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All Journal DE JURE Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal al-Ulum : Jurnal Pemikiran dan penelitian ke-Islaman HIKMAH : JURNAL PENDIDIKAN AGAMA ISLAM Building of Informatics, Technology and Science Jurnal Penelitian Pembelajaran Matematika Sekolah Prosiding Seminar Nasional Teknik Mesin Indonesian Journal of Electrical Engineering and Computer Science Jurnal Mekanik Terapan Movere Journal Jurnal Teknologi Informasi Jurnal Manajemen Sistem Informasi Buletin Pengabdian JURNAL PENGABDIAN PEMBANGUNAN PERTANIAN DAN LINGKUNGAN (JP3L) ABDIMU: Jurnal Pengabdian Muhammadiyah
Fachruddin Fachruddin
Pascasarjana Program Studi Teknik Sipil dan Lingkungan, Fakultas Teknologi Pertanian, SPs Institut Pertanian Bogor.
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Eksperimen Layer Pooling menggunakan Standar Deviasi untuk Klasifikasi Dataset Citra Wajah dengan Metode CNN Pratama, Yovi; Rasywir, Errissya; Fachruddin, Fachruddin; Kisbianty, Desi; Irawan, Beni
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.v5i1.3604

Abstract

Deep Learning, especially the Convolutional Neural Network (CNN) has proven to be reliable in processing data from various programming language platforms by utilizing deep learning. In this study, we modified it by calculating the statistical variance. The modifications made are replacing calculations on the Pooling Layer which generally use two formulas, namely max pooling and average pooling. We use the standard deviation to change the reduced image intensity value. With the research experiments built, it is expected to be able to perform facial recognition as an indicator for testing modifications. The Layer Pooling experiment uses the Standard Deviation for Classifying Face Image Datasets with the CNN Method, including the type of dataset used is the Aberdeen dataset https://pics.stir.ac.uk/2D_face_sets.htm. From the results of the experiments conducted, it was found that the highest value was using the Elu activation function and the Adagrad optimizer worth 77.844% for max pooling and 79.844% for pooling with a standard deviation. The Cellu activation function and the RMSprop optimizer are 77.986% for max pooling and 75.986% for pooling with a standard deviation. The highest score with the Softplus activation function and the Sgd optimizer is 77.844% for max pooling usage and 76.344% for pooling with standard deviation. The Tanh activation function and the Adadelta optimizer are 87.844% for max pooling and 85.844% for pooling with a standard deviation. The Elu activation function and the Adam optimizer are 87.853% for the use of max pooling and 85.285% for pooling with a standard deviation. By using the Elu activation function and the Adamax optimizer, the value is 87.842% for max pooling and 86.242% for pooling with a standard deviation. The highest score is using the Elu activation function and the Nadam optimizer with a value of 87.845% for max pooling usage and 86.345% for using standard deviation calculations as pixel pooling. From all experiments it was stated that the use of pooling with the highest value technique or max pooling still gave a better value than using the standard deviation calculation with the best tuning results using the Elu activation function and Adam's Optimiser, which was 87.853%.
SEKULERISME DAN PEDANGKALAN AGAMA Fachruddin, Fachruddin; Rizal, Samsul; Sirait, Robin; Salim, Agus; Arbeni, Wawan
HIKMAH: JURNAL PENDIDIKAN AGAMA ISLAM Vol 12, No 1 (2023)
Publisher : STAI Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55403/hikmah.v12i1.463

Abstract

Experimental of information gain and AdaBoost feature for machine learning classifier in media social data Jasmir, Jasmir; Abidin, Dodo Zaenal; Fachruddin, Fachruddin; Riyadi, Willy
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 2: November 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i2.pp1172-1181

