Atris Suyantohadi
Universitas Gadjah Mada

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KAJIAN STANDAR NASIONAL INDONESIA BIJI PALA Dinar, Latifa; Suyantohadi, Atris; Fajar F, M. Affan
JURNAL STANDARDISASI Vol 15, No 2 (2013)
Publisher : Badan Standardisasi Nasional

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Abstract

Penerapan SNI merupakan jaminan kesesuaian produk dengan spesifikasi yang telah ditetapkan. Maluku utara adalah daerah penghasil pala terbesar di Indonesia, tapi untuk menerapkan SNI biji pala yang ada saat ini yaitu SNI -0006-1993 perlu disesuaikan dengan kondisi saat ini dan perkembangan standar mutu yang diterapkan pasar dalam negeri maupun luar negeri. SNI tersebut perlu dikaji dengan membandingkan standar yang ada dipasar karena biji pala sebagian besar diekspor ke pasar luar negeri. Analisis dilakukan terhadap persyaratan mutu. Hasil kajian ini dapat disimpulkan bahwa tingginya keragaman varietas biji pala yang ada di Maluku Utara menyebabkan penerapan mutu SNI terutama untuk mutu CN sulit terpenuhi. Standar pasar yang ada saat ini lebih banyak digunakan sebagai acuan dalam menentukan kelas mutu dan harga biji pala ditingkat petani dan pedagang. Berdasarkan hasil pengujian berat biji pala untuk kualitas mutu 1 ABCD 5 gram – 8,33 gram, kualitas mutu 2 RIMPEL (Shrivel) beratnya 4,11 gram- 4,99 gram, biji pala dengan berat ≤ 4,11 masuk kedalam kualitas mutu 3 BWP. Kadar air biji pala yang beredar dipasar sudah memenuhi syarat SNI 01-0006-1993, dari hasil pengujian kadar air pada 3 kualitas mutu diperoleh kadar air 10,54% untuk mutu 1 (ABCD), 8,64% untuk mutu 2 (RIMPEL) dan 11,92 % untuk mutu 3 (BWP). Persyaratan mutu SNI untuk kadar air biji pala maksimum adalah 10 % maka mutu 1 dan mutu 2 sudah memenuhi syarat SNI. Berdasarkan hasil tersebut SNI biji pala perlu direvisi yang mencakup persyaratan jumlah biji per ½ Kg terhadap produk biji pala yang beredar dipasar.
Plant Growth Modeling Using L-System Approach and Its Visualization Suyantohadi, Atris; Alfiyan, Alfiyan; Hariadi, Mochamad; Purnomo, Mauridhi
Makara Journal of Technology Vol 14, No 2 (2010)
Publisher : Directorate of Research and Community Services, Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (143.192 KB) | DOI: 10.7454/mst.v14i2.183

Abstract

The visualizationof plant growth modeling using computer simulation has rarely been conducted with Lindenmayer System (L-System) approach. L-System generally has been used as framework for improving and designing realistic modeling on plant growth. It is one kind of tools for representing plant growth based on grammar sintax and mathematic formulation. This research aimed to design modeling and visualizing plant growth structure generated using L-System. The environment on modeling design used three dimension graphic on standart OpenGL format. The visualization on system design has been developed by some of L-System grammar, and the output graphic on three dimension reflected on plant growth as a virtual plant growth system. Using some of samples on grammar L-System rules for describing of the charaterictics of plant growth, the visualization of structure on plant growth has been resulted and demonstrated.
Penentuan Kriteria Mutu Biji Pala (Myristica fragrans Houtt) Berdasarkan Analisis Tekstur Menggunakan Teknologi Pengolahan Citra Digital Dinar, Latifa; Suyantohadi, Atris; Fajar Fallah, Mohammad Affan
Agritech Vol 33, No 1 (2013)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (465.474 KB) | DOI: 10.22146/agritech.9570

