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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL INSTEK (Informatika Sains dan Teknologi) Jiko (Jurnal Informatika dan komputer) Conference on Innovation and Application of Science and Technology (CIASTECH) Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Jurnal Kreativitas PKM Jurnal Abdimas Mahakam Building of Informatics, Technology and Science Progresif: Jurnal Ilmiah Komputer Systematics Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Buana Ilmu Jurnal Tekinkom (Teknik Informasi dan Komputer) JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Jurnal Pendidikan dan Teknologi Indonesia Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Scientific Student Journal for Information, Technology and Science Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Buana Pengabdian Eduvest - Journal of Universal Studies Jurnal Pengabdian Masyarakat Nasional Inovasi Gagasan Abdimas & Kuliah Kerja Nyata
Indra, Jamaludin
Universitas Buana Perjuangan Karawang
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 Engineering Health Professions Law, Crime, Criminology & Criminal Justice Library & Information Science Medicine & Pharmacology Neuroscience Nursing Public Health Social Sciences Other

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Implementasi Teknologi Alat Penetas dan Teropong Otomatis Untuk Meningkatkan Daya Tetas Telur Bebek di UKM Beki Karawang Garno Garno; Suparno Suparno; Asep Jamaludin; Apriade Voutama; Jamaludin Indra
Jurnal Kreativitas Pengabdian Kepada Masyarakat (PKM) Vol 5, No 10 (2022): Volume 5 No 10 Oktober 2022
Publisher : Universitas Malahayati Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33024/jkpm.v5i10.7174

Abstract

ABSTRAK Pengabdian terintegrasi dengan penelitian di bidang peternakan bebek dan teknologi penetasan telur. Kegiatan membantu UKM Beki mengatasi kesulitan penetasan telur bebek menjadi itik. Satu tahun terakhir setiap kali menetaskan telur sejumlah 300 butir telur rata-rata menetas hanya 175 ekor itik atau berhasil hanya 58%. Team pengabdi mengimplementasikan metode dalam mengatasi kesulitan UKM. Pemilihan induk bebek yang berkualitas. Pemberian pakan pada bebek vitamin dan mineral yang cukup. Pengawinan induk yang baik dengan perbandingan maksimal 1 ekor bebek jantan digabung 6-9 ekor bebek betina. Ke dua pemilihan telur yang berkualitas, meneropong telur sebelum ditetaskan. Jika terlihat embrio atau fertile berarti telur ditetaskan, jika tidak berarti infertile, telur tidak ditetaskan. Pengaturan suhu dalam proses pengeraman, alat penetas telur otomatis diset point awal di 360-370C dan pertengahan 370-380C dan mengatur kelembaban ruang bok penetasan. Hasil pengabdian dengan menerapkan metode dapat menetaskan telur bebek mencapai 86,33%. Prosentase penetasan telur itik mengalami kenaikan sebesar 28,33% dari kondisi sebelumnya. Pengabdian kepada masyarakat dalam bentuk pelatihan metode pada UKM Beki penetasan telur bebek dapat meningkatkan jumlah produksi tetas telur menjadi itik. Kata kunci: Teknologi Penetas, Teropong Telur, Fertilitas Telur, Itik, Bebek  ABSTRACT Integrated service with research in the field of duck farming and egg hatching technology. Activities to help UKM Beki overcome the difficulties of hatching duck eggs into ducks. In the last one year, every 300 eggs hatched, on average, only 175 ducks hatched or only 58% succeeded. The service team implements methods in overcoming the difficulties of SMEs. Selection of quality duck mother. Feeding ducks adequate vitamins and minerals. A good parent mating with a maximum ratio of 1 male duck combined with 6-9 female ducks. Second, selecting quality eggs, observing the eggs before they are hatched. If you see an embryo or fertile, it means the egg was hatched, if it doesn't mean it is infertile, the egg is not hatched. Setting the temperature in the incubation process, the egg incubator automatically sets the initial point at 360-370C and mid-370-380C and adjusts the humidity of the hatching bok. The results of service by applying the method to incubate duck eggs reached 86.33%. The percentage of duck eggs hatching increased by 28.33% from the previous condition. Community service in the form of training methods Beki SMEs can increase the amount of egg hatching production to ducks. Keywords: Incubator Technology, Egg Binoculars, Egg Fertility, Ducks, Ducks
Literasi Teknologi untuk Budidaya Jamur Ahmad Fauzi; Jamaludin Indra; April Hananto; Elfina Novalia; Aviv Yuniar Rahman
Jurnal Abdimas Mahakam Vol. 6 No. 02 (2022): Juli
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24903/jam.v6i02.1513

