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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmu Pertanian Indonesia Agromet MANAJEMEN IKM: Jurnal Manajemen Pengembangan Industri Kecil Menengah Jurnal Pustakawan Indonesia FORUM STATISTIKA DAN KOMPUTASI Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmu Komputer dan Informasi Jurnal Pembangunan Wilayah dan Kota Agrikultura Jurnal Keteknikan Pertanian Proceedings of KNASTIK TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmu Komputer dan Agri-Informatika Forum Agribisnis SITEKIN: Jurnal Sains, Teknologi dan Industri Jurnal Teknologi Informasi dan Ilmu Komputer Journal of ICT Research and Applications Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) International Journal of Advances in Intelligent Informatics Jurnal Aplikasi Bisnis dan Manajemen (JABM) E-Journal Widyariset JOIN (Jurnal Online Informatika) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Informatika Pertanian Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Informatika Universitas Pamulang Jurnal ULTIMATICS CYBERNETICS BHUMI: Jurnal Agraria dan Pertanahan Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika JURNAL METEOROLOGI DAN GEOFISIKA Building of Informatics, Technology and Science Journal of Robotics and Control (JRC) Indonesian Journal of Electrical Engineering and Computer Science Computer Science and Information Technologies Jurnal Tanah dan Iklim Widyariset Aiti: Jurnal Teknologi Informasi Jurnal Pustakawan Indonesia Makara Journal of Science Eduvest - Journal of Universal Studies J-Icon : Jurnal Komputer dan Informatika Jurnal Sistem Informasi

Agus Buono

Department Of Computer Science, Faculty Of Mathematics And Natural Science, Bogor Agricultural University, Jalan Meranti, Kampus IPB Darmaga, Bogor 16680,

Author-ID : 221408

Aerospace Engineering Agriculture, Biological Sciences & Forestry Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Neuroscience Physics Social Sciences Other

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Modeling Text Independent Speaker Identification with Vector Quantization Syeiva Nurul Desylvia; Agus Buono; Bib Paruhum Silalahi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 1: March 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i1.4656

Speaker identification is one of the most important technology nowadays. Many fields such as bioinformatics and security are using speaker identification. Also, almost all electronic devices are using this technology too. Based on number of text, speaker identification divided into text dependent and text independent. On many fields, text independent is mostly used because number of text is unlimited. So, text independent is generally more challenging than text dependent. In this research, speaker identification text independent with Indonesian speaker data was modelled with Vector Quantization (VQ). In this research VQ with K-Means initialization was used. K-Means clustering also was used to initialize mean and Hierarchical Agglomerative Clustering was used to identify K value for VQ. The best VQ accuracy was 59.67% when k was 5. According to the result, Indonesian language could be modelled by VQ. This research can be developed using optimization method for VQ parameters such as Genetic Algorithm or Particle Swarm Optimization.

Optimization of Parallel K-means for Java Paddy Mapping Using Time-series Satelite Imagery Alvin Fatikhunnada; Kudang Boro Seminar; Liyantono Liyantono; Mohamad Solahudin; Agus Buono
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 3: June 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i3.6876

Spatiotemporal analysis of MODIS Vegetation Index Imagery widely used for vegetation seasonal mapping both on forest and agricultural site. In order to provide a long-terms of vegetation characteristic maps, a wide time-series images analysis is needed which require high-performance computer and also consumes a lot of energy resources. Meanwhile, for agriculture monitoring purpose in Indonesia, that analysis has to be employed gradually and endlessly to provide the latest condition of paddy field vegetation information. This research is aimed to develop a method to produce the optimized solution in classifying vegetation of paddy fields that diverse both spatial and temporal characteristics. The time-series EVI data from MODIS have been filtered using wavelet transform to reduce noise that caused by cloud. Sequential K-means and Parallel K-means unsupervised classification method were used in both CPU and GPU to find the efficient and the robust result. The developed method has been tested and implemented using the sample case of paddy fields in Java Island. The best system which can accommodate of the extend-ability, affordability, redundancy, energy-saving, maintainability indicators are ARM-based processor (Raspberry Pi), with the highest speed up of 8 and the efficiency of 60%.

