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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 Jurnal Simetris 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

Published : 78 Documents Claim Missing Document

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Texture Analysis of Citrus Leaf Images Using BEMD for Huanglongbing Disease Diagnosis Sumanto; Buono, Agus; Priandana, Karlisa; Paruhum Silalahi, Bib; Sri Hendrastuti, Elisabeth
JOIN (Jurnal Online Informatika) Vol 8 No 1 (2023)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v8i1.1075

Plant diseases significantly threaten agricultural productivity, necessitating accurate identification and classification of plant lesions for improved crop quality. Citrus plants, belonging to the Rutaceae family, are highly susceptible to diseases such as citrus canker, black spot, and the devastating Huanglongbing (HLB) disease. Traditional approaches for disease detection rely on expert knowledge and time-consuming laboratory tests, which hinder rapid and effective disease management. Therefore, this study explores an alternative method that combines the Bidimensional Empirical Mode Decomposition (BEMD) algorithm for texture feature extraction and Support Vector Machine (SVM) classification to improve HLB diagnosis. The BEMD algorithm decomposes citrus leaf images into Intrinsic Mode Functions (IMFs) and a residue component. Classification experiments were conducted using SVM on the IMFs and residue features. The results of the classification experiments demonstrate the effectiveness of the proposed method. The achieved classification accuracies, ranging from 61% to 77% for different numbers of classes, the results show that the residue component achieved the highest classification accuracy, outperforming the IMF features. The combination of the BEMD algorithm and SVM classification presents a promising approach for accurate HLB diagnosis, surpassing the performance of previous studies that utilized GLCM-SVM techniques. This research contributes to developing efficient and reliable methods for early detection and classification of HLB-infected plants, essential for effective disease management and maintaining agricultural productivity.

Prediction of Duration of Dry Bamboo Leaf Counting Using Fuzzy Logic Marcelita, Faldiena; Mindara, Gema Parasti; Noviyanti, Inna; Sholihah, Walidatush; Buono, Agus
Eduvest - Journal of Universal Studies Vol. 3 No. 12 (2023): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v3i12.967

Dry bamboo leaves are selected as a planting medium for ornamental plants to enhance nutrient content and improve soil drainage. Before being processed into fertilizer, dry bamboo leaves need to be shredded first. The leaf counting process for planting ornamental plants in villages still relies on manual methods such as using knives and scissors, which can be time-consuming and less effective. In response to this issue, a device for shredding dry bamboo leaves has been developed to improve efficiency and facilitate the leaf counting process. The innovation created is a household-scale dry bamboo leaf shredder that is more affordable and easy to mobilize due to its compact dimensions and lighter weight. The device is also easy to operate, as the shredding occurs when it is closed, and the process stops when it is opened, ensuring safe use for various users. The manual control of bamboo leaf weight and counting duration results in inconsistent shredding outcomes. Therefore, development has been carried out on the dry bamboo leaf shredder with artificial intelligence capabilities, specifically using fuzzy logic to automate the counting duration based on the size and weight of the bamboo leaves being inputted.

Modified Q-Learning Algorithm for Mobile Robot Real-Time Path Planning using Reduced States Hidayat; Buono, Agus; Priandana, Karlisa; Wahjuni, Sri
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 3 (2023): Juni 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i3.4949

Path planning is an essential algorithm in any autonomous mobile robot, including agricultural robots. One of the reinforcement learning methods that can be used for mobile robot path planning is the Q-Learning algorithm. However, the conventional Q-learning method explores all possible robot states in order to find the most optimum path. Thus, this method requires extensive computational cost especially when there are considerable grids to be computed. This study modified the original Q-Learning algorithm by removing the impassable area, so that these areas are not considered as grids to be computed. This modified Q-Learning method was simulated as path finding algorithm for autonomous mobile robot operated at the Agribusiness and Technology Park (ATP), IPB University. Two simulations were conducted to compare the original Q-Learning method and the modified Q-Learning method. The simulation results showed that the state reductions in the modified Q-Learning method can lower the computation cost to 50.71% from the computation cost of the original Q-Learning method, that is, an average computation time of 25.74s as compared to 50.75s, respectively. Both methods produce similar number of states as the robot’s optimal path, i.e. 56 states, based on the reward obtained by the robot while selecting the path. However, the modified Q-Learning algorithm is capable of finding the path to the destination point with a minimum learning rate parameter value of 0.2 when the discount factor value is 0.9.

