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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal Informatika dan Teknik Elektro Terapan Panrita Abdi - Jurnal Pengabdian pada Masyarakat JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information Technology and Computer Science (JOINTECS) Jurnal Ilmiah FIFO Equilibrium: Jurnal Ilmiah Ekonomi, Manajemen dan Akuntansi JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI ILKOM Jurnal Ilmiah Jiko (Jurnal Informatika dan komputer) Conference on Innovation and Application of Science and Technology (CIASTECH) JOURNAL OF SCIENCE AND APPLIED ENGINEERING Jurnal Abdimas Mahakam Applied Technology and Computing Science Journal Jurnal Aplikasi Dan Inovasi Ipteks SOLIDITAS Systematics Buana Information Technology and Computer Sciences (BIT and CS) Jurnal Mnemonic JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Pengabdian Masyarakat Multidisiplin Journal of Applied Data Sciences Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) International Conference on Industrial Revolution for Polytechnic Education International Journal of Community Service (IJCS) Prosidia Widya Saintek
Aviv Yuniar Rahman
Universitas Widyagama Malang
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APLIKASI ALAT PABRIK MINI KASCING UNTUK KELOMPOK PEMANFAATAN LIMBAH ORGANIK Aviv Yuniar Rahman; Feddy Wanditya Setiawan; April Lia Hananto
Panrita Abdi - Jurnal Pengabdian pada Masyarakat Vol. 7 No. 2 (2023): Jurnal Panrita Abdi - April 2023
Publisher : LP2M Universitas Hasanuddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/pa.v7i2.18521

Abstract

A mini vermicompost fertilizer factory that can produce vermicompost and worm fertilizers independently will be distributed to the organic waste utilization group. This mini vermicompost factory tool is made so that members of the organic waste utilization group can harvest fresh vermicompost and worm fertilizers. The benefits of making this tool are reducing organic waste in the group environment, improving group members' economy, and harvesting vermicompost and fresh worms. In its application to the community, it uses the method of identifying needs, making tool designs, making tool realizations, testing or demonstrations of tools, and training and assistance on procedures for using mini vermicompost fertilizer plants. The result of this activity is that members of the organic waste utilization group can independently harvest fresh vermicompost and worm fertilizers. This significantly increases the quantity of fresh vermicompost and worm fertilizer products. This activity positively impacts the environment and the community's economy by reducing organic waste and increasing the income of group members, indirectly improving rural communities' economies.  ---  Alat pabrik mini pupuk kascing yang dapat memproduksi pupuk kascing dan cacing secara mandiri yang akan disebar ke kelompok pemanfaatan limbah organik. Alat pabrik mini kascing ini dibuat agar masyarakat yang tergabung dalam kelompok pemanfaatan limbah organik dapat panen pupuk kascing dan cacing segar. Manfaat dalam membuat alat ini yaitu untuk mengurangi limbah organik dilingkungan kelompok, meningkatkan ekonomi anggota kelompok, panen pupuk kascing dan cacing segar. Dalam penerapan kepada masyarakat ini menggunakan metode Identifikasi kebutuhan, membuat desain alat, membuat realisasi alat, uji coba atau demonstrasi alat dan Pelatihan dan Pendampingan Tatacara Pemakaian Alat Pabrik Mini Pupuk Kascing. Hasil dari kegiatan ini adalah anggota kelompok pemanfaatan limbah organik mampu memanen pupuk kascing dan cacing segar secara mandiri. Hal ini menambah kuantitas produk pupuk kascing dan cacing segar secara signifikan. Kegiatan ini memberikan dampak positif bagi lingkungan dan perekonomian masyarakat, yaitu mengurangi limbah organik dan meningkatkan pendapatan anggota kelompok yang secara tidak langsung juga meningkatkan perekonomian masyarakat desa.
SEGMENTASI CITRA BURUNG LOVEBIRD MENGGUNAKAN K-MEANS Hero Diogenes Adoe; Aviv Yuniar Rahman; Istiadi Istiadi
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 10 No 1 (2023): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v10i1.3452