Abstract

In this research, we use several machine learning methods and feature selection to process social media data, namely restaurant reviews. The selection feature used is a combination of information gain (IG) and adaptive boosting (AdaBoost) which is used to see its effect on the classification performance evaluation value of machine learning methods such as Naïve Bayes (NB), K-nearest neighbor (KNN), and random forest (RF) which is the aim of this research. NB is very simple and efficient and very sensitive to feature selection. Meanwhile, KNN is known for its weaknesses such as biased k values, overly complex computation, memory limitations, and ignoring irrelevant attributes. Then RF has weaknesses, including that the evaluation value can change significantly with only small data changes. In text classification, feature selection can improve the scalability, efficiency and accuracy of text classification. Based on tests that have been carried out on several machine learning methods and a combination of the two selection features, it was found that the best classifier is the RF algorithm. RF produces a significant increase in value after using the IG and AdaBoost features. Increased accuracy by 10%, precision by 12.43%, recall by 8.14% and F1-score by 10.37%. RF also produces even accuracy, precision, recall, and F1-score values after using IG and AdaBoost with an accuracy value of 84.5%; precision of 85.58%; recall was 86.36%; and F1-score was 85.97%.
UPAYA MENINGKATKAN HASIL BELAJAR DAN KEMAMPUAN PEMAHAMAN KONSEP MELALUI MODEL KOOPERATIF LEARNING TIPE THINK PAIR SHARE (TPS) DALAM PEMBELAJARAN MATEMATIKA SISWA KELAS VII SMP N 11 KOTA BENGKULU NOVIANITA, LIZZA; Susanta, Agus; fachruddin, fachruddin
JP2MS Vol 2 No 2 (2018): Agustus
Publisher : Program Studi S1 Pendidikan Matematika FKIP Universitas Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jp2ms.2.2.152-156

Abstract

This research is classroom action research (PTK) with data collection technique through activity observation sheet and test result of student learning. The subjects of this study are the students of class VII A SMP Negeri 11 Kota Bengkulu Odd Semester of the School Year 2017 which amounted to 32 students. The results showed that the implementation of learning strategy through cooperative model of learning type Think Pair Share (TPS) can increase student learning activity and learning outcomes. The increase of student learning activity can be seen from the value of observation of student learning activity of mathematics cycle I that is 19,67 (criteria enough), cycle II is 23,17 (good criterion), cycle III 26,17 (good criterion). Improvement of students' mathematics learning outcomes can be seen from the average score of student learning outcomes cycle I is 67.40; cycle II is 75,47; and cycle III has increase that is 82,34 and completeness of classical learning cycle I, cycle II, cycle III in sequence is 44%, 50%, and 81,25%. Keywords: Activities, Learning Outcomes, cooperative learning type Think Pair Share (TPS).
TECHNICAL GUIDANCE FOR IMPROVING THE USE AND UTILIZATION OF DRONE DATA IN WEST ACEH LAND AGENCY Alvisyahri, Alvisyahri; Idris, Fadli; Fachruddin, Fachruddin; Rahman, Aulia; Malia, Rezqi; Dinda, Raina Parmitalia
ABDIMU: Jurnal Pengabdian Muhammadiyah Vol 3, No 2 (2023)
Publisher : Universitas Muhammadiyah Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37598/abdimu.v3i2.1828

