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All Journal DoubleClick : Journal of Computer and Information Technology Edu Dharma Journal: Jurnal penelitian dan pengabdian masyarakat Algoritme Jurnal Mahasiswa Teknik Informatika Informatics and Enginering Dedication NURSING ANALYSIS: Journal of Nursing Research MDP Student Conference Jurnal Rekayasa Sistem Informasi dan Teknologi
rusbandi rusbandi, rusbandi
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Medicine & Pharmacology Nursing Other

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Pelatihan Pembuatan Grafik Untuk Penyajian Data Laporan Teguh, Rizani; Iba Ricoida, Desy; Rusbandi, Rusbandi
FORDICATE Vol 3 No 1 (2023): November 2023
Publisher : Universitas Multi Data Palembang, Fakultas Ilmu Komputer dan Rekayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/fordicate.v3i1.6312

Abstract

Srijaya Negara Palembang High School partners want to increase students' level of understanding regarding the use of Microsoft Excel, especially in making graphs. The MDP University Service Team carries out this activity in the form of training, which aims to increase students' understanding of Microsoft Excel which is carried out using presentation, practice and question and answer methods. The training activity was attended by 36 student participants and 2 accompanying teachers and was carried out well and smoothly according to the planned schedule. The results of the training activities were based on indicators from questionnaire questions to participants, overall in the "Good" and "Very Good" categories and 100% of participants stated that they wanted to take part in the training again if it were to be carried out again in the future.
Perbandingan Akurasi Algoritma Data Mining dalam Memprediksi Kelulusan Tepat Waktu Ricoida, Desy Iba; Hermanto, Dedy; Pibriana, Desi; Rusbandi, Rusbandi; Pribadi, Muhammad Rizky
DoubleClick: Journal of Computer and Information Technology Vol 7, No 2 (2024): Edisi Februari 2024
Publisher : Universitas PGRI Madiun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25273/doubleclick.v7i2.19300

Abstract

Lulusan tepat waktu menjadi salah satu poin penilaian sangat penting bagi sebuah perguruan tinggi untuk memperoleh nilai akreditasi. Dikatakan lulusan tepat waktu jika seorang mahasiswa dapat lulus empat tahun atau dibawah empat tahun jika berada pada jenjang Strata-1. Penelitian ini menggunakan dataset yang diperoleh dari universitas dengan data dari angkatan 2015-2019, dimana total data yang digunakan yaitu sebanyak 1307 baris. Sebanyak 26 atribut yang digunakan dalam penelitian ini yaitu tahun_masuk, waktu_kuliah, jenis_kelamin, tipe_sekolah, jurusan, IPS 1-10, SKS 1-10 dan status. Algoritma yang digunakan dalam penelitian ini yaitu decision tree, naive bayes, logistic regression, KNN dan random forest. Hasil yang diperoleh dalam penelitian ini yaitu algoritma random forest memiliki tingkat akurasi yang paling tinggi sebesar 90.88% dengan hasil dari AUC yang diperoleh yaitu sebesar 97.2% dan perhitungan F1-Score dari hasil nilai precision dan recall diperoleh sebesar 89.9%, tertinggi dari empat algoritma lainnya. Sedang untuk algoritma decision tree dan logistic regression memiliki nilai akurasi masing-masing yaitu sebesar 89.12% dan 89.47%. Nilai dari logistic regressing lebih tinggi untuk akurasi, akan tetapi untuk nilai F1-Score decision tree lebih baik dari logistic regression yaitu 88.7% berbanding 87.6%.
Penerapan Teknik SMOTE Pada Analisis Sentimen Bea Cukai Menggunakan Algoritma Naïve Bayes Moniung, Yosefa Camilia; Marcellino, Alwin; Rusbandi, Rusbandi
Algoritme Jurnal Mahasiswa Teknik Informatika Vol 4 No 2 (2024): April 2024 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v4i2.8155