Abstract

Kabupaten Karawang memiliki lahan pertanian yang dapat mendukung budidaya jamur. Pendapatan budidaya jamur yang menjanjikan maka perlu adanya sosialiasi pemanfaatan teknologi. Pengkondisian ruangan budidaya jamur dilakukan menggunakan mikrokontroller dengan pengaturan standar ruangan budidaya jamur. Budidaya jamur befokus pada dua jenis jamur yaitu Jamur Tiram (Pleurotus Ostreatus) dan Jamur Merang yang merupakan salah satu komoditas pertanian yang memiliki nilai gizi sangat baik dan memiliki potensi yang baik untuk dikembangkan. Kegiatan dilakukan dengan penerapan teknologi mikrokontroller dan IoT dalam kumbung jamur untuk budidaya jamur merang. Literasi dilakukan kepada petani melalui sosialisasi penerapan tekologi tersebut sesuai dengan potensi manfaat Industri 4.0 mengenai perbaikan kecepatan fleksibilitas produksi. Peralatan teknologi yang diterapkan terdiri atas sensor dan actuator. Monitoring ruangan dapat terlihat melalui display LED yang menggambarkan kondisi ruang kumbung. Hasil yang diperoleh selama masa tanam 35 hari yaitu warna jamur lebih cerah, ukuran jamur lebih besar dan hasil panen lebih banyak. Kata Kunci: Budidaya jamur, Literasi teknologi, mikrokontroller, IoT, Industri 4.0.
Analisis Sentimen Terhadap Program Kampus Merdeka Menggunakan Naive Bayes Dan Support Vector Machine Irma Putri Rahayu; Ahmad Fauzi; Jamaludin Indra
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 2 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i2.5381

Abstract

In order to prepare students to face the rapid development of technology, changes in work life and skills, students must be better prepared to face the progress of the times. Universities must be able to carry out innovative learning processes so that students achieve optimal learning outcomes which include aspects of knowledge, skills and attitudes. So the MBKM program was launched to answer these demands. However, MBKM has pros and cons in its implementation, so it is necessary to analyze and evaluate policies to improve performance through feedback from the public by conducting sentiment analysis of MBKM policies on twitter users from 2019 to 2022 with the hashtag #kampusmerdeka. This study used the Naïve Bayes and SVM algorithms to determine accuracy based on sentiment classification. The data used 1118 data with positive sentiment 618 data and negative sentiment 500 data. This study resulted in an accuracy of 86%, precision of 87% and recall of 80% with testing data using the Naïve Bayes algorithm. Then using the linear kernel SVM algorithm with the same testing data resulted in accuracy of 93%, precision of 100% and recall of 84%. Therefore, it is important to conduct studies to improve the MBKM program so that its implementation is clearly in accordance with existing procedures.
IMPLEMENTASI ALGORITMA APRIORI TERHADAP MARKET BASKET ANALYSIS PADA DATA PENJUALAN RETAIL Hilda Fitriana Dewi; Hanny Hikmayanti Handayani; Jamaludin Indra
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 4 No 4 (2022): EDISI 14
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (297.796 KB) | DOI: 10.51401/jinteks.v4i4.2182

Abstract

Perusahaan retail berkembang dengan sangat cepat dan memungkinkan ada permasalahan yang sering dihadapi perusahaan, termasuk kurangnya sistem yang mengatasi tata letak produk. Selain itu, terdapat beberapa perusahaan yang belum mengetahui pola pembelian barang konsumen. Masalah lainnya adalah belum adanya sistem penyimpanan yang efisien. Permasalahan tersebut maka dibutuhkan penerapan data mining. Metode yang digunakan menggunakan algoritma apriori. Hasil penelitian ini apabila konsumen membeli item Round Snack Boxes Set Of 4 Fruits, maka konsumen juga membeli Round Snack Boxes Set Of4 Woodland dengan nilai support 13% dan nilai confidence 78%. Apabila konsumen membeli Spaceboy Lunch Box, maka konsumen membeli Round Snack Boxes Set Of4 Woodland dengan nilai support 7% dan nilai confidence 63%. Apabila konsumen membeli Round Snack Boxes Set Of4 Woodland, maka membeli Round Snack Boxes Set Of 4 Fruits dengan nilai support 13% dan nilai confidece 53%. Penjualan yang paling diminati oleh konsumen dari data penjualan retail ini ialah Round Snack Boxes Set Of 4 Fruits, Round Snack Boxes Set Of4 Woodland, dan Spaceboy Lunch Box.
Kajian Model Backpropagation dan Hybrid ANFIS Dalam Memprediksi Pertumbuhan Penduduk di Kabupaten Karawang Tatang Rohana; Jamaludin Indra; Gugy Guztaman Munzi
Journal of Information System Research (JOSH) Vol 4 No 2 (2023): January 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v4i2.2547

