Yulianti, Titin
LPM Unimed

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RERATA INTENSITAS WARNA TERPISAH UNTUK IDENTIFIKASI DAGING KAMBING, DAGING BABI, DAGING CELENG, DAN DAGING ANJING Yudamson, Afri; Yulianti, Titin; Setyawan, FX Arinto; Sulistiyanti, Sri Ratna
JURNAL PENGABDIAN KEPADA MASYARAKAT Vol 23, No 1 (2017)
Publisher : LPM Unimed

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Abstract

AbstrakPaper ini memaparkan hasil penelitian untuk mengidentifikasi beberapa jenis daging menggunakan metode rerata intensitas warna terpisah. Sampel yang digunakan dalam penelitian ini adalah daging Anjing, daging Babi, daging Celeng, dan daging Kambing karena dengan kasat mata, beberapa jenis daging tersebut tampak serupa. Sampel-sampel tersebut ditangkap menggunakan kamera android. Kemudian setiap citra yang dihasilkan, disegmentasi untuk memisahkan citra daging dari latar belakangnya. Kemudian dihitung nilai persentase dari Red, Green, dan Blue. Hasil penelitian menunjukkan bahwa rentang nilai persentase Red dari 50,78% sampai 53,87% dapat menjadi ciri daging Anjing, rentang nilai persentase Green dari 29,11% sampai 31,43% dapat menjadi ciri daging Babi dan daging Celeng, dan rentang nilai persentase Blue dari 25,33% sampai 28,22% dapat menjadi ciri daging Kambing.Kata kunci: daging serupa, segmentasi citra, rerata intensitas warna terpisah, karakterisasi citra AbstractThis paper reports our research about identifying some kinds of meats using separate color intensity average. Samples used in this research are Dog meat, Pork, Boar meat, and Lambs because these types of meat seen similar in plain view. Those sample images were acquired by the android camera. Then each image was segmented to separate from the background. After that, the values of Red, Green, and Blue percentages were calculated. The results show that Red percentage range of 50.78% to 53.87% can be the characteristic of Dog meats, Green percentage range of 29.11% to 31.43% can be the characteristic of Pork and Boar meats, and Blue percentage range of 25.33% to 28.22% can be the characteristic of Lambs.Keywords: similar meat, segmented image, separate color intensity average, image characterization
Internet Traffic Measurement: Trends and Impact to Campus Network Nama, Gigih Forda; Komarudin, M.; Mardiana, Mardiana; Setiapriadi, R Arum; Septama, Hery Dian; Muhammad, Meizano Ardhi; Yulianti, Titin
INSIST Vol 1, No 1 (2016)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (771.664 KB) | DOI: 10.23960/ins.v1i1.18

Abstract

Abstract— University of Lampung (Unila) is an Institution of Higher Education located in Bandar Lampung. Since 2016, Unila has deployed Internet Access Management (IAM) to guarantee the healthiness of the campus network, as well as to enhance the effectiveness of the bandwidth usage. This study focused on internet traffic measurement, conducted in Unila’s campus network during February 1 until February 29, 2016. Overall, this study shows user behavior on their application. The trend data of monthly most popular URL Categories accessed by users was; 1st Computers & Technology with 30032328 hits or 39.1%, the 2nd was Search Engines & Portals with 14214611 hits or 18.5%. There were around 30-40 % of internet traffic was use for Streaming Media activity, it proves that the existence of Streaming Media Activity in Campus Network which contribute to network congestion. During a month doing internet measurement, we identify the most active device/user that are the 1st was Aruba Wireless Controller with total traffic flow 40.45%, the 2nd was CCR-1 with 26.2%, the 3rd was CCR-2 with 16.9%, and the 4th was Digital Library Server with total flow was 0.6%. Monthly uplink traffic total flow was 5889.92 GB while downlink traffic total flow was 61041.35 GB. We made a recommendation to Unila management for implementing traffic provisioning especially on streaming media activity specific on access to Google Global Cache (GGC), to overcome network congestion during peak time period on working hours. Keywords—internet access management, internet traffic measurement; traffic trend