Fuzzy-based Spectral Alignment for Correcting DNA Sequence from Next Generation Sequencer Kana Saputra S; Wisnu Ananta Kusuma; Agus Buono
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 2: June 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i2.2395

Next generation sequencing technology is able to generate short read in large numbers and in a relatively short in single running programs. Graph based DNA sequence assembly used to handle these big data in assembly step. The graph based DNA sequence assembly is very sensitive to DNA sequencing error. This problem could be solved by performing an error correction step before the assembly process. This research proposed fuzzy inference system (FIS) model based spectral alignment method which can detect and correct DNA sequencing error. The spectral alignment technique was implemented as a pre-processing step before the DNA sequence assembly process. The evaluation was conducted using Velvet assembler. The number of nodes yielded by the Velvet assembler become a measure of the success of error correction. The results shows that FIS model based spectral alignment created small number of nodes and therefore it successfully corrected the DNA reads.

Estimating Parameter of Nonlinear Bias Correction Method Using NSGA-II in Daily Precipitation Data Angga Wahyu Pratama; Agus Buono; Rahmat Hidayat; Hastuadi Harsa
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 1: February 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i1.6848

Nonlinear (NL) method is the most effective bias correction method for correcting statistical bias when observation precipitation data can not be approximated using gamma distribution. Since NL method only adjusts mean and variance, it does not perform well in handling bias on quantile values. This paperpresents a scheme of NL method with additional condition aiming to mitigate bias on quantile values. Non-dominated Sorting Genetic Algorithm II (NSGA-II) was applied to estimate parameter of NL method. Furthermore, to investigate suitability of application of NSGA-II, we performed Single Objective Genetic Algorithm (SOGA) as a comparison. The experiment results revealed NSGA-II was suitable when solution of SOGA produced low fitness. Application of NSGA-II could minimize impact of daily bias correction on monthly precipitation. The proposed scheme successfully reduced biases on mean, variance, first and second quantile However, biases on third and fourth moment could not be handled robustly while biases on third quantile only reduced during dry months.

ANALISIS HUBUNGAN CURAH HUJAN DENGAN KEJADIAN BANJIR DAN KEKERINGAN PADA WILAYAH DENGAN SISTIM USAHATANI BERBASIS PADI DI PROPINSI JAWA BARAT (ANALYSIS OF RELATIONSHIP BETWEEN RAINFALL AND FLOOD AS WELL AS DROUGHT EVENTS ON AREA WITH RICE ... Woro Estiningtyas; Rizaldi Boer; Agus Buono
Agromet Vol. 23 No. 1 (2009): June 2009
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

There are significantly decreasing of rainfall in wet season and dry season, and changed in onset of early season, that all of them can make crouded in plan of planting date, field actifity especially for food crops africulture. In the other side, climate is one of condition that has been ready and can not change, where probability of climate change will be reality that should be happened every time. Increasing frequency of climate extrem will give high impact in agriculture, especialy in rice-based farming system. This paper describes the climate risk based on statistical approaches. The climate risk is focused on flood and drought event. The analysis used was a chance occurrence based on time series data of rainfall and flood/droughts (affected and puso) based on median value from time series data. The goal of this research are : (1) to know rainfall critical value that can be influence flood and drought event in some of central food crops i West Java, (2) to know probability of flood and drought event in some of central food crops in West Java. The result of this research show that critical value of the rainfall that can be influence flood and drought event is very variety. Average of for flood event for paddy field near coastal based on median approach is 140 mm/month with probability 0,6. For another location, 166 mm/month with probability 0,68. Average of critical value of the rainfall for drought event is 64 mm/month for paddy field near coastal with probability 0,73. For another location, critical rainfall value is 119 mm/month with probability 0,76. For spesific research or detail scale (district or sub distric) we can use rainfall critical value and probablity based on data in that specific location because the data is more representative local riil condition.

PENERAPAN RANTAI MARKOV PADA PENGEMBANGAN UJI KETERDUGAAN KUNCI (Markov Chain Technique in Key Predictability Test Development) Sari Agustini Hafman; Anang Kurnia; Agus Buono
FORUM STATISTIKA DAN KOMPUTASI Vol. 17 No. 1 (2012)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (706.618 KB)

