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Studi Morfologi Domba Ekor Gemuk Silangan (DEGS) Di Lembah Palu Irfan, Mohamad; Dg. Malewa, Amiruddin
AgriSains Vol 13, No 3 (2012)
Publisher : FAPETKAN UNTAD

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This Research target to know the comparison form and size measure of parts of body (morfologi) of Fat Tail Sheep Livestock Traverse (female and Masculine DEGS) residing in Countryside of Bora and Chief Of Village Taipa Sulawesi Province. Parameter of livestock body qualitative and quantitative which Method used in this research is combination between "Frequency Relative" as which used by Mulliadi (1996) and Analyse The Especial Component (Principal Component Analyse) according to Gasperz (1992). Research result indicate that qualitative and quantitative sheep livestock in Countryside Bora more dominant form and also size measure of body compared to a sheep residing in Chief of village Taipa, this matter  strenghtened with the result analyse the especial component (AKU) (P>0,05) do not give the real influence among second of accurate sheep. that way also size measure parameter at female sheep like head footage, long  ear, long neck, long  body, long  back, long  thigh and tail length do not give the real influence (P>0,05). Key words : DEGS, morfologi.
Gambaran Kesejahteraan Burung Murai Batu (Copsychus malabaricus) di Annafi Bird Farm, Cirebon, Jawa Barat Irfan, Mohamad; Agustian, Dwi; Hiroyuki, Andi
Indonesia Medicus Veterinus Vol 9 (5) 2020
Publisher : Faculty of Veterinary Medicine, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19087/imv.2020.9.5.683

Abstract

Dalam International Union for Conservation of Nature (IUCN) Redlist pada tahun 2019 status konservasi burung murai batu (Copsychus malabaricus) di dunia tergolong beresiko punah. Di Pulau Jawa murai termasuk burung langka. Penyebab utama kelangkaan dan kepunahan adalah rusaknya habitat dan perburuan untuk diperdagangkan, sehingga perlu adanya upaya konservasi salah satunya dalam bentuk kegiatan penangkaran agar keberadaanya tetap lestari. Annafi Bird Farm merupakan salah satu penangkar burung murai batu yang berada di Cirebon, Jawa Barat dalam pemanfaatannya perlu untuk memperhatikan kesejahteraan hewan. Kesejahteraan hewan adalah segala urusan yang berhubungan dengan keadaan fisik dan mental hewan menurut ukuran perilaku alami hewan. Penilaian terhadap penerapan kesejahteraan hewan dapat membantu pihak penangkar untuk lebih memperhatikan kesejahteraan satwa dari penanganan medis maupun non-medis. Penelitian ini bertujuan untuk menggambarkan kesejahteraan burung murai batu yang dikelola oleh penangkar Annafi Bird Farm. Sampel responden diambil menggunakan total sampling yaitu satu animal keeper yang bekerja di penangkaran. Selain itu dilakukan pengamatan pada 65 ekor burung dari seluruh kandang. Variabel yang diamati adalah kesejahteraan hewan dan program kesejahteraan hewan pada burung murai batu di penangkaran. Pengambilan data dilakukan menggunakan wawancara terstruktur dan lembar observasi checklist mengacu pada peraturan dirjen PHKA No. 6 Tahun 2011 yang diisi oleh peneliti dan pengelola kemudian data diolah secara deskriptif. Hasil didapatkan bahwa menurut peneliti memiliki skor 74,8 dan menurut pengelola 82. Skor tersebut termasuk kategori baik. Hal yang perlu diperhatikan untuk meningkatkan kesejahteraan murai batu yaitu pada dimensi bebas rasa sakit dan luka dan bebas bebas dari rasa takut dan tertekan.
Implementasi Algoritma Support Vector Machine untuk Meingdentifikasi Komentar Negatif dalam Gambar di Media Sosial Andriyan, Acep Razif; Alam, Cecep Nurul; Sa’adillah, Dian; Maylawati, Maylawati; Irfan, Mohamad; Lukman, Nur
Intellect : Indonesian Journal of Learning and Technological Innovation Vol. 2 No. 1 (2023): Intellect : Indonesian Journal of Learning and Technological Innovation
Publisher : Yayasan Lembaga Studi Makwa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57255/intellect.v2i1.288