PENGELOLAAN COLD STORAGE IKAN DALAM PERSPEKTIF EKONOMI KELEMBAGAAN BARU Suharno, Suharno; Firdaus, Nova; Suharno; Buono, Agus
Forum Agribisnis Vol. 14 No. 2 (2024): FA VOL 14 NO 2 SEPTEMBER 2024
Publisher : Magister Science of Agribusiness, Department of Agribusiness, FEM-IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/fagb.14.2.1-15

Cold storage yang dibangun Kementerian Kelautan dan Perikanan (KKP) di berbagai daerah sebagai salah satu implementasi kebijakan Sistem Logistik Ikan Nasional (SLIN) yang bertujuan untuk menjaga ketersediaan ikan untuk bahan baku industri dan konsumsi dalam negeri. Cold storage 1.000 ton didirikan untuk menjadi role model sarana buffer stock milik pemerintah di Wilayah Jakarta namun dalam implementasinya masih mengalami kendala karena pemanfaatannya belum optimal dan belum menarik minat pelaku perikanan dalam cakupan yang lebih luas. Tujuan penelitian adalah mengkaji sistem kelembagaan yang diterapkan dalam pengelolaan cold storage 1.000 ton dari perspektif bisnis. Penelitian menggunakan metode studi kasus di cold storage pemerintah yaitu cold storage berkapasitas 1.000 ton yang terletak di Muara Baru, Jakarta Utara. Analisis kelembagaan pengelolaan cold storage dilakukan secara kualitatif deskriptif dengan pendekatan teori Ekonomi Kelembagaan Baru. Output analisis yang diharapkan berupa penilaian terhadap kelembagaan yang berjalan apakah telah sesuai dengan prinsip-prinsip ekonomi kelembagaan baru dan teori yang mendukung lainnya. Hasil penelitian menunjukkan bahwa kelembagaan cold storage 1.000 ton masih membutuhkan peningkatan pengelolaan. Aspek yang paling berkontribusi terhadap kurangnya kinerja bisnis di cold storage tersebut adalah property right dan flexibility and adaptability. Implikasi yang dapat diberikan adalah perbaikan kelembagaan melalui 1) pengembangan model bisnis yang lebih customize dengan kebutuhan pengguna, 2) pembentukan badan atau lembaga yang lebih otoritatif dalam layanan publik, 3) penyelarasan insentif dan membangun kerja sama dengan cakupan pengguna yang lebih luas, 4) penerapan standar prosedur yang diimbangi komitmen kepatuhan dari stakeholders dan kontrol yang kuat, 5) peningkatan kecepatan dan fleksibilitas layanan serta 6) penetapan harga yang kompetitif.

Perancangan Prototipe Sistem Manajemen Pengetahuan Antar Universitas (Studi Kasus IPB Dan UNPAK) Ibrahim, Firmansyah; Hermadi, Irman; Buono, Agus
Jurnal Pustakawan Indonesia Vol. 14 No. 2 (2015): Jurnal Pustakawan Indonesia
Publisher : Perpustakaan IPB

The rapid development of knowledge encourages universities to collaborate on their knowledge in specific expertise field to create an equitable distribution of knowledge. Program of computer science at Bogor Agriculture University (IPB) is a superior expertise in the field of agriculture while Pakuan University (UNPAK) is superior expertise in the field of electronics. The aim of this study was to design a prototype of knowledge management system as the knowledge sharing for learning of inter-universities using Knowledge Management System Life Cycle (KMSLC) method. The study result was Joomla one kind of Content Management System (CMS) can be used to share knowledge in the form of discussion forums and combining various info from IPB and UNPAK in one interface including news, announcements, agenda, and social media. This CMS also collaborate with applications Electronic Learning System (ELS) Moodle and Hyper Text Markup Language (HTML). ELS Moodle serves as an application in learning of inter-university with the single sign concept which was run in a single interface, while HTML serves as a search engine knowledge by generating external link that combines 2 KMS from IPB and UNPAK into one interface. The conclusion was the knowledge sharing for learning of inter-university can be done with the design of knowledge management system through collaboration three different systems.Keywords: CMS Joomla, ELS Moodle, HTML search engine, KMSLC, Knowledge Management Systems, Prototype