Abstract

Population growth rate prediction is a process of estimating the population in the future. Predictions are made so that the government can prepare strategic steps in anticipating the negative impact of an uncontrolled population increase. The research data is the population of Karawang Regency from 2011 to 2020. Backpropagation and Hybrid ANFIS are the models used in this study. The purpose of this study was to determine the RMSE value and scatter data formed from the results of the ANFIS Backpropagation and Hybrid training models in predicting population growth rates in Karawang Regency. In addition, this study is intended to determine the level of accuracy of the two models. The research step begins with research data validation, preprocessing, training and testing, as well as accuracy testing. Accuracy testing uses the Mean Absolute Percentage Error (MAPE) method. Backpropagation and Hybrid models in predicting the rate of population growth have worked well. This can be seen from the training results of the two models. Backpropagation model has the best RMSE of 0.0328 and Hybrid has the best RMSE of 0.021884. The results of the analysis of the accuracy of predicting population growth rates for 2019 and 2020 that have been carried out, both models have a good level of accuracy. Backpropagation has an average accuracy rate of 84.76%, while the Hybrid model has an average accuracy rate of 93.71%. Based on the results of accuracy testing, the Hybrid model has a better level of accuracy than the Backpropagation model.
Penerapan Convolutional Neural Network pada Timbangan Pintar Menggunakan ESP32-CAM Hanung Pangestu Rahman; Jamaludin Indra; Rahmat Rahmat
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 1 (2023): Januari 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i1.5469

Abstract

Scales are needed by traders, including vegetable traders, but the scales created in the market can only determine the weight. That way traders need time to calculate the price based on the weight and type of vegetables. In previous research there has been research on smart scales that can calculate the total price based on the weight and type of vegetables being weighed, this study used the Raspberry Pi 3 Model B and the Convolutional Neural Network (CNN) as a method for the scales to be able to identify the types of vegetables that are on it. Along with the rapid development of technology, the price of the Raspberry Pi for all variants has increased in price. Therefore the need for research on smart scales with components that have relatively cheaper prices. In this study, researchers used the ESP32-CAM microcontroller, which is priced relatively cheaper than the Raspberry Pi 3 Model B. This research still uses the Convolutional Neural Network (CNN) method and a load cell equipped with the HX711 module as a sensor to obtain the weight value of an object. The dataset collected totaled 600 image data with 150 image data for each type of vegetable, classes in the training data consisted of tomatoes, cabbage, carrots, and potatoes. Smart scales using the ESP32-CAM get results of a classification accuracy of 90% and the average difference of the tools built is 0.8 grams compared to the SF-400 brand digital scales.
Analisis Sentimen Pengguna Twitter Terhadap Kenaikan Harga Bahan Bakar Minyak (BBM) Menggunakan Metode Logistic Regression Muhammad Raja Nurhusen; Jamaludin Indra; Kiki Ahmad Baihaqi
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 1 (2023): Januari 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i1.5491

Abstract

In Indonesia itself, fuel is a very important raw material for society, especially for the industrial sector. The fuel price hike policy sparked controversy on social media, one of which was Twitter. After the increase in fuel prices was passed, every day on Twitter was filled with tweets with the hashtag (#bbmnaik). The pros and cons that exist in the community regarding the increase in fuel prices is an interesting research material. This study aims to analyze public sentiment whether it is negative or supportive. The method used is Logistic Regression assisted by the Confusion Matrix for evaluation calculations. The advantage of this method compared to other methods is that the Logistic Regression method is often used to create a predictive model whose result values are in the form of yes/no, true/false, thus this method is very suitable for this research. The data used is 3000 data with keywords (increase in fuel prices). The results of the analysis that has been carried out show that positive sentiments get an accuracy value of 38% and negative sentiments of 80%. Classification performance of the Logistic Regression method gains 73%. The results of evaluation calculations with the Confusion Matrix using data testing as many as 600 data get an accuracy rate of 77%, a precision value of 95%, a recall value of 79%, and an f1 score of 86%. So it can be concluded from the results of the sentiment analysis that has been done that the public is more pro against the rejection of the increase in fuel prices.
Klasifikasi Sampah Logam Dan Plastik Berbasis Raspberry Pi Dengan Metode Convolution Neural Network Ahmad Rahman; Ahmad Fauzi; Jamaludin Indra
Scientific Student Journal for Information, Technology and Science Vol. 4 No. 1 (2023): Scientific Student Journal for Information, Technology and Science
Publisher : Scientific Student Journal for Information, Technology and Science