Abstract

Knowledge of the types of lovebirds is needed by lovebird lovers. The dominant color segmentation can provide information about the types of lovebirds. So the purpose of this research is to build a lovebird segmentation system using the K-means method. The research method used is image processing method. To carry out the segmentation process of the original image compared to the compressed image. Data collection is carried out by utilizing primary data in the form of pictures of lovebird birds which will later be processed using k means. Matlab is used to build a k means segmentation system. The data analysis stage in this study uses steps, data selection, preprocessing and data cleaning, data transformation, data mining, and evaluation/interpretation. The results of the study provide information that by using K-Means, the segmentation of lovebirds based on color can be detected. In this study, the lovebird image segmentation program using Matlab to extract RGB space to Greyscaled showed a higher accuracy rate of 96.26% than segmentation using manual methods, namely 85.19%.
PENINGKATAN MANAJEMEN KEUANGAN DAN PEMASARAN PADA UKM UBI JALAR BERBASIS WEB Aviv Yuniar Rahman; Chauliah Fatma Putri; Adya Hermawati
Jurnal Pengabdian Masyarakat Multidisiplin Vol 6 No 3 (2023): Juni
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/jpm.v6i3.3115

Abstract

Usaha Kecil menengah di Indonesia masih banyak yang harus di tingkatkan untuk memudahkan sebuah pekerjaan dalam setiap bidangnya. Salah satunya yaitu pada bidang manajemen keuangan dan pemasaran. Kali ini, banyak UKM di Indonesia masih banyak menggunakan sistem pemasaran dan keuangan yang bersifat manual. Sistem ini dikatakan manual, karena masih menggunakan cara-cara tradisional seperti menghitung keuangan manual, proses pemasaran yang harus menggunakan sistem face to face. Dalam hal ini tim pengabdi menguraikan permasalahan tersebut untuk meningkatkan sistem pemasaran dan keuangan pada UKM Ubi Jalar. Karena banyak di tempat tersebut masih menggunakan sistem manual yang nantinya akan di ganti menjadi sistem berbasis website. Hasil dalam konsep manajemen keuangan mitra sebelumnya benar 75% telah meningkat sebanyak 90%. Kemudian dari yang salah pada konsep manajemen keuangan dari yang sebelumnya 25% menjadi 10%. Hal ini terjadi peningkatan pada pengetahuan mitra tentang konsep manajemen keuangan. Selanjutnya yaitu tujuan manajemen, sebelumnya mitra bisa menjawab benar dengan tingkat 70% menjadi 100%. Kemudian mitra menjawab salah dari yang sebelumnya 30% terjadi penurunan menjadi 0%. Peningkatan mitra pada pengetahuan tujuan manajemen keuangan ini terbilang sangat tinggi karena telah mencapai 100%. Hasil dalam pentingnya manajemen pemasaran dari sebelumnya mitra menjawab benar 85% menjadi benar 100%. Kemudian dari hasil yang salah sebelumnya `15% menjadi salah 0%. Hal ini terjadi peningkatan, karena mitra mengetahui pentingnya manajemen pemasaran. Kemudian dalam menentukan target pasar, sebelumnya mitra menjawab benar sebesar 70%, menjadi 100%. Dan hasil salah sebelumnya 30% menjadi 0%. Peningkatan dalam menentukan target pasar ini meningkat dalam pengetahuan mitra UKM Ubi Jalar.
Image Classification of Tempe Fermentation Maturity Using Naïve Bayes Based on Linear Discriminant Analysis Dio Amin Putra; Istiadi Istiadi; Aviv Yuniar Rahman
JOURNAL OF SCIENCE AND APPLIED ENGINEERING Vol 6, No 1 (2023): JSAE
Publisher : Widyagama University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31328/jsae.v6i1.4655