Abstract

As many as 191 million people are active users of social media in Indonesia, with many users often expressing opinions or making comments on social media that are positive or negative, such as blaspheming, bullying, insulting and so on. One form of comment is presented through images (memes), namely images that contain text in them. Therefore, a system was created to classify two types of images, positive and negative, using the SVM algorithm method with RBF kernel and OCR technology for retrieving text in images. The SVM algorithm functions to carry out classification and OCR technology functions to extract text from an image. Testing was carried out using split validation which produced the accuracy of the best model using a data comparison of 90:10 and produced an accuracy of 85.7%. Abstrak Sebanyak 191 juta orang sebagai pengguna aktif media sosial di indonesia, dengan banyaknya pengguna sering kali menyampaikan pendapat atau berkomentar di media sosial yang bersifat positif maupun negatif seperti menghujat, membuly, mencaci dan lain sebagainya. Salah satu bentuk komentar tersebut disajikan melalui gambar (meme) yaitu gambar yang mengandung teks di dalamnya. Maka dari itu diperlukan sebuah sistem untuk mengklasifikasi dua jenis gambar yang bersifat positif dan negatif menggunakan metode algoritma SVM dengan karnel RBF dan teknologi OCR untuk pengambilan teks dalam gambar. Algoritma SVM berfungsi untuk melakukan klasifikasi dan teknologi OCR berfungsi untuk mengekstrak text yang berada pada sebua gambar. Pengujian dilakukan dengan menggunakan split validation yang menghasilkan akurasi dari model terbaik dengan menggunakan perbandingan data 90:10 dan menghasilkan akurasi 85.7%.
Cryptocurrency dan Stabilitas Sistem Keuangan: Tinjauan Literatur Dampak, Peluang, dan Tantangan Regulasi Abdurohim, Abdurohim; Irfan, Mohamad
Portofolio: Jurnal Ekonomi, Bisnis, Manajemen, dan Akuntansi Vol 21 No 2 (2024): Portofolio: Jurnal Ekonomi, Bisnis, Manajemen dan Akuntansi
Publisher : Fakultas Ekonomi dan Bisnis, Universitas Jenderal Achmad Yani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26874/portofolio.v21i2.696

Abstract

Cryptocurrency has become a transformative element in modern financial systems, presenting significant opportunities and risks to systemic stability. Its rapid adoption, driven by blockchain technology, demonstrates potential for enhancing transparency and efficiency. However, challenges such as price volatility, regulatory gaps, and cybersecurity threats persist as critical concerns. This study addresses the dual role of cryptocurrency in fostering innovation while posing risks to global financial stability. Employing a systematic literature review, it analyzes academic articles from leading databases, including Scopus and Web of Science, focusing on recent studies (2018–2023) examining the security, regulation, and ethical dimensions of cryptocurrency and blockchain technology. Findings highlight cryptocurrency’s potential to improve financial inclusion and operational efficiency but underscore significant risks due to price instability and inadequate regulatory frameworks. Blockchain technology offers improved security and accountability; however, effective integration requires adaptive regulations and international cooperation. This study contributes by synthesizing insights into cryptocurrency’s systemic implications, bridging gaps in understanding the intersection of technology, regulation, and stability. It provides actionable recommendations for policymakers, financial institutions, and academics to develop balanced regulatory frameworks that support innovation while safeguarding consumer interests and financial stability. Holistic regulatory approaches, strengthened cybersecurity, and cross-sector collaboration are imperative for responsible cryptocurrency integration into global financial ecosystems.
Penerapan Algoritma K-Nearest Neighbor untuk Menentukan Potensi Ekspor Komoditas Pertanian di Provinsi Sulawesi Tengah Ngemba, Hajra Rasmita; Raivandy, I Made Randhy; Hendra, Syaiful; Ardiansyah, Rizka; Dwi Wijaya, Kadek Agus; Nugraha, Deny Wiria; Irfan, Mohamad
Jurnal Teknologi dan Manajemen Informatika Vol. 9 No. 2 (2023): Desember 2023
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v9i2.10235