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

Abstract

Hasil Susenas menunjukkan hanya 1,2 persen rumah tangga melakukan daur ulang sampah. Permasalahan tersebut dapat diatasi dengan peran teknologi yaitu dengan membuat alat yang dapat mengklasifikasikan jenis sampah. Raspberry pi mengklasifikasikan sampah bekas minuman kemasan logam, plastik dan other. Gambar dari pi camera diproses pada raspberry pi untuk mengetahui jenis sampah logam, plastik dan other. Pada proses klasifikasi terdapat 2 tahapan yaitu train model dan predict. Proses klasifikasi menggunakan metode cnn. Train model adalah proses pelathihan model untuk mengenal sampah. Hasil proses training dengan 20 kali epoch diperoleh hasil nilai akurasi training 0.9866. Dari model yang sudah ditraining dilakukan proses prediksi untuk melakukan klasifikasi sampah. Dari 20 kali percobaan diperoleh rata-rata akurasi pengujian model 81,387 %.
Implementasi Fuzzy Logic Tsukamoto pada Deteksi Kondisi Badan Berdasarkan Suhu Tubuh Muhammad Romadhon; Jamaludin Indra; Hilda Novita
Scientific Student Journal for Information, Technology and Science Vol. 4 No. 1 (2023): Scientific Student Journal for Information, Technology and Science
Publisher : Scientific Student Journal for Information, Technology and Science

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

Abstract

Covid – 19 atau Coronavirus Disease pertama kali muncul di negara China pada tahun 2019 dan menyebar secara luas hingga saat ini. Salah satu pencegahan untuk mengurangi dampak penyebarannya yaitu dengan memeriksa suhu tubuh. Suhu tubuh normal antara 36,5°C sampai 37,5°C, apabila melebihi 37,5°C maka terindikasi virus corona. Salah satu bagian penting dari parameter pencegahan penyebaran Covid – 19 yaitu dengan mengecek suhu tubuh, maka diperlukan alat untuk mendeteksi kondisi badan berdasarkan suhu tubuh sebagai pendeteksian awal pencegahan virus corona. Nodemcu ESP8266 yang bersifat open source dapat menjalankan sensor suhu tanpa kontak berdasarkan radiasi inframerah berbasis Internet Of Things. Metode Fuzzy Logic Tsukamoto dapat memberikan suatu keputusan yang pasti. Pendeteksian kondisi badan menggunakan metode Fuzzy Logic Tsukamoto yang diterapkan untuk mengklarifikasi keputusan benar atau salah pada kondisi badan seseorang. Hasil dari penelitian ini dengan menggunakan sensor MLX90614 memiliki selisih hingga 1,29°C dengan alat thermo gun. Pada deteksi kondisi badan menggunakan metode Fuzzy Logic Tsukamoto memiliki tingkat akurasi hingga 86,7%. Hasil suhu tubuh dan kondisi badan beserta input nama lengkap di simpan dalam database dan ditampilkan pada web.
Analisis Sentimen Terhadap Komentar Video Youtube Menggunakan Support Vector Machines Toif Muhayat; Ahmad Fauzi; Jamaludin Indra
Progresif: Jurnal Ilmiah Komputer Vol 19, No 1: Februari 2023
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v19i1.1060