Abstract

One of the foods in Indonesia that has a lot of nutritional content and benefits, one of which is tempeh. Tempe is usually made by fermenting soybeans with mold under special conditions to become tempeh. In the fermentation process, tempeh producers need to monitor the maturity of the tempeh until it is suitable for consumption. To detect this maturity requires a separate effort, so that an image processing approach is proposed in this study with the support of feature selection. An image allows for various features to be taken, such as texture features using GLCM and various color features including RGB, HSV, LAB, CMYK, YUV, HCL, HIS, LCH. With so many features, it is necessary to do a selection so that computation in its classification becomes efficient. This study aims to classify tempeh fermented images using the Naive Bayes method with Linear Discriminant Analysis (LDA)feature selection for GLCM features and eight color features. Tempe fermentation image is divided into three classes, namely raw, ripe and rotten. Based on the experimental results, the average accuracy in the test is 84.06%. In testing the fastest time is 1.87 seconds and the longest is 2.20 seconds. This shows that the classification of fermented tempeh maturity with Naive Bayes with LDA feature selection can work well.
Klasifikasi Citra Burung Jalak Menggunakan Artificial Neural Network dan Random Forest Aviv Yuniar Rahman
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 8, No 2 (2022): Volume 8 No 2
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v8i2.53480

Abstract

Klasifikasi Citra Burung Jalak Menggunakan Fitur ekstraksi GLCM dan Artificial Neural Network sebelumnya sudah pernah diteliti. Hasil dalam penelitian tersebut menunjukkan tingkat akurasi dalam klasifikasi jenis burung jalak hanya mencapai 49,20% dengan split ratio 50:50.Oleh karena itu, peneliti mengusulkan klasifikasi citra burung jalak menggunakan Artificial Neural Network dan Random Forest. Klasifikasi ini bertujuan untuk meningkatkan hasil akurasi sebelumnya. Hasil dalam pengujian yang dilakukan antara Artificial Neural Network dengan Random Forest bisa disimpulkan bahwa pada fitur Wavelet memiliki hasil yang maksimal pada proses klasifikasi burung jalak. Hasil dalam pengujian dimulai dengan Artificial Neural Network memiliki nilai tertinggi pada precision mencapai 0.986, recall 0.987, f-measure sebesar 0.988 dan accuracy sebesar 89% pada split ratio 50:50. Hasil dari Random Forest memiliki nilai tertinggi pada precision mencapai 1.000, recall mencapai 0.877, f-measure mencapai 0.975 dan accuracy mencapai 100% dengan perbandingan mulai dengan 50:50. Hasil klasifikasi citra burung jalak dari segi matrix confusion menunjukkan bahwa perbandingan data antara 10:90 sampai dengan 90:10 juga sangat berpengaruh dalam proses ketepatan dalam mengklasifikasi. Pengujian yang telah dilakukan telah membuktikan bahwa metode Random Forest dapat memperbaiki kinerja dan hasil pada metode Artificial Neural Network. Serta dalam hal ini menunjukkan Random Forest lebih baik dalam ketepatan dan keakuratan dibandingkan dengan Artificial Neural Network dalam mengklasifikasi jenis burung jalak
Identification of Tempe Fermentation Maturity Using Principal Component Analysis and K-Nearest Neighbor Istiadi, Istiadi; Rahman, Aviv Yuniar; Wisnu, Alif Dio Raka
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i1.12006

Abstract

Tempe is one of the traditional foods in Indonesia which has nutritional content and benefits that are very much favored by all Indonesian people. To determine the maturity of tempe, it is generally done by fermenting it into tempeh using a certain temperature and usually tempe entrepreneurs are done traditionally. But in this way, tempe producers do not know what temperature and humidity are right for tempeh maturity. In this study, researchers used the MATLAB R2018a application with a total data set of 137 raw data, 137 ripe data and 136 rotten data, totaling 410 tempe image data. The purpose of this research is to produce a system that can detect the ripeness of tempe using the KNN (K-Nearest Neighbor) method which is equipped with GLCM texture feature extraction, with extraction of 8 color features, using the PCA (Principal Component Analysis) selection feature. And compare the results with the same method, namely KNN (K-Nearest Neighbor) without using the PCA (Principal Component Analysis) selection feature with the required running time between the two. KNN with PCA selection feature gets an average accuracy value of 80.63% and takes 1.06 seconds. Compared with the same method, namely KNN without using the selection feature, it gets an average accuracy value of 81.67% with a time of 1.18 seconds.
KLASIFIKASI TEKS BERITA BREAKING NEWS DI MANGGARAI MENGGUNAKAN LONG SHORT TERM MEMORY (LSTM) Daiman, Claudia Nila; Yuniar Rahman, Aviv; Nudiyansyah, Firman
Jurnal Mnemonic Vol 7 No 2 (2024): Mnemonic Vol. 7 No. 2
Publisher : Teknik Informatika, Institut Teknologi Nasional malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/mnemonic.v7i2.9939