Abstract

Drones are advanced technology that can help humans in transportation because they can see almost everything and save human energy. In fact, in some cases, they may not disrupt traffic like regular vehicles. The Technical Guidance Activity to Increase Capacity in the Use and Utilization of Drone Data (UHV/Unmanned Aerial Vehicle) is intended to provide West Aceh District Land Service officials with insight and knowledge about the use and utilization of drone data. The purpose of this service is to provide an introduction and insight to West Aceh District Land Service officials regarding the use and utilization of drone data (UHV/Unmanned Aerial Vehicle) as well as providing direction and knowledge about the steps for implementing the use and utilization of drone data. The Technical Guidance Activity for Increasing the Capacity of Use and Utilization of Drone Data (UHV/Unmanned Aerial Vehicle) for West Aceh Regency Land Service officials is an activity held by the USK Forestry Research Center in collaboration with Teuku Umar University on Wednesday 15 February 2023 from at 08.30 until finished. The theme of the material provided is Mapping Using Drones and its application in making contour maps with the help of GIS applications. The method used is a presentation. With this technical guidance regarding the Use and Utilization of Drone Data (UHV/Unmanned Aerial Vehicle), participants understand the ease of processing map data, especially those related to land mapping.  Keyword : Drone, UHV/Unmanned Aerial Vehicle, Mapping
COMPARATIVE STUDY OF RELIGIOUS MODERATION BETWEEN THE YOUNGER GENERATION AND THE OLDER GENERATION Fachruddin, Fachruddin; Yusuf, Ahmad Maulana
Jurnal Al-Ulum : Jurnal Pemikiran dan Penelitian Ke-Islaman Vol 12 No 2 (2025): al-Ulum: Jurnal Pendidikan, Penelitian dan Pemikiran Keislaman
Publisher : Universitas Islam Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31102/alulum.12.2.2025.116-126

Abstract

Religious moderation between the younger and older generations shows that both have unique characteristics and challenges. The younger generation, with an innovative spirit and access to information, can become agents of change that encourage tolerance and understanding between religious communities. Meanwhile, the older generation has experience and wisdom that are important to be used as a basis in efforts to strengthen religious moderation, the spirit of religious moderation to find common ground in religion. The method of this research is qualitative, data collection is interview, observation, and documentation. Seber data is the older generation and the younger generation to find and search for definitions related to research phenomena. The analysis technique used is the Descriptive Analysis technique. The results of the study show that the comparison shows that there are differences in religious moderation attitudes between generations. The younger generation is more inclusive, tolerant, and open to differences, which is largely influenced by interfaith interactions on social media. In contrast, older generations tend to maintain more conservative views, both from a religious perspective and the needs of life. The implication of this research is to understand the differences in mindsets and approaches to religious moderation between generations, so that it can be the basis for cross-generational dialogue programs to strengthen social harmony, Religious education in schools and religious institutions can adjust teaching methods to be more relevant to the needs of each generation.
Education and vulnerability strategies of coffee farmers in facing the climate change in Kekuyang Village, Aceh Tengah District [Edukasi dan strategi kerentanan petani kopi dalam menghadapi perubahan iklim di Gampong Kekuyang Kabupaten Aceh Tengah] Fachruddin, Fachruddin; Pramulya, Rahmad; Ariska, Nana; Aulia, Muhammad Reza; Dahlan, Dahlan
Buletin Pengabdian Bulletin of Community Services Vol 5, No 1 (2025): Bull. Community. Serv.
Publisher : The Institute for Research and Community Services (LPPM) Universitas Syiah Kuala (USK)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/bulpen.v5i1.43003

Abstract

Upas fungal disease on coffee plants is a threat that causes young plants to die. Poor access to infrastructure, especially roads to coffee farms for women farmers, as well as a lack of training on Good Agricultural Practices (GAP) and coffee agritourism, are also significant obstacles to the economic development of coffee farmers. In addition, population growth and new land clearing in unauthorized areas further worsen environmental and coffee land conditions in Kekuyang Village. This service aims to educate and strategize the vulnerability of coffee farmers in facing climate change in Kekuyang Village, Aceh Tengah District. The coffee farmer vulnerability education program has been implemented successfully through Focus group discussion (FGD). The team delivered educational materials focused on the application of adaptation strategies with a multidimensional approach. In the human aspect, training and raising awareness of sustainable agricultural practices are required. In the social dimension, strengthening community networks and cooperation with various parties is very important. Meanwhile, in the environmental aspect, crop diversification and the use of coffee varieties that are more resistant to climate change can help minimize risks. From a financial perspective, better access to insurance and value-enhancing products is a priority. In addition, improvements to agricultural infrastructure and the application of environmentally friendly technologies are key strategies to deal with the challenges of climate change in an integrated manner.
Increasing the Accuracy of Brain Stroke Classification using Random Forest Algorithm with Mutual Information Feature Selection Fachruddin, Fachruddin; Rasywir , Errissya; Pratama, Yovi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 4 (2024): August 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i4.5795

