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PERFORMANS KERBAU LUMPUR DAN STRATEGI PENGEMBANGANNYA PADA DAERAH DENGAN KETINGGIAN BERBEDA DI KABUPATEN CIANJUR (PERFORMANCE ANALYSIS OF SWAMP BUFFALO AT DIFFERENT ALTITUDES IN CIANJUR DISTRICT AND ITS DEVELOPMENT STRATEGIES ., Komariah; Sumantri, Cece; Nuraini, Henny; Nurdiati, Sri; Mulatsih, Sri
Jurnal Veteriner Vol 16 No 4 (2015)
Publisher : Faculty of Veterinary Medicine, Udayana University and Published in collaboration with the Indonesia Veterinarian Association

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Abstract

The research objectives were to analyze reproduction performance and productivity of swamp buffalofrom different altitudes in Cianjur and draw up a hierarchy of productivity strategy development usinganalysis of SWOT (Strength, Weakness, Opportunity, Threats) and Analytical Hierarchy Process (AHP)with four criteria: technology, costs, impact, and the response of farmers. Survey was conducted in Cianjurduring January-March 2014 by interview prepared questionnaires and direct observation of 63 buffalo farmers. Secondary data were also obtained from relevant agencies. Primary data were collected usingdirect observation of 139 reproductive female buffaloes then were further analyzed. A total of 58 buffaloesat their productive period were sampled and taken their morphometric data. Whilst 37 buffaloes weremeasured their frame size using Body Condition Score (BCS). The results showed that the reproductionperformance of buffaloes in the lowlands are not significantly different from those in the highland. The ageat first oestrus, first mating, first calving, gestation period were 25.6 months, 26.6 months, 38.7 months,11.8 months, respectively.. The oestrus period was 5.3 days, and post-partum mating interval was 54.6days. Differences in altitude and sex significantly affected (P <0.05) the morphometry assessment. Thebody weight of male buffaloes were found lower than the females both in highlands and lowlands (P<0.05).The body conditioning score of buffalo performance at highland was better compared to those in thelowland. Based on the SWOT analysis and AHP: (1) The main strategy is to improve the technology basedon the criteria of internal weakness by increasing scale holdings to seize opportunities buffalo meat selfsufficiency;(2) based on the criteria of cost and impact, the strategy was to cover threats over the professionout of the region by empowering farmers (facilitate increased productivity buffalo); (3) based on the responsecriteria, the primary strategy is to improve the quality of education of farmers by facilitating productivityimprovement opportunities to achieve self-sufficiency buffalo meat. The main development strategy basedon the four criteria: technology, cost, impact, and farmer response were increasing of buffalo ownershipscale, production facilities, and farmers education quality.
ANALISIS PEMBENTUKAN POLA GRAF PADA KALIMAT BAHASA INDONESIA MENGGUNAKAN METODE KNOWLEDGE GRAPH Yusuf, Yasin; Nurdiati, Sri; Silalahi, Paruhum
Lingua Vol 10, No 1 (2014): January 2014
Publisher : Lingua