One Time Key (OTK) system with key from alphabetical sequences is one of symmetric encryption algorithm that used in Indonesia to protect secret information. Alphabetic sequences in OTK system must be cryptographically secure pseudorandom sequences. OTK system in Indonesia only tested by overlapping m-tuple test developed by Marsaglia (2005). Overlapping m-tuple test doesn’t check the unpredictability of alphabetical sequences, it just tests distribution form and indpendency of alphabetical sequences. So, an alphabetical sequence in OTK system cannot be used in cryptography application by the reason of unpredictability sequence is unknown. Because some of Pseudorandom Number Generator (PRNG) algorithm based on block cipher algorithm that has markovian properties, markov chain model used to detect predictability alphabetical sequences. Data in this study consists of two data sources i.e. simulation data that generated from four classes PRNG and OTK system keys in 2005 that used in three communication units of foreign ministry. Simulation data is used to develop key predictability test methodology by find predictability threshold value based on characteristic of match level. OTK system keys will be predictability tested by comparing characteristic of match level with threshold value that is obtained from simulation data. The first result of this study shows the alphabetical sequence generated by first, second and fourth PRNG class can't be modeled with first-order markov chain until third-order. The third PRNG class, except PRNG LCG1, LCG2, coveyou, rand and randu, also can't be modeled with first order markov chain until third-order. Sequence generated by LCG2, coveyou, rand and randu are not fit for use in cryptography because it has a high probability to be modeled by high orders of markov chain (above the order of three). The second result obtains predictability threshold value with markov chains based on the minimum and maximum match level on the second-order and third-order. The last result shows the size of training data must be greater than the size of the observation data with the best ratio between the size of training data with observational data is 100: 10. The results of testing using 10 times repeated shows that the match level average of the OTK system key match on the all of three-order less than 4.5 x 10-2, so the OTK system the is feasible to secure information in three communication units. Keywords: One Time Key (OTK), markov chain, PRNG, probability transition, match level

Pemodelan Jaringan Syaraf Tiruan untuk Memprediksi Awal Musim Hujan Berdasarkan Suhu Permukaan Laut Laila Sari Lubis; Agus Buono
Jurnal Ilmu Komputer dan Agri-Informatika Vol 1 No 2 (2012)
Publisher : Departemen Ilmu Komputer, Institut Pertanian Bogor

Anjatan, Indramayu adalah salah satu daerah pertanian di Indonesia. Keberhasilan atau kegagalan panen setiap tahun tergantung pada ketersediaan air di wilayah tersebut. Oleh karena itu, diperlukan suatu metode yang akurat untuk memprediksi awal musim hujan. Metode yang digunakan untuk prediksi dalam penelitian ini adalah jaringan saraf tiruan (JST) back-propagation. Hasil akurasi prediksi JST diukur dengan R2 dan RMSE. Penelitian ini menggunakan suhu permukaan laut (SST) ECHAM4p5_CA yang merupakan salah satu model suhu permukaan laut di bulan Juni, Juli, dan Agustus. Domain SST dipilih berdasarkan korelasi 5% dan 10% untuk masing-masing bulan Juni, Juli, dan Agustus. Penelitian ini menggunakan arsitektur JST dengan dua parameter: hidden neuron (HN) dan learning rate (LR). Jumlah hidden neuron yang digunakan dalam penelitian ini adalah 5, 10, 20, dan 40, dan tingkat pembelajaran adalah 0.3, 0.1, dan 0.01. Prediksi hasil terbaik untuk korelasi 5% menggunakan JST adalah untuk bulan Juni dengan R2 adalah 51% dan RMSE 3.03 pada HN 10 dan LR 0.01, Juli dengan R2 adalah 48% dan RMSE 3.39 pada HN 20 dan LR 0.1, dan Agustus dengan R2 adalah 75% dan RMSE 2.51 di HN 40 dan LR 0.01. Prediksi hasil terbaik untuk korelasi 10% menggunakan JST adalah untuk bulan Juni dengan R2 adalah 44% dan RMSE 3.32 di HN 5 dan LR 0.3, Juli dengan R2 adalah 42% dan RMSE 3.42 di HN 10 dan LR 0.1, dan Agustus dengan R2 adalah 71% dan RMSE 3.37 di HN 20 dan LR 0.01. Kesimpulan dari penelitian ini adalah hidden neuron dan learning rate dengan nilai yang berbeda mempengaruhi R2 dan RMSE. Kata kunci: hidden neuron, jaringan saraf tiruan, learning rate, RMSE, R2

Perbandingan Sistem Perhitungan Suara Tepuk Tangan dengan Metode Berbasis Frekuensi dan Metode Berbasis Amplitudo Puspita Kartika Sari; Karlisa Priandana; Agus Buono
Jurnal Ilmu Komputer & Agri-Informatika Vol. 2 No. 1 (2013)
Publisher : Departemen Ilmu Komputer - IPB University

