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Kumalasari et.al (Speech classification using combination virtual center of gravity and k-means clustering…) II. MethodVoice sampling is done by recording sound using the voice recorder app that is on your phone or computer. The voting process is done up to several times.

Transportasi pasien antar rumah sakit membutuhkan jalur tercepat, rute terpendek merupakan salah satu opsi terbaik. Pencarian jalur terpendek merupakan proses pencarian menuju simpul tujuan dengan bobot seoptimal mungkin, bobot yang digunakan berupa jarak tempuh. Jarak didapat dari proses perhitungan menggunakan rumus Haversine.Algoritma ­Floyd-Warshall dan A*(star) merupakan algoritma pencarian yang dapat digunakan untuk mencari jalur terpendek.Dari perhitungan menggunakan algoritma Floyd-Warshall didapat jarak dan simpulantar rumah sakit Samarinda Medika Citra menuju rumah sakit umum daerah Abdul Wahab Sjahranie melalui 12 simpul dengan jarak heuristik 2,987 kilometer, dan dari rumah sakit Dirgahayu menuju rumah sakit umum daerah Abdul Wahab Sjahranie melalui 11 simpul dengan jarak heuristik 3,764 kilometer. Hasil menggunakan algoritma A*(star)diperoleh jarak heuristik 4,733 kilometer dari rumah sakit Samarinda Medika Citra menuju rumah sakit umum daerah Abdul Wahab Sjahranie melalui 15 simpul, dan dari rumah sakit Dirgahayu menuju rumah sakit umum daerah Abdul Wahab Sjahranie melalui 18 simpul dengan jarak heuristik 10,607 kilometer

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The government agencies require accurate tourism demand forecasts to plan the required tourism infrastructure, such as accommodation location planning and transportation development. Tourism demand forecasts can be viewed from various factors, one of which is the number of tourists per period. Without ignoring the number of domestic tourists, the increasing number of foreign tourists is prioritized by the government to increase the country's foreign exchange. Usually, a tourist destination is to visit some tour objects and need some accommodation and hotel sites to rest. With this consideration, the forecasting number of foreign tourists can be done by using data on the number of tour objects, accommodation and hotel sites, foreign and domestic tourists from the previous period. Data on the number of domestic tourists used to measure the tendency of foreign tourists compared with domestic tourists to all existing tour objects. All data history can be viewed as time series data. Conventionally, many researchers have employed traditional methods of time series analysis, modeling, and forecasting such as ARX (Autoregressive with exogenous input) model. FIS (Fuzzy Inference System) is a system that processes the input mapping formulation provided to produce output using Fuzzy Logic. The aim of this study is to forecast the number of foreign tourists by using FIS through a training process conducted by adapting the number of linguistic variables. All the training data are modeled by using the ARX model.

The texture feature description becomes a tremendous challenge in the field of computer vision and pattern recognition. The high-quality feature descriptor attributes some of which are unique, due to a large number of texture classes, robust against illumination variations, and low dimensional representations. A number of image feature extraction methods had been proposed, which can be divided into two categories: holistic and local image feature extraction. The holistic feature extraction method is very sensitive to changes in geometric shapes and some variations of illumination and noise. The local image feature extraction methods can effectively overcome those weaknesses. In this study, the texture features of an RGB image are built using the Local Weighting Pattern (LWP). By using the gray-level dynamic range modification technique, Fuzzy Membership Function (MF) is applied to LWP texture images to build Fuzzy-based LWP image (FLWP). From the resulting image is then used to generate a feature descriptor in the form of labels.

Sistem biometrika merupakan teknologi pengenalan diri dengan menggunakan bagian tubuh manusia ataupun dari perilaku manusia, untuk meningkatkan efisiensi dan efektifitas dalam setia aspek kehidupan dengan mengurangi pemakaian kartu identitas dan kata sandi. Diperlukan sebuah sistem yang dapat membantu manusia untuk mengenali tipe golongan darah. pengenalan tipe golongan darah dapat dilakukan computer salah satunya dengan metode pengenalan pola dan pelatihan masing masing karakterristik golongan darah melalui citra.Percobaan pada penelitian ini membahas tentang verifikasi golongan darah manusia yang diawali dengan pengumpulan data, akusisi citra, preprocessing, ekstraksi ciri. dari sel darah manusia yang nantinya dapat membentuk suatu pola khusus dari kumpulan hasil ekstraksi ciri. Dengan menggunakan kombinasi metode euclidean distance dan correlation coefficient diperoleh pola hasil pelatihan yang menggunakan fuzzy linguistic value berada pada rentang low medium dan medium. Dengan menggunakan 20 data uji dimana setiap golongan darah terdiri dari 5 sampel, diperoleh keputusan hasil verifikasi kecocokan yang diuji dengan menggunakan metode unjuk kerja False Acceptance Rate (FAR) sebesar  dan False Rejected Rate (FRR) sebesar 45% dengan tingkat Akurasi (Acc) sebesar 83%