Abstract

Separation of nutmeg based on quality at the farm level is still not done. At the market level process to separate the whole seed and seed damage done by direct observation. The process has the disadvantage, among others, can not be done continuously and mixed results. Development of non-destructive method for separate nutmeg by class quality effectively and objectively indispensable. On image texture analysis can be used to differentiate the surface properties of an object in the image associated with the rough and smooth, also the specific properties of the surface roughness and smoothness criteria that characterize an object of an object. This study aims to analyze the texture characteristics of the object image nutmeg with image processing to determine the quality grade of nutmeg. The materials used are nutmeg derived from Ternate town of North Maluku with reference to defined quality standards in 2000 that divides Menegristek nutmeg into three quality classes ABCD, Rimpel and BWP. Determination of the quality criteria nutmeg done by the method of discriminant analysis. Texture characteristics extracted from the object image consisting of nutmeg contrast, correlation, energy, homogenity, entropy. The results showed significant parameter correlation and the entropy distinguish quality classes nutmeg with a degree of truth of 96,7%.ABSTRAKPemisahan biji pala berdasarkan mutu di tingkat petani saat ini masih belum dilakukan. Di tingkat pedagang proses untuk memisahkan antara biji utuh dan biji rusak dilakukan dengan pengamatan langsung. Proses tersebut memiliki kelemahan antara lain tidak dapat dilakukan secara terus menerus dan hasil yang beragam. Pengembangan metode non-destruktif untuk memisahkanan biji pala berdasarkan kelas mutunya secara efektif dan objektif sangat diperlukan. Analisis  tekstur pada citra dapat digunakan untuk membedakan sifat-sifat permukaan suatu benda dalam citra yang berhubungan dengan kasar dan halus, juga sifat-sifat spesifik dari kekasaran dan kehalusan permukaan suatu objek yang mencirikan kriteria suatu objek. Penelitian ini bertujuan menganalisis ciri tekstur dari citra objek biji pala dengan pengolahan citra untuk menentukan kelas mutu pala. Bahan yang digunakan adalah biji pala yang berasal dari kota Ternate Maluku Utara dengan mengacu pada standar mutu yang ditetapkan Menegristek tahun 2000 yang membagi biji pala kedalam tiga kelas mutu ABCD, Rimpel dan BWP.  Penentuan kriteria mutu pala dilakukan dengan metode analisis diskriminan. Ciri tekstur yang diekstrak dari citra objek biji pala terdiri dari kontras, korelasi, energi, homogenitas, entropi. Hasil penelitian menunjukan parameter korelasi dan entropi signifikan membedakan kelas mutu pala dengan tingkat kebenaran sebesar 96,7%.
Uji Kinerja Teknologi Kontrol Tepat Guna untuk Peningkatan Kualitas Produksi Sutera Alam Sutiarso, Lilik; Suyantohadi, Atris; Purwanto, Hari; Radi, Radi
Agritech Vol 26, No 4 (2006)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1765.684 KB) | DOI: 10.22146/agritech.9484

Abstract

The world demand of raw-silk provides a great opportunity to the development of raw-silk production in Yogyakarta. Recently, only 21% of the overall world demand of raw-silk is fulfilled, whereas Indonesia contributes only 0.1% per year. The main problem is the lack of quality of raw-silk. The optimum growth of silkworm depends on micro environments, i.e. temperature, humidity, aeration, and light intensity. The research aimed at designing an automated “on/off” control technology in the silkworm rearing environmental monitoring in the farming system, while the expected result was high-grade quality of cocoon. In the research, two different conditions of silkworm growing environments were compared, i.e. controlled environment (in the rearing box) and uncontrolled environment. The result indicated that there was increase in  the quality of cocoon. Test of cocoons in laboratory showed that the average thickness of cocoons in controlled rearing environment and in rearing environment was 0.033 cm and 0.029 cm, respectively. The percentage of cocoons in controlled rearing environment was higher than cocoons in normal environment.
Penerapan Alat Pengepres Ampas Tahu untuk Pengrajin Tempe Gembus Sentra Industri Tahu "Ngudi Lestari" Srandakan, Bantul Suyantohadi, Atris; Supartono, Wahyu; Suryandono, Agustinus
Agritech Vol 20, No 1 (2000)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1199.34 KB) | DOI: 10.22146/agritech.13709

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Analisis Preferensi Konsumen dan Uji Mutu Mie Instant di Daerah Istimewa Yogyakarta Suyantohadi, Atris; Suharno, Suharno; Jumeri, Jumeri
Agritech Vol 20, No 2 (2000)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1144.12 KB) | DOI: 10.22146/agritech.13694