Abstract

Berita sering kali menyebar dari berbagai sumber, termasuk media sosial dan situs web. Metode LSTM (Long Short Term Memory) yang lebih baik dalam mengolah data temporal dan sekuensial dapat mempercepat pengambilan keputusan terhadap berita terkini di Manggarai. Tujuan dari penelitian ini adalah untuk mengembangkan sistem klasifikasi teks berita terkini menggunakan LSTM dan membuat model yang dapat mengklasifikasikan berita dengan akurasi tinggi ke dalam empat kategori: ekonomi, kecelakaan, politik dan pariwisata. Penelitian ini menggunakan 4000 dataset yang masing-masing kategori terdiri dari 1000 unit data. Data tersebut dibagi menjadi beberapa variasi rasio data latih dan uji: 3600:400, 3200:800, 2400:1600 dan 1600:2400. Model LSTM menunjukkan performa terbaik dengan rasio 3600:400, presisi 88,75%, presisi 88,79%, recall 88,75%, dan skor F1 88,76%. Akurasi menunjukkan persentase prediksi yang benar, precision mengukur ketepatan prediksi positif, recall menghitung seberapa baik model menangkap semua contoh positif, dan F1-score merupakan rata-rata harmonis dari precision dan recall. Hasil tersebut menunjukkan bahwa model LSTM dapat mengklasifikasikan teks berita secara efisien dan akurat. Penelitian ini memvalidasi penerapan LSTM dalam klasifikasi teks berita untuk memberikan informasi penting dan cepat kepada masyarakat Manggarai
Intelligent classification and performance prediction of multi-text assessment with recurrent neural networks-long short-term memory Paryono, Tukino; Sediyono, Eko; Hendry, Hendry; Huda, Baenil; Lia Hananto, April; Yuniar Rahman, Aviv
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp3350-3363

Abstract

The assessment document at the time of study program accreditation shows performance achievements that will have an impact on the development of the study program in the future. The description in the assessment document contains unstructured data, making it difficult to identify target indicators. Apart from that, the number of Indonesian-based assessment documents is quite large, and there has been no research on these assessment documents. Therefore, this research aims to classify and predict target indicator categories into 4 categories: deficient, enough, good, and very. Learning testing of the Indonesian language assessment sentence classification model using recurrent neural networks-long short-term memory (RNN-LSTM) using 5 layers and 3 parameters produces performance with an accuracy value of 94.24% and a loss of 10%. In the evaluation with the Adamax optimizer, it had a high level of accuracy, namely 79%, followed by stochastic gradient descent (SGD) of 78%. For the Adam optimizer, Adadelta, and root mean squared propagation (RMSProp) have an accuracy rate of 77%.
Implementation of Batik Dyeing Tools to Increase the Productivity of the Coloring Process in Batik SMEs Putri, Chauliah Fatma; Aviv Yuniar Rahman
IJCS: International Journal of Community Service Vol. 2 No. 1 (2023): IJCS: International Journal of Community Service
Publisher : PT Inovasi Pratama Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55299/ijcs.v2i1.395