Abstract

Brain stroke stands out as a leading cause of death, distinguishing it from common illnesses and highlighting the critical need to utilize machine learning techniques to identify symptoms. Among these techniques, the Random Forest (RF) algorithm emerged as the main candidate because of its optimal accuracy values. RF was chosen for its ensemble learning properties that optimize accuracy while simultaneously, bagging all outputs (DT), thus increasing its efficacy. Feature Selection, an important data analysis step, which is mainly achieved through pre-processing, aims to identify influential features and ignore less impactful features. Mutual Information serves as an important feature selection method. Specifically, the highest level of accuracy was achieved by cross-validating the test data - 10, resulting in 0.7760 without feature selection and 0.7790 with mutual information. Most of the attributes in the brain stroke dataset show relevance to the stroke disease class, but the resulting decision tree shows age as a particularly important node. So, the research results show that the selection feature (Mutual Information) can increase the accuracy of brain stroke classification, although it is not significant, namely an increase of 0.0030%. With an increase, where there is no significant difference, it can be said that almost all the attributes contained in the brain stroke dataset used have an influence on their relevance to the stroke disease class.
Pengembangan Modul Penilaian Usulan Hibah Internal Pada Sistem Informasi Penelitian dan Pengabdian Kepada Masyarakat Politeknik Negeri Sambas Usman, Muhammad; Astuti, Theresia Widji; Fathushahib, Fathushahib; Sanusi, Sanusi; Fachruddin, Fachruddin
Jurnal Teknologi Informasi Vol 4, No 1 (2025): Mei
Publisher : Universitas Teuku Umar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35308/jti.v4i1.11932

Abstract

Politeknik Negeri Sambas saat ini telah mengembangkan sistem informasi manajemen penelitian dan pengabdian masyarakat, namun sistem tersebut masih memiliki beberapa keterbatasan fungsional. Beberapa masalah utama yang teridentifikasi adalah belum adanya mekanisme pembobotan nilai oleh reviewer dalam proses evaluasi proposal, laporan kemajuan, dan laporan akhir penelitian, dan keterbatasan integrasi data antar modul kegiatan penelitian dan Pengabdian kepada Masyarakat (PKM). Untuk mengatasi masalah tersebut, dilakukan optimalisasi sistem melalui pengembangan modul penilaian berbobot dengan kriteria terstandar yang terintegrasi database, Implementasi fitur otomatisasi surat tugas, dan peningkatan kemampuan webserver dan database untuk mendukung operasi multiplatform. Teknologi Laravel dipilih sebagai framework pengembangan utama untuk meningkatkan reusability code dan memastikan kompatibilitas antar platform. Solusi ini diharapkan mampu menyederhanakan proses evaluasi proposal serta monitoring hasil penelitian dan pengabdian kepada masyarakat melalui sistem pembobotan terstruktur dan penilaian yang objektif, sekaligus meningkatkan efisiensi administrasi penelitian lewat otomatisasi dokumen.  Hasil akhir dari sistem ini adalah reviewer dapat melakukan penilaian proposal yang diajukan oleh pengusul dosen yang selanjutnya berfungsi sebagai data bagi P3M Poltesa dalam menentukan usulan proposal mana yang diberikan pendanaan sesuai dengan skema yang ada.
Pelatihan Pemanfaatan Teknologi Mesin Kompos Kepada Petani di Kecamatan Seulimum, Kabupaten Aceh Besar Mustaqimah, Mustaqimah; Nurba, Diswandi; Yasar, Muhammad; Bulan, Ramayanty; Devianti, Devianti; Fachruddin, Fachruddin; Yusra, Andi
JURNAL PENGABDIAN PEMBANGUNAN PERTANIAN DAN LINGKUNGAN (JP3L) Vol 2 No 2 (2025): JURNAL PENGABDIAN PEMBANGUNAN PERTANIAN DAN LINGKUNGAN (JP3L): Volume 2 Nomor 2,
Publisher : LEMBAGA KAJIAN PEMBANGUNAN PERTANIAN DAN LINGKUNGAN (LKPPL)

