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All Journal Pastura; Journal Of Tropical Forage Science Jurnal Ilmu Perairan (Aquatic Science) Proceeding Buffalo International Conference JURNAL PETERNAKAN JUSIFO : Jurnal Sistem Informasi Sistemasi: Jurnal Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA Tropical Animal Science Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JURNAL INSTEK (Informatika Sains dan Teknologi) Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal Sistem Cerdas Building of Informatics, Technology and Science Jurnal Sistem informasi dan informatika (SIMIKA) Jurnal Inovasi dan Teknologi Pembelajaran (JINOTEP) Kajian dan Riset Dalam Teknologi Pembelajaran JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Teknik Informatika (JUTIF) Wahana Peternakan PETERPAN (Jurnal Peternakan Terapan) Jurnal Pendidikan dan Teknologi Indonesia Studium: Jurnal Pengabdian Kepada Masyarakat Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Karya Abdi Masyarakat Jurnal Ilmiah Ilmu-Ilmu Peternakan Innovative: Journal Of Social Science Research Journal of Animal Nutrition and Production Science The Indonesian Journal of Computer Science
M. Afdal
Fakultas Peternakan Universitas Jambi
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Public Health Social Sciences Veterinary Other

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Mutu Jagung yang Diperdagangkan di Kota Jambi Diukur Berdasarkan Nilai Bulk Density dan Kandungan Serat Kasar S Fakhri; Y Zaharanova; M Afdal
PETERPAN (Jurnal Peternakan Terapan) Vol. 5 No. 1 (2023)
Publisher : Politeknik Negeri Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (289.294 KB) | DOI: 10.25181/peterpan.v5i1.2817

Abstract

Maize is being used as the main energy source in poultry feed in Indonesia. The authorities therefore, must guarantee that the maize available in markets must meet Indonesian quality standards. Determination of maize quality standards is still based on nutrient contents obtained through chemical analysis, which is very expensive and time consuming. The purpose of this study was to evaluate the quality of maize based on the bulk density (BD) value and crude fiber (CF) content of maize, these two parameters were then correlated to obtain the prediction equation. Samples were taken from 17 poultry shops (PS) of Jambi City and were divided into 3 groups based on sales turnover scale (large, medium, small). Each scale represented by 6 PS. Pure maize was used as a control. A total of 3 kg of maize samples was randomly taken from each PS represented by 3 sacks of maize.Obtained samples were subjected to BD measurement and CF analysis. The results showed that BD and CF of maize were not affected by sales turnover scale. There was adulteration of maize cobs in a proportion of 6.78, 7.67 and 15.47% in granulated, crushed and ground maize, respectively. The quality of maize traded at Jambi City was not affected by sales turnover scale. The chemical quality of maize as reflected by CF content (Y, %) can be predicted from BD (g/ml) according to this equation Y= -0.0285X + 21.83, r2= 0.65.
Kecernaan In-Sacco Bahan Kering, Bahan Organik, Dan Serat Kasar Daun Bangun-Bangun (Coleus amboinicus L) Yang Diproteksi Kapsul, Saponin Dan Tanin Yusuf Amirullah Luber; M Afdal; A. Adriani; D Darlis
Wahana Peternakan Vol. 6 No. 1 (2022): Wahana Peternakan
Publisher : Fakultas Peternakan Universitas Tulang Bawang Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37090/jwputb.v6i1.537