Abstract

Social media platforms like YouTube are frequently used by the public and can quickly make issues go viral. Recently, customs duties have come under scrutiny for being considered too high. For example, a man who bought shoes worth 10 million rupiahs was charged 30 million rupiahs in import duties, and a female migrant worker from Madura was charged hundreds of millions of rupiahs for bringing 3kg of gold from Saudi Arabia. These cases have sparked public debate, leading to a sentiment analysis using the Naïve Bayes algorithm and SMOTE method. The research dataset was imbalanced, prompting a comparison between using SMOTE and not using it. The evaluation results without SMOTE showed an accuracy of 95.175%, with precision at 95%, recall at 100%, and an F1-score of 98% for the negative class, but all metrics for the positive class were 0%. After applying SMOTE, the overall accuracy was 85.526%. The negative class achieved a precision of 98%, recall of 87%, and an F1-score of 92%, while the positive class achieved a precision of 19%, recall of 64%, and an F1-score of 30%. Without SMOTE, the accuracy was higher, but overfitting occurred.
ANALYSIS ENGAGEMENT OF INSTAGRAM VISITORS AT UNIVERSITY OF MULTI DATA PALEMBANG BASED ON TOPIC USING LDA Jerin, Nathaniel; Rizky Pribadi, Muhammad; Rusbandi, Rusbandi
Jurnal Rekayasa Sistem Informasi dan Teknologi Vol. 1 No. 2 (2023): November
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59407/jrsit.v1i2.172

Abstract

Social media has a big impact on everyday life, one of which is to communicate or to get information. Therefore, the development of social media applications makes people use social media applications to find information via the internet. The Instagram applications is one of the most popular social media because it has different topics based on post in the from of images or videos. Therefore, it is very difficult to identify a topic manually. One way to get implied information on social media is through topic modeling. This research was conducted to analyze the application of the LDA method to identify what topics are on Instagram at Multi Data Palembang University. The topics chosen in this study were obtained from LDA based on coherence values. This research uses 2 models, namely random forest and decision tree. Each model tested will produce different accuracy, precision, recall, and f1-score values. Tests were carried out on the LDA labeling dataset and manual labeling, the test results on the LDA labeling dataset were very good using the random forest model with an accuracy values of 78%, precision 80%, recall 66.66%, and f1-score 72.72%.
Klasifikasi Kualitas Selada Menggunakan Algoritma K-Nearest Neighbors dengan Nutrisi NPK Berdasarkan Fitur HSV Maharani, Sanila; Rusbandi, Rusbandi
MDP Student Conference Vol 4 No 1 (2025): The 4th MDP Student Conference 2025
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v4i1.11224

Abstract

Hydroponics is a soilless planting method that uses water containing essential nutrient solutions. Lettuce (Lactuca sativa) is a popular vegetable, including those grown hydroponically because of its high nutritional content. In hydroponics, plants depend on three main elements: Nitrogen (N), Phosphorus (P), and Potassium (K). Deficiency of one of these elements affects the color and quality of lettuce. This study aims to classify the nutritional quality of lettuce using the K-Nearest Neighbors (KNN) algorithm with NPK nutrients based on HSV features, with evaluation through Euclidean Distance. Lettuce is classified into four categories FN (Full Nutrition), K (Potassium), N (Nitrogen), and P (Phosphorus). The results showed the highest accuracy at K = 1 of 86.2%, precision 85.7%, recall 70.5%. So this method is proven effective for classifying the nutritional quality of lettuce.
BUAH TANGAN JENIS TEPUNG TERIGU PADA ROTI GORENG BERNABEU FITUR LBP DENGAN JARINGAN SARAF TIRUAN Chandra B, Leonardo; Gasim, Gasim; Rusbandi, Rusbandi
Algoritme Jurnal Mahasiswa Teknik Informatika Vol 1 No 1 (2020): Oktober 2021 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (461.273 KB) | DOI: 10.35957/algoritme.v1i1.441