Abstract

Agriculture is a highly robust sector in Indonesia. This is evidenced in Central Sulawesi Province, where the gross domestic product (GDP) from the agricultural sector, based on constant prices from 2018 to 2021, continues to experience growth. Such conditions suggest that commodities in the agricultural sector have the potential to become export products, enabling a greater economic boost for the region. Before engaging in exports, it is necessary to identify which commodities have potential. One way to determine this is by applying Klassentypology. To simplify the process, it can be implemented in machine learning using the K-Nearest Neighbor algorithm. K-Nearest Neighbor is chosen because this algorithm can handle data containing noise and has good adaptability when given new data. In this research, two machine learning models were developed. The first model is used to classify whether a commodity is advancing or lagging, while the second model is used to classify commodities that grow rapidly and slowly. The highest accuracy obtained from the first model is 96.23%. Meanwhile, the highest accuracy from the second model is 93.49%.
A Deep Learning Approach Using VGG16 to Classify Beef and Pork Images Zulfikar, Wildan Budiawan; Angelyna, Angelyna; Irfan, Mohamad; Atmadja, Aldy Rialdy; Jumadi, Jumadi
JOIV : International Journal on Informatics Visualization Vol 9, No 2 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.2.2848

Abstract

There are 87.2% of the Muslim population in Indonesia, which makes Indonesia one of the countries with the largest Muslim population in the world. As a Muslim, it is supposed to carry out and stay away from the commands that Allah SWT commands, one of which is in QS. Al-maidah:3, one of the commands in the verse is not to consume haram food such as pork. Even so, it turns out that many traders in Indonesia still cheat to get more significant profits, namely by counterfeiting beef and pork. The lack of public knowledge supports this situation to differentiate between the two types of meat. Therefore, the classification process is used to distinguish the two kinds of meat using the convolutional neural network approach with VGG16 with several preprocessing stages. Two primary stages are used during the preprocessing stage: scaling and contrast enhancement. The VGG16 algorithm gets very good results by getting an accuracy value of 99.6% of the test results using 4,500 images for training data and 500 images for testing data. To compare the effectiveness of these techniques, it is recommended to use alternative CNN architectures, such as mobilNet, ResNet, and GoogleNet. More investigation is also required to gather more varied datasets, enabling the ultimate goal to achieve the best possible categorization, even when using cell phone cameras or with dim or fuzzy photos.
Implementation of Brute Force Algorithm for Digital Land Mapping Information System: Implementasi Algoritma Brute Force untuk Sistem Informasi Pemetaan Tanah Digital Irfan, Mohamad; Ngemba, Hajra Rasmita; Hendra, Syaiful; Syahrullah, Syahrullah; Lapatta, Nouval Trezand; Hamid, Odai Amer
Technomedia Journal Vol 10 No 1 (2025): June
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v10i1.2271

Abstract

The Land Asset Mapping Information System of the Palu City Local Government was developed to streamline digital land record management and enhance public service delivery. However, users experience substantial delays averaging 3-5 minutes per query during manual data searches. This study aims to optimize search efficiency by implementing the Brute force string-matching algorithm, allowing users to retrieve precise land records through direct pattern input. A waterfall system development methodology was systematically applied across five phases: requirements analysis, system design, PHP/JavaScript implementation, White Box testing, and maintenance. The research team collaborated closely with 12 technical officers from the City Spatial Planning and Land Office to validate system requirements and evaluate real-world performance. The implementation of the Brute force algorithm reduced average search times by 68\% (from 185s to 59s) while maintaining 100\% accuracy in test datasets containing 5,000+ land records. Rigorous testing confirmed the algorithm's reliability across various edge cases, including partial matches and special character inputs. The application of the Brute force method has transformed the system's search functionality, particularly for frequent queries involving land parcel IDs and owner names. These improvements have increased daily processing capacity by 40\%, significantly benefiting urban planning and dispute resolution workflows. While demonstrating excellent performance for medium-sized datasets, the solution presents opportunities for future enhancement through hybrid approaches combining Brute force with indexing techniques for large-scale deployments beyond 50,000 records.
Analysis of the Readiness of Vocational School Teachers for the Expertise Program  Electrical Engineering in Developing Learning Based on Local Potential Supraptono, Eko; Sonhaji, Sonhaji; Kurniawan, Galang Wahid; Sunardiyo, Said; Irfan, Mohamad; Hidayattullah, Ardhana Luthfi
International Journal of Active Learning Vol. 10 No. 2 (2025): October 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ijal.v10i2.34325

