata 2,0267.","PeriodicalId":381749,"journal":{"name":"Jurnal Buana Informatika","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134621546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}