Pengembangan Sistem Pakar Identifikasi Awal Penyakit Kedelai Dengan Pendekatan Naïve Bayes Berbasis Android Astuti, Indah Puji; Hermadi, Irman; Buono, Agus; Mutaqin, Kikin H.
Jurnal Pustakawan Indonesia Vol. 14 No. 2 (2015): Jurnal Pustakawan Indonesia
Publisher : Perpustakaan IPB

Pengidentifikasian penyakit kedelai secara dini menjadi salah satu cara untuk meningkatan angka produktifitas kedelai. Jumlah pakar penyakit kedelai yang masih relatif sedikit apalagi di daerah pedesaan membuat ketergantungan atas keberadaan seorang pakar penyakit kedelai sangatlah tinggi terutama bagi para pemula di bidang pertanian. Suatu sistem pakar menjadi salah satu solusi yang dapat dijadikan sarana untuk berkonsultasi tentang penyakit kedelai layaknya seorang pakar. Sistem yang diimplementasikan dalam basis Android akan lebih mudah digunakan di manapun dan kapanpun tanpa harus bertemu dengan pakar karena kesempatan dan waktu pakar yang tidak mudah untuk ditemui setiap saat. Tujuan penelitian ini adalah untuk mengembangkan sistem pakar identifikasi awal penyakit kedelai dengan mengadopsi metode Expert System Development Life Cycle (ESDLC) untuk tahapan pengembangan sistem dan pendekatan Naïve Bayes sebagai metode inferensinya. Hasil penelitian ini berupa prototype sistem pakar XSIDS yang terdiri dari enam modul utama yaitu modul pengetahuan tentang kedelai, kebijakan pemerintah, konsultasi, tentang kami, tentang XSIDS dan note.Kata Kunci : Android, ESDLC, Naïve Bayes, Sistem Pakar, Penyakit Tanaman Kedelai

Digital Marketing Alliance on Small Medium Enterprises (SMES): A Systematic Literature Review Bahukeling, Trukan Sri; Imam Suroso, Arif; Buono, Agus; Nurhayati, Popong
Jurnal Aplikasi Bisnis dan Manajemen Vol. 10 No. 1 (2024): JABM, Vol. 10 No. 1, Januari 2024
Publisher : School of Business, Bogor Agricultural University (SB-IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17358/jabm.10.1.199

The development of digital marketing continues to grow and increase rapidly. Strengthening digital marketing by SMEs encourages marketing alliances with other parties. Simultaneously, the digital marketing alliance literature accumulated with this growth, but research is still few and not consistently integrated. SMEs are widely regarded as engines of economic growth and a vital contributor to a country's GDP. A brief comprehensive review is needed to help researchers and practitioners understand the adoption of digital marketing alliance systems. This study aims to analyze and classify the literature on digital marketing alliances in SMEs. Design/methodology by conducting literature studies published between 2016-2021 in the journal listed in the Journal Citation Report. It is then analyzed according to a systematic literature review approach involving interpretation-based assessments of research methodologies and critical findings in the study. The direction of this research is expected in the future to have implications for academics and practitioners. The authors' conclusions develop a theoretical model of digital marketing alliance between government and private that is applied to SMEs, impacting to create excellence in the era of digitalization. The originality /value of this research is the first expected to take a holistically integrated approach to study the digital marketing alliance of SMEs. Keywords: digital marketing, marketing alliance, small medium enterprises (smes), literature studies