Abstract

This study aims to analyze the readiness of teachers of the Electrical Engineering Expertise Program at SMK Negeri Semarang City in developing learning based on local potential in the digital era. Teacher readiness is reviewed through aspects of pedagogic, professional, digital, teaching experience, and training or certification. Local potential-based learning is understood as integrating regional resources and local wisdom into the curriculum through contextual methods with the support of digital technology. The research method uses a mixed approach. Quantitative data is obtained through questionnaires to measure teachers' readiness levels, while qualitative data is collected through interviews, classroom observations, and analysis of curriculum documents. Quantitative data analysis was carried out with descriptive statistics and linear regression to identify relationships between variables, while qualitative data were analyzed thematically to strengthen quantitative findings. The study's results are expected to reveal the supporting and inhibiting factors in implementing local potential-based learning, such as the limitations of digital infrastructure, the lack of relevant training, and education policies that are not optimal to encourage technology integration. Theoretically, this research contributes to enriching the study of teacher readiness by placing local potential as the basis for vocational learning innovation. Practically, the research results are expected to be a reference for education stakeholders to design strategies for increasing teacher capacity and policies more adaptive to technological developments and local industrial needs.
Application of Smoke Washer Device in Waste Incineration Machine to Reduce Exhaust Gas Emissions at Jatibarang Landfill Semarang Supraptono, Eko; Kurniawan, Galang Wahid; Sutopo, Yeri; Khumaedi, Muhammmad; Irfan, Mohamad; Sonhaji, Sonhaji; Hidayattullah, Ardhana Luthfi; Tukiman, Tukiman
Jurnal Abdimas Vol. 29 No. 2 (2025): December 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/abdimas.v29i2.33762

Abstract

Waste management at the Jatibarang Landfill, Semarang, faces challenges due to incinerator exhaust gas emissions, potentially decreasing air quality, and posing health risks to surrounding communities. This community service program implemented a smoke washer (wet scrubber) adapted to the conditions of a simple incinerator. The activities included designing and fabricating the device, integrating electrical and control systems, providing operational training for partners (CV Dewa Nata Persada and Jatibarang Landfill), and conducting field testing of exhaust gas quality. The tested parameters consisted of particulate matter (PM), carbon monoxide (CO), and sulfur dioxide (SO₂), which were compared with the quality standards of the Ministry of Environment and Forestry Regulation No. P.70 of 2016. The measurement results indicated that all parameters were below the threshold limits, with pollutant concentrations decreasing from the initial operation to the following hours, signifying more stable performance of the device under steady-state operating conditions. These findings demonstrate the importance of the community service program in enhancing partners’ awareness and capacity in environmentally friendly waste management, underscoring the project's significant impact.
Analisis Perilaku Beternak Masyarakat terhadap Usaha Ternak Kambing di Kawasan Dataran Tinggi Wilayah Transmigrasi Lembatongoa Kecamatan Palolo Kabupaten Sigi Maulita, Miftahul; Irfan, Mohamad; Mujayin, Yudi; Abdullah, Sirajuddin; Syahrir, Syahrir
Mimbar Agribisnis : Jurnal Pemikiran Masyarakat Ilmiah Berwawasan Agribisnis Vol 10, No 2 (2024): Juli 2024
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/ma.v10i2.14119

Abstract

This research aims to analyze the farming behavior of the transmigration community towards keeping goats in the highland areas in the Lembantongoa Transmigration area, Palolo District, Sigi Regency in September – November 2023. The research method used is a survey. Data collection techniques, namely field studies or observations through the interview process and filling out questionnaires. The variables observed in this research are economic (X1), social and cultural (X2), environmental (X3), food sources (X4), maintenance systems (Y1), income (Y2) and business development (Y3). The respondents used in this research were all transmigration communities who carried out goat breeding activities in the transmigration area, namely 74 breeders. The data collection technique uses a 1-5 Likert scale, while data analysis is carried out using quantitative descriptive methods. The results of the research showed that the highest average indicator scale proportion values were obtained for each latent variable, including: anticipation of plantation risk (X1.1), length of breeding (X2.3), temperature and humidity (X3.4), alternative feed (X4.5), cage cleanliness (Y1.5), farming income (Y2.1) and human resources (Y3.5). The conclusion of the research shows that the community's farming behavior regarding all latent variables has an average scale proportion that is in the good category.