Abstract

Many Youtube users leave comments on the YouTube video content they watch. These comments would be useful if further analysis were carried out. This study aims to analyze Sentiments Toward Youtube Video Comments, to make it easier for creators to find out what types of videos are of interest to viewers, without having to read the comments one by one. The stages carried out in this research are web scrapping, preprocessing, labeling, feature extraction, classification and evaluation. The results of the analysis show that the type of video content with the theme of daily vlogs is more in demand by YouTube users with positive dominant sentiment results. The daily vlog theme has a positive sentiment of 84.0% and a negative sentiment of 16.0%. The use of the SVM (Support Vector Machine) algorithm has an accuracy value of 86%, a precision of 87%, a recall of 99% and an f1-score of 100%.Keywords: Sentiment Analysis; Text Mining; Support Vector Machine; Youtube AbstrakBanyak pengguna Youtube yang meninggalkan komentar pada konten video youtube yang mereka tonton. Komentar-komentar tersebut akan memberikan manfaat jika saja dilakukan analisis lebih lanjut. Penelitian ini bertujuan menganalisis Sentimen Terhadap Komentar Video Youtube, untuk memudahkan kreator mengetahui jenis video yang diminati penonton, tanpa harus membaca komentar secara satu per satu. Tahapan yang dilakukan dalam penelitian ini adalah web scrapping, preprocessing, labelling, ekstraksi fitur, klasifikasi dan evaluasi. Hasil analisis menunjukkan jenis konten video bertema daily vlog lebih banyak diminati oleh pengguna youtube dengan hasil sentimen dominan positif. Tema daily vlog memiliki sentimen positif sebesar 84.0% dan sentimen negatif sebesar 16.0%. Penggunaan algoritma SVM (Support Vector Machine) memiliki nilai akurasi sebesar 86%, presisi sebesar 87%, recall sebesar 99% dan f1-score sebesar 100%.Kata Kunci: Analisis Sentimen; Text Mining; Support Vector Machine; Youtube
Co-Authors AA Sudharmawan, AA Abdul Gapur Achmad, Syifa Latifah Adi Rizky Pratama Adi Rizky Pratama Agung Susilo Yuda Irawan Ahmad Afifur Rahman Ahmad Fauzi Ahmad Fauzi Ahmad Rahman Al Fathir Rizal Januar Alif Kirana Anton Romadoni Junior Apriade Voutama April Hananto Ardiansyah, Fikri Arif Nurman Arip Solehudin Aris Martin Kobar Arum Puspita Lestari, Santi Asep Jamaludin Aviv Yuniar Rahman Awal, Elsa Elvira Ayu Juwita Ayu Ratna Juwita Azis Saputra Azzahra, Wava Lativa Baihaqi, Kiki Ahmad Cici Emilia Sukmawati Dadang Yusup Deden Wahiddin Deny Maulana Dwi Sulistya Kusumaningrum Dwi Vina Wijaya Eko Pramono Fadmadika, Fadilla Faisal, Sutan Fauzi Ahmad Muda Fauzi, Ahmad Firdaus, Thoriq Janati Firmansyah Maulana Fitri Nur Masruriyah, Anis Garno . Garno, Garno Gugy Guztaman Munzi Hanny Hikmayanti Handayani Hanung Pangestu Rahman Hilda Fitriana Dewi Hilda Novita Hilda Yulia Novita Irma Putri Rahayu Juwita, Ayu Ratna Karyanto, Dony Dwi Khoirull Munazzal Kusumaningrum, Dwi Sulistya Lestari, Santi Arum Puspita M Andrian Agustyan Maharina, Maharina Maliah Andriyani Mudzakir, Tohirin Al Muhammad Cesar Afriansyah Arief Muhammad Deden Miftah Fauzi Muhammad Imam Naufal Muhammad Khoiruddin Harahap Muhammad Raja Nurhusen Muhammad Romadhon Nazori AZ Novalia, Elfina Nugraha, Najmi Cahaya Nurdin, Cherry Januar Nurlaelasari, Euis Nursyawalni, Reva Paryono, Tukino Pratama, Adi Rizky Purnama, Ariya Purnomo, Indarto Aditya Rahmat Hidayat Rahmat Rahmat Rahmat Rahmat Rija Nur Hijriyya Rissa Ilmia Agustin Rizki, Lutfi Trisandi Rizky Rifaldi Robinson Nababan Rohana, Tatang Romlah Saefulloh, Nandang Sandi Susanto Santi Lestari Sihabudin Sihabudin, Sihabudin Siregar, Amril Mutoi Siti Robiah Suparno Sutan Faisal Syahrul Azis Tatang Rohana Tia Astiyah Hasan Tohirin Al Mudzakir Tohirin Mudzakir Toif Muhayat Tri Vicika, Vikha Ulfa Amelia Wahiddin, Deden Wildan Amin Wiharja Yana Cahyana Yogi Firman Alfiansyah