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Desain Sistem Informasi Pendukung Keputusan untuk Optimalisasi Profit pada Usaha Kecil Peternakan Broiler Suyantohadi, Atris
Agritech Vol 21, No 2 (2001)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2092.575 KB) | DOI: 10.22146/agritech.13605

Abstract

Small Broiler Breeding Enterprise usually cultivates chicken from one hundred up to five thousand stocks. Some weakness were found in such enterprise including non market segmentation, unpredictable fluctuation on the price of the chicken, DOC and ransum. As the research object was Small Broiler Breeding Enterprise in Yogyakarta, which the sample was allocated on product of DOC Hibro Am 888. By using Decision Support Information System that was designed as a tool tor optimize profit of such enterprise, the best result of the sample analysis was achieved in seven week old. The result showed that for five hundred stocks, the optimum achievement should be Rp 574.508,1 at the production cost Rp 2.239.987,5 in November 2000. The Break Event Point analysis for 397 stocks. Basing on the selling price factor and its variable cost, the application program that was desugned for Decision Support Information System gave easiness in supporting the optimum decision.
Desain Sistem Kontrol Ruang Pertumbuhan Ulat Sutera untuk Meningkatkan Kualitas Produksi Sutera Alam Sutiarso, Lilik; Suyantohadi, Atris; Purwanto, Hari
Agritech Vol 24, No 4 (2004)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3294.513 KB) | DOI: 10.22146/agritech.13385

Abstract

The world demand of raw-silk provides a great opportunity to the development of raw-silk production in Yogyakarta. Recently, only 21% out of the overall world demand of raw-silk is fulfilled, whereas Indonesia contributes only 0.1% per year. The main problem is the lack of quality of raw-silk. The optimum growth of silkworm depends on micro environments, i. e. temperature, humidity, aeration, and light intensity. The research was aimed, to apply an automated -"on/or control technology in the silkworm rearing environmental monitoring. The result expected is high-grade quality of cocoon. In the research, two different conditions of silkworm growing environments were compared: controlled environment (in the rearing box) and normal environment. Then, from third instar (silkworms growth stage) to cocoons stage (final stage or fifth instar), temperature and air humidly were set on 24°C - 26°C and 70% - 80% respectively. While, Aeration and light intensity were ranged 0.1 - 0.3 m/s and 15 - 30 lux for all instar stages (constant) respectively. The result indicated that there was an increasing the percentage of cocoon skins grade in the controlled rearing environment (19.66%), compared to the result of normal rearing environment (18.56%), also there was significantly different result on the thickness of the cocoon produced
Aplikasi Sistem Monitoring Pertumbuhan Tanaman Berbasis Web Menggunakan Machine Vision Sutiarso, Lilik; Suyantohadi, Atris; Kastono, Dody; Nugroho, Andri Prima
Agritech Vol 31, No 4 (2011)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (597.984 KB) | DOI: 10.22146/agritech.9644