Abstract

Penelitian ini bertujuan untuk mengetahui kecernaan BK, BO dan SK pada daun bangun-bangun (Coleus amboinicus L) setelah dilakukan proteksi. Rancangan penelitian yang digunakan adalah rancangan acak lengkap (RAL) yang terdiri dari 4 perlakuan dan 5 ulangan. Perlakuan yang diberikan adalah memproteksi daun bangun-bangun P0 daun bangun-bagun tanpa perlakuan, P1 daun bangun-bangun di proteksi dengan kapsul, P2 daun bangun- bangun di proteksi daun kembang sepatu (saponin), P3 daun bangun-bangun di proteksi batang pisang (tanin). Peubah yang diamati yaitu kecernaan bahan kering (KcBK), kecernaan bahan organik (KcBO), dan kecernaan serat kasar (KcSK). Data diperoleh dianalisis dengan analisis ragam. Jika berpengaruh nyata dilanjutkan dengan uji jarak Duncan. Hasil penelitian menunjukkan bahwa proteksi menggunakan kapsul, saponin dan tanin berpengaruh nyata (P<0,05) terhadap KcBK, KcBO, dan KcSK daun bngun-bangun lebih lanjut terlihat pada P2 menunjukkan hasil yang baik dibandingkan P0, P1 dan P3. Hasil terbaik dicapai pada P2 yaitu proteksi menggunakan saponin yang di ekstrak dari daun kembang sepatu dengan hasil kecernaan BK (83,56%), BO (83,61%), SK (83,02%) Berdasarkan hasil ini dapat disimpulkan bahan proteksi berupa saponin dapat memproteksi daun bangun-bangun dengan baik.
Pendekatan Machine Learning: Analisis Sentimen Masyarakat Terhadap Kendaraan Listrik Pada Sosial Media X Kusuma, Gathot Hanyokro; Permana, Inggih; Salisah, Febi Nur; Afdal, M.; Jazman, Muhammad; Marsal, Arif
JUSIFO : Jurnal Sistem Informasi Vol 9 No 2 (2023): JUSIFO (Jurnal Sistem Informasi) | December 2023
Publisher : Program Studi Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Raden Fatah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19109/jusifo.v9i2.21354

Abstract

Environmental issues and the depletion of fossil fuels continue to escalate as the number of fossil fuel-based vehicle users increases in Indonesia. Electric vehicles emerge as one of the potential alternative solutions to address current environmental challenges, given their eco-friendly nature and lack of pollution emissions. Sentiment analysis is conducted to understand public responses, both supportive and opposing, towards electric vehicles. This research aims to analyze the sentiment of X-social media users regarding electric vehicles using machine learning techniques. The research stages include data collection, data selection, preprocessing, and classification using Naïve Bayes Classifier (NBC), Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) algorithms. The test results show that on a balanced dataset using ROS, SVM performs the best with accuracy = 68.7%, precision = 77.9%, and recall = 68.4%. Meanwhile, NBC yields an accuracy of 60.3%, precision of 61.3%, and recall of 60.3%, while KNN has an accuracy of 53.9%, precision of 54%, and recall of 53.9%.
Perbandingan Algoritma KNN, NBC, dan SVM: Analisis Sentimen Masyarakat Terhadap Perparkiran di Kota Pekanbaru Intan, Sofia Fulvi; Permana, Inggih; Salisah, Febi Nur; Afdal, M.; Muttakin, Fitriani
JUSIFO : Jurnal Sistem Informasi Vol 9 No 2 (2023): JUSIFO (Jurnal Sistem Informasi) | December 2023
Publisher : Program Studi Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Raden Fatah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19109/jusifo.v9i2.21357

Abstract

The public response in Pekanbaru to parking policies and regulations has given rise to various sentiments, both positive and negative. This discussion extends not only within the local community but also across various social media platforms. This research aims to analyze public sentiment towards the new parking policies and regulations in the Pekanbaru area. The study involves the KNN, NBC, and SVM algorithms to classify public sentiment into positive, neutral, and negative categories. Balancing techniques used in this research include Random Over Sampling (ROS) and Random Under Sampling (RUS). The data utilized in this study were obtained from posts on the social media platform X. The testing of the dataset using ROS resulted in high accuracy, precision, and recall values. The findings of this research indicate that overall, the SVM algorithm outperforms KNN and NBC in terms of accuracy, precision, and recall. Additionally, the most dominant sentiment is negative, with 422 tweets expressing dissatisfaction with the current parking policies.
A Comparative Study of the Performance of KNN, NBC, C4.5, and Random Forest Algorithms in Classifying Beneficiaries of the Kartu Indonesia Sehat Program Nabillah, Putri; Permana, Inggih; Afdal, M.; Muttakin, Fitriani; Marsal, Arif
JUSIFO : Jurnal Sistem Informasi Vol 10 No 1 (2024): JUSIFO (Jurnal Sistem Informasi) | June 2024
Publisher : Program Studi Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Raden Fatah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19109/jusifo.v10i1.21536