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Abstract

Knowledge graph adalah sebuah pendekatan baru untuk memahami bahasa alami. Metodeini memiliki 9 relasi biner dan 4 relasi frame. Analisis suatu kalimat dengan menggunakanknowledge graph membutuhkan aturan pemotongan kalimat (chunking). Aturan chunkingsudah ada pada struktur kalimat bahasa Inggris dan Cina, tetapi belum ada untuk strukturkalimat bahasa Indonesia.Tujuan dari penelitian ini adalah membentuk aturan chunkingpada struktur kalimat bahasa Indonesia dan membuat pola graf kalimat bahasaIndonesia.Tahapan penelitian ini adalah dimulai dengan studi literatur awal, pembuatanchunk indicator, pemotongan kalimat (chunking), pembuatan chunk graph, dan diakhiridengan kontruksi sentence graph. Hasil penelitian ini adalah aturan chunking kalimatbahasa Indonesia dengan indicator sebanyak 8, yaitu koma dan titik, kata ganti petunjuk,kata kerja bantu, kata depan, jump, kata-kata logika, jeda nafas, kata sambung. Selain itu,diperoleh pula pola graf kalimat bahasa Indonesia yang sekaligus menunjukkan arti(aspek semantik) dari kalimat yang dianalisis. This research aimed to construct chunking rule on Indonesian language sentencestructure and make pattern of Indonesian language sentence graph. It was done sinceknowledge graph is a new approach to understand natural language. This method has 9(nine) binary relation and 4 (four) frame relation. A sentence analysis using this approachneeds rule of sentence chunking, This research method was started from beginning ofliterary studies, chunk indicator constructing, sentence chunking, chunk graphconstructing, and sentence graph constructing. Result of this research was there was ruleof Indonesian language sentence chunking with 8 (eight) indicators such as periods, fullstops, demonstratives, auxiliary verbs, prepositions, jump, logical words, pauses,conjunctions. Besides that, it had also been achieved pattern of Indonesian languagegraph which gives meaning (semantic aspect) from analyzed sentences at once.
Identifikasi Jenis Kayu Menggunakan Support Vector Machine Berbasis Data Citra Gunawan, AA Gede Rai; Nurdiati, Sri; Arkeman, Yandra
Jurnal Ilmu Komputer dan Agri-Informatika Vol 3, No 1 (2014)
Publisher : Departemen Ilmu Komputer IPB

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Abstract

Identifikasi jenis kayu di Indonesia pada umumnya dilakukan secara manual, dengan cara memperhatikan pori kayu pada daerah penampang kayu menggunakan kaca pembesar atau mikroskop dengan pembesaran minimal 10 kali. Teknik komputerisasi belum banyak dilakukan terutama karena kurangnya penelitian di bidang ini dan sulitnya mendapatkan database kayu. Penelitian ini bertujuan mengembangkan sebuah sistem untuk mengklasifikasikan 4 jenis kayu yang diperdagangkan di Indonesia dengan metode support vector machine (SVM) berbasis citra. Teknik ekstraksi ciri yang digunakan adalah two-dimensional principal component analysis (2D-PCA). Sistem ini dapat mengidentifikasi kayu dalam waktu singkat sehingga mempercepat proses identifikasi jenis kayu. Hasil klasifikasi dari 120 kali percobaan dengan menggunakan 96 data citra dengan 4 jenis kayu menunjukkan akurasi terbaik sebesar 95.83% pada kernel Polinomial. Kata kunci: Citra mikroskopis, Identifikasi jenis kayu, SVM
PENGEMBANGAN VISUAL INTERACTIVE SIMULATION DALAM SISTEM PENUNJANG KEPUTUSAN DENGAN PENDEKATAN AGEN (Studi Kasus Investasi pada Industri Biodisel Kelapa Sawit) Harsani, Prihasuti; Nurdiati, Sri; Kusuma, Wisnu Ananta
Seminar Nasional Informatika (SEMNASIF) Vol 1, No 3 (2008): Intelligent System dan Application
Publisher : Jurusan Teknik Informatika

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Abstract

Sistem Penunjang Keputusan dengan simulasi dapat menjadi efektif dengan pemanfaatan Visual Interactive Simulation (VIS). Melalui VIS pengambil keputusan mengontrol sepenuhnya jalannya simulasi dengan penentuan skenario dan modifikasi parameter simulasinya.  Pembangunan sistem dengan VIS dilakukan dengan metodologi gaia untuk memodelkan sistem agen. Melalui gaia, dihasilkan lima model utama sebagai dasar pembentukan arsitektur sistem, yaitu model interaksi, model role, model service, model acquitance dan model agen. Pendefinisian arsitktur sistem yang lebih konkret dilakukan melalui Agent Unified Modelling Languagae (AUML)
SPEAKER IDENTIFICATION USING HYBRID MODEL OF PROBABILISTIC NEURAL NETWORK AND FUZZY C-MEANS Zilvan, Vicky; Buono, Agus; Nurdiati, Sri
Widyariset Vol 16, No 2 (2013): Widyariset
Publisher : LIPI-Press