Abstract

Batik as a work of cultural art in Indonesia is a work that is also attractive for tourist cities such as Malang City. Batik SMEs in Malang City develop batik typical of the region while maintaining traditional manufacturing methods.  UKM Batik Tulis Poesaka Djagad, located in Blimbing Village, Balearjosari Subdistrict, Malang City, is a Batik UKM that is productive in making batik typical of Malang. In the process of strengthening batik colors, it takes a long time for the color strengthening solution to be absorbed perfectly so that it is less effective. The purpose of this community service activity is to apply a color reinforcement tool to UKM Batik Tulis Poesaka Djagad in the hope of speeding up the coloring process so as to increase the productivity of written batik. The stages of this activity include preparation and planning, implementation, monitoring and evaluation. The implementation of training activities on the use of batik coloring process tools involved the owner, the SME batik craftsmen themselves and several other SME batik craftsmen. The results of the application of the coloring process tool can increase the productivity of batik cloth output, especially at the batik coloring process stage and coloring results with better quality.
Detection of Diseases and Pests on The Leaves of Sweet Potato Plants sing Yolov4 nisti, Melita; Yuniar Rahman, Aviv; Marisa, Fitri
Buana Information Technology and Computer Sciences (BIT and CS) Vol 5 No 1 (2024): Buana Information Technology and Computer Sciences (BIT and CS)
Publisher : Information System; Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36805/bit-cs.v5i1.6065

Abstract

Sweet potato (Ipomea batats) is a root plant that can live in all weather, in mountainous areas and on the coast.. This plant is one of the important food crops in Indonesia, and makes Indonesia the second largest sweet potato producer after China. However, according to data from the Central Statistics Agency (BPS), sweet potato production in Indonesia in 2018 decreased by 5.63% when compared to production in 2017 which reached 1,914,244 tons (Gultom, 2021). Based on these data, it is important to conduct research on pest and disease detection in plants. Therefore, the author conducted a study related to this problem entitled Detection of Diseases and Pests on the Leaves of Sweet Potato Plants using Yolov4 with the aim of helping educate farmers in recognizing diseases on the leaves of sweet potato plants and how to overcome them. In this study the dataset was sweet potato leaves with a total of 1500 data divided into three classes, namely aspidomorpha, yellow spot and normal leaves with 4000 iterations. The best training results on 1500 data with 75% accuracy. The Yolov4 algorithm produces high accuracy in detecting diseases in the leaves of sweet potato plants.
Co-Authors Adi Saputra, Deni Adya Hermawati Affi Nizar Suksmawati Ahmad Farhan, Ahmad Ahmad Fauzi Anderias Bai Seran April Hananto April Lia Hananto arrozi, lalu muhamad alawi Bagus Setyawan Budiawan, Renaldi Widi Chauliah Fatma Putri Da Costa, Zania Abuk Daiman, Claudia Nila Dio Amin Putra Eko Sediyono Fauzi Ahmad Muda Firman Nurdiansyah Firman Nurdiyansyah Firman Nurdiyansyah Firman Nurdiyansyah, Firman Hananto, Agustia Hendry Hero Diogenes Adoe Huda, Baenil Ilhamsyah Ilhamsyah Indra, Jamaludin Istiadi Istiadi Istiadi Joko Purwanto khusniyatul latifah Luruk, Maria Ovalia Mamba’us Sa’adah Maria Alfanita Bhia, Meisya MARIFANI FITRI ARISA Muhammad Romadloni Putra Muslim, Shinta Nilam Sari Napulun, Kanisius Nasharuddin Mas Neno, Adi nisti, Melita Novalia, Elfina Nudiyansyah, Firman Pahlevi Putra, Rangga Paryono, Tukino Priyandoko Gigih Priyatna, Bayu Putra, Rangga Pahlevi Putra, S.Pd., M.T., Rangga Pahlevi Putra Ratna Hidayati Rukmanta Jayawiguna Sabar Setiawidayat Setiawan, Feddy Wanditya Sidi, Husri Suhada, Karya Syah, Adryan Syahroni Wahyu Iriananda, Syahroni Wahyu Ursaputra Pratama, Lionardi Wisnu, Alif Dio Raka Yuliana Rachmawati