Abstract

This study evaluates the performance of various algorithms in determining eligible recipients for the Kartu Indonesia Sehat program. The Random Forest algorithm demonstrated the highest accuracy, precision, and recall, with values of 72.08%, 72.41%, and 99.64%, respectively. The emphasis on recall helps minimize errors in identifying eligible recipients. Additionally, the C4.5 algorithm reduced the total number of variables from 33 to 8, highlighting its computational efficiency. The findings provide valuable insights for the Social Affairs Office of Dumai City in making informed decisions regarding KIS eligibility. The results underscore the effectiveness of using algorithmic approaches to enhance the accuracy and efficiency of aid distribution processes.
Pengelolaan Limbah Rumah Tangga menjadi Eco-Enzyme melalui Proses Fermentasi Indriyani; Tafzi, Fitry; Afdal, M.; Ulyarti; Lisani
Studium: Jurnal Pengabdian Kepada Masyarakat Vol 3 No 3 (2024): Studium: Jurnal Pengabdian Kepada Masyarakat
Publisher : WIDA Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53867/jpm.v3i3.107

Abstract

Forum Indonesia Muda (FIM) is an independent forum consisting of young people from various backgrounds, universities, and youth movements from all over Indonesia, with the aim of building the nation through a spirit of collective contribution. With the diverse backgrounds of its members, each individual has their own role, leading FIM Jambi to have several divisions to channel the youth roles effectively. Organic waste is material that is discarded but still has potential for reuse, especially fruit and vegetable peels that can be processed into liquid and solid products beneficial to the environment. This liquid is known as eco-enzyme, which is highly beneficial for health, the environment, and agriculture. This activity aims to reduce the amount of fruit and vegetable peel waste. The community service activity is divided into four stages of implementation, namely: the survey stage, the socialization stage, the technical training stage, and the mentoring stage. The results of this activity are expected to generate a significant positive impact on waste management and environmental sustainability, particularly for FIM as youth who play a role in environmental preservation. This activity provides a solution that can be widely applied in the community to create a cleaner and healthier environment.
Efektivitas Model Pembelajaran Berbasis Proyek Terhadap Keaktifan dan Kemampuan Mahasiswa Suseno, Rahayu; Indriyani, Indriyani; Afdal, M.; Nizori, Addion
Jurnal Inovasi dan Teknologi Pembelajaran Vol 9, No 1 (2022)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um031v9i12022p090

Abstract

Abstrak: Penelitian ini bertujuan untuk mengetahui efektivitas pembelajaran berbasis proyek dalam meningkatkan aktivitas dan kemampuan mahasiswa. Metode penelitian yang digunakan adalah Weak Experimental dengan desain One Group Pretest – Posttest yang dilakukan kepada mahasiswasemester lima pada mata kuliah Sanitasi Industri, Program studi Teknologi Hasil Pertanian. Pengumpulan data menggunakan instrument tes dan angket. Analisis data dilakukan dengan analisis deskriptif. Hasil penelitian menunjukkan bahwa kemampuan mahasiswa meningkat berdasarkan n-gain rata-rata kelas yang masuk dalam kriteria sedang sebesar 0,39. Tanggapan mahasiswa terhadap pembelajaran berbasis proyek termasuk kedalam kriteria sangat tertarik (94,92%) dengan persentase sangat setuju 30,98% dan setuju 63,93%. Metode pembelajaran berbasis proyek efektif dalam meningkatkan aktivitas dan kemampuan mahasiswa pada mata kuliah Sanitasi Industri.Abstract: This study aims to determine the effectiveness of project-based learning in increasing student activities and abilities. The research method used is Weak Experimental with the design of One Group Pretest – Posttest which is carried out to fifth semester students in the Industrial Sanitation course, Agricultural Product Technology Study Program. Collecting data using test instruments and questionnaires. Data analysis was done by descriptive analysis. The results showed that the student's ability increased based on the n-gain average class that was included in the moderate criteria of 0.39. Student responses to project-based learning were included in the criteria for being very interested (94.92%) with the percentage strongly agreeing 30.98% and agreeing 63.93%. Project-based learning methods are effective in increasing student activities and abilities in Industrial Sanitation courses.
Comparison of Service and Ease of e-Commerce User Applications Using BERT Yuda, Afi Ghufran; Novita, Rice; Mustakim; Afdal, M.
Jurnal Sistem Cerdas Vol. 7 No. 2 (2024)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v7i2.403