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A hybrid model of Probabilistic Neural Network and Fuzzy C-Means has been developed. The model has been applied using Mel Frequency Cepstrum Coefficients (MFCC) as feature extraction for identification. In addition to the natural voice, the effect of noise has also been taken into account. It has been shown that the model has good accuracy at 96% for voice without noise, 85.5% for voice with noise at the level of signal to noise ratio 30, and 60% for voice with noise at the level of signal to noise ratio 20. It has also been concluded that the clustering procedure using Fuzzy C-Means could improve the accuracy up to 96% for large number of training data.
REKONSTRUKSI MODEL 3D MENGGUNAKAN FOTO UDARA UNTUK MENDUGA TINGGI OBJEK Hanief, Hafzal; Nurdiati, Sri; Suwardhi, Deni
MAJALAH ILMIAH GLOBE Vol 15, No 2 (2013)
Publisher : Badan Informasi Geospasial

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (198.921 KB) | DOI: 10.24895/MIG.2013.15-2.80

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ABSTRAKRekonstruksi 3D, terutama untuk ekstraksi tinggi menggunakan foto udara digital yang diambil dari kamera nonmetrikdan Pesawat Udara Nir Awak (PUNA) adalah studi yang menantang. Tujuan dari penelitian ini adalah: (1) untukmenentukan presisi tinggi objek yang diungkapkan dari model 3D dan menetapkan prosedur untuk memberikan hasilyang optimal. Dua atau lebih tumpang tindih foto udara dapat dibangun ke dalam model 3D dengan menerapkanprinsip-prinsip collinearity dan geometri epipolar menggunakan algoritma rekonstruksi 3D. Karena ketidakstabilankamera digital non-metrik, kamera harus dikalibrasi sebelum rekonstruksi 3D diproses, dengan cara bahwa kualitasekstraksi spasial dapat kemudian diukur. Penelitian ini dilakukan dengan menggunakan 24 megapixel Resolusi SonyNEX7 kamera digital dan Hexacopter UAV. Kamera Kalibrasi Toolbox digunakan untuk menghitung parameter intrinsikkamera dan program yang spesifik dikembangkan dengan menggunakan MATLAB dalam rangka membangun model3D dan untuk memperoleh ketinggian objek. Hasil validasi dilakukan dengan membandingkan ketinggian model 3Ddengan satu pengukuran dengan menggunakan Electronic Total Station. Keakuratan tinggi objek hingga 1 mmberhasil dicapai, dengan ketinggian kesalahan prediksi terbesar mencapai 15,2 cm pada 70 m ketinggian terbang diatas permukaan tanah.Kata Kunci : Rekonstruksi 3D, Collinearity, Geometri Epipolar, PUNA.ABSTRACTReconstruction of 3D, especially on height extraction using digital aerial photos taken from a non-metric cameraand Unmanned Aerial Vehicle (UAV) is a challenging study. The purposes of this study are: (1) to determine theprecision of an object’s height reveal from a 3D model, and (2) to establish procedures to deliver the optimal result.Two or more overlapping aerial photos can be constructed into a 3D model by applying principles of collinearity andepipolar geometry using 3D reconstruction algorithm. Since there is an instability on a non-metric digital camera, thecamera must be calibrated before 3D reconstruction is process, in that way the quality of spatial extraction, then canbe measured. The study is conducted using 24 megapixels resolution Sony NEX7 digital camera and HexacopterUAV. Camera Calibration Toolbox was utilized to calculate intrinsic parameters of the camera and a specific programis developed using MATLAB in order to build the 3D model and to obtain the object’s height. The result validation isdone by comparing the height from 3D model with that one measured using Electronic Total Station. The accuracy ofthe object’s height up to 1 mm was successfully achieved, with largest height prediction error reaches of 15.2 cm at 70m flying height above ground level.Keyword : 3D Reconstruction, Collinearity, Epipolar Geometry, UAV.
UTILIZING SOFT COMPUTING FOR DETERMINING PROTEIN DEFICIENCY Hartati, Sri; Nurdiati, Sri
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 5, No 1 (2011): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (384.847 KB) | DOI: 10.22146/ijccs.1996