Sistem penilaian berdasarkan suara tepuk tangan sering digunakan dalam acara perlombaan di Indonesia. Namun, penentuan pemenang dengan cara konvensional cenderung subjektif. Penelitian ini mengembangkan sistem penilaian otomatis berbasis komputer untuk menghitung jumlah orang bertepuk tangan dan menentukan pemenang dari perlombaan berdasarkan tepuk tangan. Penelitian ini membandingkan dua metode yang dapat diterapkan yaitu metode berbasis frekuensi dan metode berbasis amplitudo. Metode yang berbasis frekuensi mengimplementasikan Mel Frequency Cepstral Coefficient (MFCC) sebagai pengekstraksi ciri dan codebook sebagai pengenal pola. Hasil yang diperoleh merupakan suatu model berupa kelas-kelas yang diklasterkan oleh K-Means clustering. Parameter penting dalam metode ini adalah jumlah koefisien cepstral, overlap, time frame, dan jumlah klaster. Beberapa pengujian dilakukan untuk menemukan parameter optimum dengan nilai akurasi tertinggi. Metode kedua merupakan metode berbasis amplitudo yang dilakukan dengan menghitung jumlah sampel sinyal yang memiliki nilai amplitudo di atas nilai-nilai ambang (thresholds) tertentu yang menghasilkan akurasi maksimum. Hasil penelitian menunjukkan bahwa akurasi sistem berbasis frekuensi untuk tepuk tangan periodik adalah 83.3% dan untuk tepuk tangan acak ialah 50% sehingga akurasi sistem untuk tepuk tangan acak berbasis threshold yang lebih sederhana ialah 66.7 %. Dengan demikian, metode berbasis amplitudo baik digunakan.Kata kunci: Codebook, K-means, Mel Frequency Cepstral Coefficients (MFCC), Pengenalan Suara, Threshold

IDENTIFIKASI CAMPURAN NADA PADA SUARA PIANO MENGGUNAKAN CODEBOOK Ade Fruandta; Agus Buono
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2011
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

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Pada paper ini disajikan teknik pengenalan nada, baik sebagai nada tunggal maupun nada campuran dengan menggunakan mel-frequency cepstrum coefficients (MFCC) sebagai ekstraksi ciri dan pemodelancodebook untuk pengenal pola. Suara yang dpergunakan adalah suara piano dan dikenali 12 nada tunggal dan 66 nada campuran yang disample dengan 11 kHz pada durasi 1 detik. Pembuatan codebook dilakukan secara bertahap, yaitu codebook jumlah campuran dan codebook nada (tunggal dan campuran) yang dikembangkan dengan menggunakan teknik pengklasteran. Hasil percobaan menunjukkan bahwa jumlah codeword yang optimum adalah 20 dengan lebar frame 256 data, dengan akurasi 98.2%. Namun demikian, ada beberapa nada yang sulit dikenali, yaitu CC#, CD, CF, dan A#B yang memiliki akurasi masing-masing di bawah 50%. Untuk nada CC# lebih sering dikenali nada C, untuk nada CD lebih sering lebih sering dikenali dengan nada C#, untuk nada CF lebih sering dikenali dengan nada C# dan CF#, sedangkan untuk nada A#B lebih sering dikenali dengan nada A#. Kesalahan dalam pengenalan ini dikarenakan nada-nada tersebut berada dalam klaster yangsama sehingga jarak nada-nada tersebut saling berdekatan.

PEMODELAN JARINGAN SYARAF TIRUAN UNTUK PREDIKSI PANJANG MUSIM HUJAN BERDASAR SEA SURFACE TEMPERATURE Agus Buono; M. Mukhlis; Akhmad Faqih; Rizaldi Boer
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2012
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