Abstract

The development of e-commerce has transformed shopping patterns by harnessing the internet, enabling consumers to shop online. In Indonesia, e-commerce has experienced rapid growth, with numerous options such as Tokopedia, Shopee, and Lazada, leading to intense competition. Sentiment analysis using machine learning techniques has become crucial for understanding consumer views on these e-commerce services. This study analyzes user comments on Tokopedia, Shopee, and Lazada e-commerce platforms from Instagram social media, totaling 3900 data points, using the Bidirectional Encoder Representations from Transformers (BERT) model with 5 epochs and a batch size of 32. Sentiment analysis utilizes 3 types of labels: positive, neutral, and negative. The final results of the study include the performance analysis of the BERT model, as well as comparisons for each predefined category, namely Promotions & Offers, and Services. The final results of the model indicate good performance, with accuracy rates of 95%, 97%, and 99%, respectively.
Analisis Sentimen Masyarakat Terhadap Penghapusan Honorer Berdasarkan Opini Dari Twitter Menggunakan Naïve Bayes Classifier Andriyani, Dwi Ratna; Afdal, M; Monalisa, Siti
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3541

Abstract

The removal of honorees is currently a hot topic throughout Indonesia. Sharing how honorary personnel do so that the honorary removal policy is not implemented. Most honorary personnel have served for several years, but the government has issued a circular on the abolition of honorees. Various pros and cons of society regarding the abolition of honorees, such as honorary workers can lose their jobs, not get income, and unemployment is increasing. The purpose of the study is that the government can provide strategies that must be carried out in the event of the removal of honorees, such as appointing all honorees to become Civil Servants or Government Employees with Work Agreements. So the removal of the honoree became one of the trending topics on Twitter social media in 2022. From the results of the analysis conducted, public opinion that uses Twitter is very influential for honorary workers by grouping opinions into three categories, namely positive opinions, neutral opinions, and negative opinions. So the study with text mining used the Naïve Bayes Classifier algorithm with data from Twitter tweets from January 2022 to December 2022 with 2,705 data. The results of this study obtained accuracy with 10 K-fold Cross Validation on K-10, which was 73.01%. And it was found that sentiment polarity against the removal of honorees on positive class sentiment by 10% against agreeing to remove honorees with 285 data tweets, neutral class sentiment by 67% against agreeing and disagreeing with the removal of honorees with 1,801 data tweets, and negative class sentiment by 23% against disagreeing with the removal of honorees with 619 data tweets
Penerapan Algoritma FP-Growth untuk Menentukan Strategi Promosi Berdasarkan Waktu dan Pembelian Produk Wilrose, Anandeanivha; Afdal, M; Monalisa, Siti; Munzir, Medyantiwi Rahmawita
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3577