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Abstract? In recent years, the occurrence of protein shortage of children under 5 years old in many poor area has dramatically increased. Since this situation can cause serious problem to children like a delay in their growth, delay in their development and also disfigurement, disability, dependency, the early diagnose of protein shortage is vital. Many applications have been developed in performing disease detection such as an expert system for diagnosing diabetics and artificial neural network (ANN) applications for diagnosing breast cancer, acidosis diseases, and lung cancer. This paper is mainly focusing on the development of protein shortage disease diagnosing application using Backpropagation Neural Network (BPNN) technique. It covers two classes of protein shortage that are Heavy Protein Deficiency. On top of this, a BPNN model is constructed based on result analysis of the training and testing from the developed application. The model has been successfully tested using new data set. It shows that the BPNN is able to early diagnose heavy protein deficiency accurately. Keywords? Artificial Neural Network, Backpropagation Neural Network, Protein Deficiency.
ANALISIS PEMBENTUKAN POLA GRAF PADA KALIMAT BAHASA INDONESIA MENGGUNAKAN METODE KNOWLEDGE GRAPH Yusuf, Yasin; Nurdiati, Sri; Silalahi, Paruhum
Lingua Vol 10, No 1 (2014): January 2014
Publisher : Lingua

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Abstract

Knowledge graph adalah sebuah pendekatan baru untuk memahami bahasa alami. Metodeini memiliki 9 relasi biner dan 4 relasi frame. Analisis suatu kalimat dengan menggunakanknowledge graph membutuhkan aturan pemotongan kalimat (chunking). Aturan chunkingsudah ada pada struktur kalimat bahasa Inggris dan Cina, tetapi belum ada untuk strukturkalimat bahasa Indonesia.Tujuan dari penelitian ini adalah membentuk aturan chunkingpada struktur kalimat bahasa Indonesia dan membuat pola graf kalimat bahasaIndonesia.Tahapan penelitian ini adalah dimulai dengan studi literatur awal, pembuatanchunk indicator, pemotongan kalimat (chunking), pembuatan chunk graph, dan diakhiridengan kontruksi sentence graph. Hasil penelitian ini adalah aturan chunking kalimatbahasa Indonesia dengan indicator sebanyak 8, yaitu koma dan titik, kata ganti petunjuk,kata kerja bantu, kata depan, jump, kata-kata logika, jeda nafas, kata sambung. Selain itu,diperoleh pula pola graf kalimat bahasa Indonesia yang sekaligus menunjukkan arti(aspek semantik) dari kalimat yang dianalisis.This research aimed to construct chunking rule on Indonesian language sentencestructure and make pattern of Indonesian language sentence graph. It was done sinceknowledge graph is a new approach to understand natural language. This method has 9(nine) binary relation and 4 (four) frame relation. A sentence analysis using this approachneeds rule of sentence chunking, This research method was started from beginning ofliterary studies, chunk indicator constructing, sentence chunking, chunk graphconstructing, and sentence graph constructing. Result of this research was there was ruleof Indonesian language sentence chunking with 8 (eight) indicators such as periods, fullstops, demonstratives, auxiliary verbs, prepositions, jump, logical words, pauses,conjunctions. Besides that, it had also been achieved pattern of Indonesian languagegraph which gives meaning (semantic aspect) from analyzed sentences at once.
Strategi Peningkatan Kinerja Karyawan Taman Buah Mekarsari Kusumawati, Rika; Maarif, M. Syamsul; Nurdiati, Sri
Jurnal Aplikasi Bisnis dan Manajemen (JABM) Vol 5, No 1 (2019): JABM Vol. 5 No. 1, Januari 2019
Publisher : School of Business, Bogor Agricultural University (SB-IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17358/jabm.5.1.59