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Penelitian ini difokuskan pada pemodelan Jaringan Syaraf Tiruan untuk prediksi Panjang Musim Hujan, dengan mengambil studi kasus stasiun Sumur Watu di Indramayu. Peubah yang dipergunakan sebagai prediktor adalah Suhu Permukaan Laut pada bulan Juni, Juli dan Agustus yang berupa data grid dan dipilih berdasar nilai korelasi pada taraf nyata 5% dan 10%. Sedangkan peubah respon adalah panjang musim hujan satu periode ke depan yang diukur dalam dasarian (10 harian). Dari 17 tahun periode data, selanjutnya dilakukan pemodelan JST dengan 4 variasi jumlah hidden neuron (5, 10, 20 dan 40) dan 3 laju pembejaran (0.3, 0.1 dan 0.001) pada 6 data set kombinasi dari 3 jenis bulan dan 2 jenis taraf nyata, dan dilakukan dengan 4-fold cross validation untuk melihat skil dari model dalam melakukan prediksi . Selain itu juga dilakukan pemodelan jaringan syaraf tiruan dengan menggunakan grid yang secara konsisten nyata berpengaruh pada panjang musim hujan baik untuk suhu muka laut pada bulan Juni, Juli, ataupun Agustus. Hasil percobaan menunjukkan bhawa suhu muka laut pada bulan agustus memberikan skil tertinggi dengan akurasi 81% dan 84%. Sedangkan untuk bulan Juni dan Juli berkisar sekitar 50%. Prediksi dengan SST pada grid yang konsisten memberikan akurasi sebesar 65%.

Co-Authors Ade Fruandta Adi Rakhman Aditya Cipta Raharja Agung Prajuhana Putra Akhmad Faqih Alif Kurniawan Alvin Fatikhunnada Anang Kurnia Angga Wahyu Pratama Aries Maesya Arif Imam Suroso Arini Aha Pekuwali Arini Pekuwali Astuti, Indah Puji Atik Pawestri Sulistyo Aziz Kustiyo Aziz Rahmad Benyamin Kusumoputro Bib Paruhum Silalahi Budi Nugroho Cece Sumantri Dhany Nugraha Ramdhany Dian Kartika Utami Djaksana, Yan Mitha Edi Santosa Ekowati Handharyani Elisabeth Sri Hendrastuti Endang Purnama Giri Erliza Hambali Erliza Noor Ernan Rustiadi Fadhilah Syafria Fadhilah Syafria Fajar Delli Wihartiko Fildza Novadiwanti Firdaus, Husni Firmansyah Ibrahim Fredicia Fredicia Galih Kurniawan Sidik Galih Kurniawan Sidik Galih Kurniawan Sidik Gema Parasti Mindara Gendut Suprayitno Gita Adhani GUNARSO GUNARSO Hastuadi Harsa Herianto Herianto Hidayat Hidayat Hidayat I Wayan Astika Ibrahim, Firmansyah Iis Rodiah Imas Sukaesih Sitanggang Indah Prasasti Indah Puji Astuti Indah Puji Astuti Indra Jaya Inggih Permana Inna Noviyanti Irman Hermadi Irmansyah . Irsal Las Irsal Las ISKANDAR ZULKARNAEN SIREGAR Kana Saputra S Karlisa Priandana Kikin H Mutaqin Kudang Boro Seminar Laila Sari Lubis Laila Sari Lubis Lailan Syaufina Lidya Ningsih Liyantono . M. Cholid Mawardi M. Mukhlis Marcelita, Faldiena Medria Kusuma Dewi Hardhienata Mohamad Solahudin Muhammad Ardiansyah Muhammad Rafi Muttaqin Mushthofa Mustakim Mustakim Mustakim Mustakim Muttaqin, Muhammad Rafi Niswati, Za'imatun Nova Firdaus Nurhayati, Yosi Popong Nurhayati Pratistya, Sayu Desty Puspita Kartika Sari Puspita Kartika Sari Putri Yuli Utami Raharja, Aditya Cipta Rahmat Hidayat Rizal Syarief Rizaldi Boer Rizki, Arviani RR. Ella Evrita Hestiandari Santo, Deni Sanusi Sanusi Sari Agustini Hafman Savitri, Siska Sholihah, Walidatush Sidik, Galih Kurniawan Siregar, Ardinsyah Sitanggang, Imas S. Siti Kania Kushadiani Siti Raehan Sony Hartono Wijaya Sri Dianing Asri Sri Nurdiati Sri Wahjuni Stephane Douady Suharno Suharno Suharno Sumanto, Sumanto Syeiva Nurul Desylvia Taufik Djatna Thoyyibah Tanjung Toto Haryanto Trukan Sri Bahukeling Uliniansyah, Mohammad Teduh Vicky Zilvan Wisnu Ananta Kusuma Wisnu Jatmiko Woro Estiningtyas Woro Estiningtyas Woro Estiningtyas Yandra Arkeman Yenni Vetrita Yoanda, Sely

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