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

Abstract

Pelatihan pemanfaatan teknologi mesin kompos dan pengolahan limbah organik telah sukses diselenggarakan di Kecamatan Seulimum, Kabupaten Aceh Besar. Kegiatan ini merupakan bagian dari upaya pemberdayaan masyarakat tani melalui pendekatan edukatif dan praktis dalam bidang pertanian berkelanjutan. Tujuan utama dari pelatihan ini adalah untuk meningkatkan kapasitas petani dalam memproduksi pupuk organik secara mandiri dengan memanfaatkan limbah organik lokal, seperti sisa dapur, dedaunan, dan kotoran ternak. Dengan adanya pelatihan ini, para peserta tidak hanya mendapatkan pengetahuan teoritis mengenai prinsip dasar pengomposan, tetapi juga keterampilan teknis dalam mengoperasikan mesin pencacah kompos dan memahami tahapan pengolahan hingga menghasilkan pupuk matang yang siap digunakan. Selain mendukung peningkatan produktivitas hasil pertanian, penggunaan pupuk kompos ini turut berkontribusi terhadap efisiensi biaya produksi, karena mampu mengurangi ketergantungan petani terhadap pupuk kimia yang mahal dan tidak ramah lingkungan. Dari sisi lingkungan, praktik pengomposan ini menjadi solusi dalam mengelola limbah organik agar tidak mencemari tanah dan air. Meskipun demikian, pelaksanaan pelatihan ini juga mengungkap sejumlah tantangan, seperti keterbatasan alat produksi dan perlunya pendampingan lanjutan. Artikel ini membahas capaian kegiatan pelatihan, kendala adopsi teknologi di lapangan, serta potensi keberlanjutan program pelatihan di tingkat komunitas secara jangka panjang.
Co-Authors AA Sudharmawan, AA Abadi, Cecep Slamet Abidin, Dodo Zaenal Adi Syuriadi Aldri Frinaldi Alkhayr, Sabila Mujahidah Alvisyahri, Alvisyahri Arbeni, Wawan Ariska, Nana Astuti, Theresia Widji Aulia Rahman Auliya, Nurul Azwardi Azwardi Belyamin Belyamin Beni Irawan Bulan, Ramayanty Candra Damis Widiawaty, Candra Damis Dahlan Dahlan Desi Kisbianty, Desi Devianti, Devianti Diswandi Nurba, Diswandi Errissya Rasywir Fahrijal, Farkhan fathushahib, fathushahib Februssi, Aditya Handriyani, Cut Hibatullah, Iqmal Idris, Fadli Jasmir, Jasmir Kusumawati, Andi Malia, Rezqi Muhammad Ardiansyah Muhammad Hidayat Tullah, Muhammad Hidayat Muhammad Ismail Muhammad Riza Pahlevi Muhammad Usman, Muhammad Muhammad Yasar Mustaqimah Mustaqimah Novianita, Lizza Nuraini, Assyifah Nurfitriani, Antie Pramulya, Rahmad Putra, Nobby Darly Dwi Rahman, Farhan Maulana Raina Parmitalia Dinda Rasywir , Errissya Rizki, Gebrina Robin Sirait Sanusi Sanusi Smarajaya, I Dewa Made Suharmanto, Billy Susanta, Agus Syamsuddin Syamsuddin Utama, Melda Utari, Selfia Dela Utomo, Machfud Priyo WILLY RIYADI Yovi Pratama Yuli Mafendro Dedet Eka Saputra Yusra, Andi yusuf, Ahmad Maulana Zainuddin, Zainuddin