NEURAL NETWORK INNOVATION FOR ANALYZING PHYSIOLOGICAL CHANGES IN CATTLE WITHIN MODERN TRANSPORTATION SYSTEMS Dhika, Harry; Buono, Agus; Neyman, Shelvie Nidya; Astuti, Dewi Apri
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol. 16 No. 2 (2025): JURNAL SIMETRIS VOLUME 16 NO 2 TAHUN 2025
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/simet.v16i2.16007

The distribution of cattle before Eid al-Adha often leads to transport-induced stress, negatively affecting livestock performance and economic value. This study aims to develop a predictive model of post-transport cattle performance using Artificial Neural Networks (ANN). The dataset includes physiological parameters (rectal temperature, heart rate, and respiration) and blood metabolites (glucose and creatinine) collected before and after transportation. Data augmentation and feature selection were applied using Pearson correlation to address class imbalance. The ANN model was tuned with regularisation and dropout techniques to prevent overfitting. Evaluation results show that the model achieved 91% accuracy, with F1-scores of 0.90 (Increase), 0.97 (Stable), and 0.87 (Decrease). These findings demonstrate that ANN can capture complex patterns of physiological conditions in cattle and provide reliable predictions. This model has the potential to serve as the basis for developing an early warning system to minimize the risk of performance decline in cattle due to transport stress more adaptively and efficiently.

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 Arini Aha Pekuwali Arini Pekuwali Astuti, Indah Puji Atik Pawestri Sulistyo Aziz Kustiyo Aziz Rahmad Bahukeling, Trukan Sri Benyamin Kusumoputro Bib Paruhum Silalahi Budi Nugroho Cece Sumantri DEWI APRI ASTUTI Dhany Nugraha Ramdhany Dian Kartika Utami Edi Santosa Ekowati Handharyani Elisabeth Sri Hendrastuti Endang Purnama Giri Erliza Hambali Erliza Noor Ernan Rustiadi Fadhilah Syafria Fajar Delli Wihartiko Fildza Novadiwanti Firdaus, Husni Firdaus, Nova Fredicia Fredicia Galih Kurniawan Sidik Galih Kurniawan Sidik Galih Kurniawan Sidik Gendut Suprayitno Gita Adhani GUNARSO GUNARSO Hardhienata, Medria Kusuma Dewi Harry Dhika, Harry Hastuadi Harsa Herianto Herianto Hidayat Hidayat Hidayat I Wayan Astika Ibrahim, Firmansyah Iis Rodiah Imam Suroso, Arif Imas Sukaesih Sitanggang Indah Prasasti Indah Puji Astuti Indra Jaya Inggih Permana 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 Mindara, Gema Parasti Mohamad Solahudin Muhammad Ardiansyah Muhammad Rafi Muttaqin Mushthofa Mustakim Mustakim Mustakim Mustakim Muttaqin, Muhammad Rafi Niswati, Za'imatun Noviyanti, Inna Nurhayati, Yosi Popong Nurhayati Pratistya, Sayu Desty Puspita Kartika Sari Puspita Kartika Sari Putri Yuli Utami Raehan, Siti Raharja, Aditya Cipta Rahmat Hidayat Rizal Syarief Rizaldi Boer Rizki, Arviani RR. Ella Evrita Hestiandari Santo, Deni Sanusi Sanusi Sari Agustini Hafman Savitri, Siska Shelvie Nidya Neyman Sholihah, Walidatush Sidik, Galih Kurniawan Siregar, Ardinsyah Sitanggang, Imas S. Siti Kania Kushadiani Sony Hartono Wijaya Sri Dianing Asri Sri Hendrastuti, Elisabeth Sri Nurdiati Sri Wahjuni Stephane Douady Suharno Suharno Suharno Sumanto, Sumanto Syeiva Nurul Desylvia Taufik Djatna Thoyyibah Tanjung Toto Haryanto Uliniansyah, Mohammad Teduh Vicky Zilvan Wisnu Ananta Kusuma Wisnu Jatmiko Woro Estiningtyas Woro Estiningtyas Woro Estiningtyas Yan Mitha Djaksana Yandra Arkeman Yenni Vetrita Yoanda, Sely

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