Abstract

Sales is the main activity in every business. In making business decisions, sales patterns can be used to provide useful information such as strategies for promotion. Wandri Mart is a business engaged in the sale of products or goods commonly referred to as minimarkets in the city of Payakumbuh. In conducting promotional strategies, the owner of Wandri Mart does not know when to do promotions and what promotions are needed in order to increase sales. The purpose of this study is to obtain purchasing patterns related to the time of purchase and the type of goods purchased, so that a more effective promotional strategy can be developed. The method used by researchers is data mining techniques with the FP-Growth algorithm. The data used was taken as much as 5471 sales transaction data for 1 year. The results of this study indicate that the FP-Growth algorithm can be used to determine association rules using a minimum support of 1%, 2%, 3% and a minimum confidence of 10%. Experiments using Minimum Support 1% and Minimum Confidence 10% have the highest lift ratio value and produce more rules compared to other experiments so that it is obtained if on Tuesdays in August, customers buy instant noodles and packaged drinks with 6% and 5% support respectively and 50% and 45% confidence respectively with a lift ratio of 1.75 and 1.59 respectively. The lift ratio means that the rules have high association accuracy, and this also has a positive impact on sales and can be used as useful information for Wandri Mart to increase sales
Co-Authors - Mardalena, - A. Adriani AA Sudharmawan, AA Addion Nizori ADRIANI ADRIANI Adriani Adriani Afandi, Rival Aini, Delvi Nur Al-Yasir, Al-Yasir Alfakhri, Rezky Alfian, Zhevin Andaranti, Arifah Fadhila Andriyani, Dwi Ratna Angraini Angraini Anisa Putri Annisa Ramadhani Anofrizen Anofrizen Arif Marsal Arrazak, Fadlan Auliani, Sephia Nazwa Ayu Lestari Silaban Ayu Silaban Azzahra, Aura Basri, Faishal Khairi Darlis Darlis Darlis Darlis, Darlis Eki Saputra F. Safiesza, Qhairani Frilla Fauzan Ramadhan Febi Nur Salisah Filawati Filawati FITRY TAFZI Hendri, Desvita Heni Suryani Husaini, Fahri Husna, Nur Alfa Indah Lestari, Indah Indriyani Indriyani Indriyani Inggih Permana Intan, Sofia Fulvi Irwanda, Mahyuda Jazman, Muhammad Kusuma, Gathot Hanyokro Lisani Lisna, Lisna Loka, Septi Kenia Pita Luber, Yusuf Amirullah Mawaddah, Zuriatul Megawati - Miftahul Jannah Mochammad Imron Awalludin Mona Fronita, Mona Muhammad Ambar Islahuddin Munandar, Darwin Munzir, Medyantiwi Rahmawita Mustakim Mustakim Mustakim Mutia, Risma Muttakin, Fitriani Nabillah, Putri Nasution, Nur Shabrina Nelwida Nelwida Nurfadilla, Nadia Nurkholis Nurkholis Pertiwi, Tata Ayunita Priady, Muhamad Ilham Prizky Nanda Mawaddah Putra, Moh Azlan Shah Putri, Celine Mutiara Putri, Suci Maharani Rahmah, Astriana Rahmawita, Medyantiwi Ramadani, Faradila Ramadhani, Indah Rayean, Rival Valentino Remon Lapisa Rice Novita Rozanda, Nesdi Evrilyan Saad, Wan Zuhainis Sabillah, Dian Ayu Saitul Fakhri Sari, Gusmelia Puspita Sarwo Edy Wibowo Siti Monalisa Siti Rohimah Suhessy Syarif Suhessy Syarif, Suhessy Suryadi Suryadi Suryadi Suryadi Suryani, Heni Susanti, Pingki Muliya Suseno, Rahayu Syafi'i, Azis Syafrizal Syafrizal Syahri, Alfi Syaifullah Syaifullah T. T. Poy Teja Kaswari Tri Astuti Triningsih, Elsa Tshamaroh, Muthia Ula, Walid Alma Wibisono, Yudistira Arya Wilrose, Anandeanivha Winnugroho Wiratman, Manfaluthy Hakim, Tiara Aninditha, Aru W. Sudoyo, Joedo Prihartono Y Zaharanova Yuda, Afi Ghufran Yulianti, Nelvi Yun Alwi Yurleni Yurleni Yusuf Amirullah Luber Zarnelly Zarnelly Zarqani, Zarqani