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Human resources are the main element of the organization. The organization goals will be achieved when ITS employees have high performance. The purposeS of this study were to analyze the effect of competency on employee motivation, the effect of competency on employee performance, and the effect of motivation on employee performance, and to formulate strategies for improving the employee performance at Mekarsari Fruit Garden. The respondents in this study were 167 employees selected with sampling technique using stratified random sampling. Analysis of the data used in this research included descriptive analysis of respondents, Spearman correlation test methods, analysis Structural Equation Modeling (SEM) with LISREL 8.51 and Analytical Hierarchy Process (AHP) with expert choice 2000. The results showed that 1) Competency had an effect on employee motivation at Mekarsari Fruit Garden; 2) Competency had an effect on employee performance at Mekarsari Fruit Garden; 3) Motivation had an effect on employee performance at Mekarsari Fruit Garden. The first strategy to improve employee performance was improving the prosperity of employees, and the highest factor in increasing employee performance was competency. The most influential actor was the President Director of Mekarsari Fruit Garden whereas the highest score of the objective was increasing the profit of Mekarsari Fruit Garden.Keywords: performance, competency, motivation, strategies, Mekarsari Fruit GardenAbstrak: Sumber Daya Manusia (SDM) merupakan elemen utama organisasi. Tujuan organisasi akan tercapai bila pegawai di dalamnya memiliki kinerja yang tinggi. Tujuan penelitian ini adalah untuk mengalisis pengaruh kompetensi terhadap motivasi karyawan, kompetensi terhadap kinerja karyawan dan motivasi terhadap kinerja karyawan serta merumuskan strategi dalam rangka peningkatan kinerja karyawan Taman Buah Mekarsari. Responden dalam penelitian ini sebanyak 167 karyawan dengan teknik penarikan contoh menggunakan Stratified Random Sampling. Analisis data yang digunakan dalam penelitian ini meliputi analisis deskriptif responden, uji korelasi dengan metode Spearman, analisis Structural Equation Modeling (SEM) dengan LISREL 8.5, dan analytical hierarchy process (AHP) menggunakan expert choice 2000. Hasil penelitian menunjukkan bahwa: 1) Kompetensi berpengaruh terhadap motivasi karyawan Taman Buah Mekarsari; 2) Kompetensi berpengaruh terhadap kinerja karyawan Taman Buah Mekarsari; 3) Motivasi berpengaruh terhadap kinerja karyawan Taman Buah Mekarsari. Strategi pertama untuk meningkatkan kinerja karyawan adalah meningkatkan kesejahteraan karyawaan, sementara faktor tertinggi dalam hal peningkatan kinerja adalah kompetensi. Aktor yang paling berpengaruh dalam peningkatan kinerja karyawan adalah Direktur Utama, sementara skor tertinggi dari tujuan adalah meningkatkan laba Taman Buah Mekarsari.Kata kunci: kinerja, kompetensi, motivasi, strategi, taman buah mekarsari
KONSTRUKSI ATURAN PENGGABUNGAN DUA GRAF KALIMAT Amanah, Ayu; Nurdiati, Sri; Bukhari, Fahren
SALINGKA Vol 11, No 01 (2014): SALINGKA, EDISI JUNI 2014
Publisher : Balai Bahasa Sumatra Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (60.818 KB) | DOI: 10.26499/salingka.v11i01.2

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Knowledge Graph merupakan hal baru yang berguna untuk menggambarkan bahasa manusia yang lebih berpusat pada aspek semantik daripada aspek sintetik. Representasi makna teks berbahasa Indonesia ke dalam bentuk graf dapat dilakukan dengan menggunakan Knowledge Graph. Representasi tersebut bertujuan mengurangi ambiguitas. Representasi makna teks diperoleh melalui beberapa penelitian. Penelitian representasi makna kata, makna frasa, dan makna klausa telah dilakukan sehingga penelitian ini bertujuan mengkaji representasi makna kalimat ke dalam graf kalimat dan menggabungkan dua graf kalimat. Hasil penelitian ini berupa aturan pembentukan graf kalimat dan aturan penggabungan dua graf kalimat. Kedua aturan tersebut dikonstruksi agar setiap orang memiliki representasi kalimat dan penggabungan dua graf kalimat yang sama