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Nowadays, demand for integrating between information technology (IT) and development of agricultural system isin order to increase the productivity, efficiency and profitability in term of precision agriculture. This matter occurred due to some problems in the field, such as; unintensively monitoring activities for plant during the growing period. One of the alternative solutions to overcome the problem was introducing the machine vision technology in the farming system. The research is actually as a basic research that aims using technology of digital image processing and software of computation (mathematics) to support a function of real-time monitoring system for plant growing. The research mechanism was started from digital image processing by using an image segmentation method that can identify between the main object (plant) and others (soil, weed). Image processing algorithm used excess color method and color normalization to identify plants, to calculate crop area. Otsu method was used to convert it to binary images. The next was to calculate and analyze a percentage of the plant growing, from after planting until harvesting time. The analyzed data were stored as MySQL database format in the web server. Final output of the research was the web based monitoring instruments for plant growing that can be accessed through intranet (local area network) as well as internet technology. From the software testing, monitoring with a machine vision system has a success rate reached 70 % for identifying plants.ABSTRAKTuntutan integrasi teknologi sistem informasi dan sistem pertanian saat ini dimaksudkan guna mendukung efisiensi,produktivitas dan profitabiltas pertanian. Hal tersebut didorong oleh timbulnya permasalahan di lapangan terkait dengan belum optimalnya produktivitas tanaman yang diakibatkan antara lain, kurang intensifnya pemantauan (monitoring) tanaman pada masa pertumbuhan. Salah satu alternatif solusi untuk memperbaiki permasalahan tersebut dengan mengaplikasikan teknologi machine vision. Penelitian yang dilakukan merupakan penelitian dasar yang bertujuan memanfaatkan teknologi pengolahan citra digital dan perangkat lunak komputasi untuk mendukung fungsi monitoring pertumbuhan tanaman secara real-time. Mekanisme penelitian dimulai dengan tahap pengolahan citra digital yang menggunakan metode segmentasi untuk mengenali objek tanaman dengan objek lainnya. Algoritma pengolahan citra menggunakan metode kelebihan hijau dan normalisasi warna, sedangkan untuk menghitung luas tanaman digunakan metode  Otsu  dengan  mengubah  ke  citra  biner. Tahap  berikutnya  menghitung  prosentase  pertumbuhan  tanaman selama proses budidaya sampai dengan panen. Data hasil pencitraan disimpan dalam basisdata MySql. Hasil akhir dari pengolahan data ditampilkan sebagai informasi pertumbuhan tanaman yang ditampilkan di website. Dari hasil pengujian, sistem monitoring dengan machine vision ini memiliki tingkat keberhasilan mencapai 70 % dalam mengenali tanaman.
Identifikasi Pertumbuhan Tanaman Kedelai (Glycine max L) dengan Pengaruh Pemberian Komposisi Pupuk Menggunakan Metoda Artificial Neural Network Suyantohadi, Atris; Hariadi, Mochamad; Purnomo, Mauridhi Hery
Agritech Vol 29, No 4 (2009)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (481.287 KB) | DOI: 10.22146/agritech.9699

Abstract

Artificial neural network modeling has been applied to identify soybean plant growth with fertilizer composition as a goal on this research. The architecture of artificial neural network modeling for the identification of soybean plant growth consists of three layer include on input layer with 36 cells of neuron, 7 hidden layer with 600, 500 cells of neurons to in the last hidden layer with 100 cells of neurons, and the output layer with 108 cells of neurons. Training function has been used on architecture model with 0.5 learning rate and 0.9 constant of momentum. Model has been able to provide a good level of identification with correlation coefficient 0.9996 in the analysis of testing result. Based on the results of the implementation, identification of plant growth rate on soybean consist of periodic plant growth on high tress, stem diameter, number of leaves and branches, plant growth analysis and result of plant growth component based on a combination of treatment into fertilizer plant.ABSTRAKModel artificial neural network (jaringan saraf tiruan) diterapkan untuk identifikasi pertumbuhan varietas kedelai dengan pengaruh pemberian komposisi pupuk yang diberikan selama pertumbuhan sebagai tujuan penelitian ini di­ lakukan. Susunan arsitektur model jaringan saraf tiruan untuk identifikasi tingkat pertumbuhan tanaman kedelai yang dihasilkan terdiri atas tiga lapisan, yaitu lapisan masukan dengan jumlah sel neuron 36, 7 lapisan tersembunyi dengan sel neuron masing­masing 600 sel neuron, 500 sel neuron hingga pada lapisan tersembunyi terakhir dengan 100 sel neuron dan lapisan keluaran dengan jumlah sel neuron 108. Fungsi pelatihan diterapkan dengan tingkat laju belajar sebesar 0,5 dan konstanta momentum sebesar 0,9. Model telah mampu memberikan tingkat deteksi yang baik dengan koefisien korelasi 0,9996 pada analisa pengujian.  Berdasarkan hasil implementasi program yang dijalankan, pada output identifikasi tingkat pertumbuhan tanaman kedelai yang terdiri atas pertumbuhan periodik tanaman atas tinggi tanaman, diameter batang, jumlah daun dan jumlah cabang, analisa pertumbuhan dan kompononen hasil tanaman akan dapat diinformasikan berdasarkan perlakuan parameter kombinasi pemberian pupuk kedalam tanaman.