Abstract

Penelitian ini tentang mengidentifikasi jenis tepung terigu pada goreng dengan menggunakan metode jaringan saraf tiruan. Jenis tepung terigu yang digunakan adalah kunci biru, sania, dan segitiga biru. Metode pengenalan yang digunakan adalah backpropagation . Hasil pengujian yang dilakukan menggunakan ukuran pixel 450x450px, jarak potret sejauh ±20 cm, resolusi kamera 16MP, menggunakan data latih sebanyak 100 citra/jenis dan data uji sebanyak 80 citra/jenis serta dengan menggunakan ekstraksi ciri Local Binary Pattern maka didapatkan hasil berupa tingkat akurasi sebesar 68,57%, presisi sebesar 53,33% dan recall sebesar 54,47%.
Identifikasi Jenis Buah Pir Berdasarkan Bentuk Menggunakan Metode HOG dan JST Paniza, Mehri; Rusbandi, Rusbandi; Alamsyah, Derry
Algoritme Jurnal Mahasiswa Teknik Informatika Vol 2 No 1 (2021): Oktober 2021 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (534.922 KB) | DOI: 10.35957/algoritme.v2i1.1455

Abstract

Buah pir memiliki bentuk dan warna yang mirip sehingga muncul lah permasalahandalam pengenalan jenis buah pir berdasarkan bentuk menggunakan kecerdasan buatan. Varianatau jenis buah pir dan setiap jenis buah pir tersebut memiliki bentuk ataupun warna yangberbeda-beda. Beberapa spesies pohon pir menghasilkan buah yang rasanya manis, bahkanterkadang lebih manis dari buah apel. Data latih yang digunakan pada penelitian ini sebanyak240 citra setiap jenis buah pir dan data uji yang digunakan sebanyak 60 citra. Metode yangdigunakan pada penilitian ini adalah Histogram of Oriented Gradients digunakan sebagaiEktraksi fitur sedangkan Jaringan Syaraf Tiruan sebagai pengenalan objek. Jenis buah pir yangdigunakan ada 5 yaitu Abate, Forelle, Kaiser, Red dan Williams. Berdasarkan hasil pengujianmenggunakan tabel skenario Tuning Parameter didapatkan rata-rata akurasi terbaik melebihi97%, dan akurasi keseluruhan terbaik terdapat pada Hidden Layer 5 Learning Rate 0.1 danEpoch 10000.
Klasifikasi Penyakit Daun Jagung Menggunakan Metode Convolutional Neural Network Putra, Ivan Pratama; Rusbandi, Rusbandi; Alamsyah, Derry
Algoritme Jurnal Mahasiswa Teknik Informatika Vol 2 No 2 (2022): April 2022 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2192.855 KB) | DOI: 10.35957/algoritme.v2i2.2360

Abstract

Jagung merupakan tanaman pangan utama ketiga setelah padi dan terigu di dunia dan menempati posisi kedua setelah padi di Indonesia. Penyakit tanaman sering kali disebabkan oleh aktifitas atau serangan organism di dalam bagian tubuh tanaman, di luar tubuh, atau di sekitarnya. Penelitian ini bertujuan untuk mengklasifikasikan penyakit daun jagung menggunakan metode convolutional neural network (CNN) dengan arsitektur Resnet 50 dengan optimizer Adam, Nadam dan SGD. Dataset terdapat 4225 citra di pisahkan menjadi 3380 data train, 845 data test. Citra yang digunakan di resize menjadi ukuran 224x224. Pada penelitian ini mendapatkan hasil tingkat akurasi tertinggi untuk arsitektur Resnet 50 dengan menggunakan optimizer Adam didapatkan tingkat akurasi sebesar 98,4%.
Penerapan Aplikasi Plaxis Pada Prodi Teknik Sipil Fakultas Teknik Universitas Tridinanti Palembang Teguh, Rizani; Rusbandi, Rusbandi; Sudiadi, Sudiadi; Novita, Dien; Mardiani, Mardiani
FORDICATE Vol 1 No 2 (2022): April 2022
Publisher : Universitas Multi Data Palembang, Fakultas Ilmu Komputer dan Rekayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1154.671 KB) | DOI: 10.35957/fordicate.v1i2.2406

Abstract

Perkembangan teknologi informasi di segala bidang, termasuk universitas, membuat dosen dan mahasiswa terus meningkatkan kemampuannya dalam mengerjakan proyek-proyek. Salah satu upaya yang dapat dilakukan adalah dengan menerapkan teknologi komputer yang dapat mendukung proses kerja proyek yang berkaitan dengan mata kuliah Mekanika Tanah. Selama ini mahasiswa dan dosen selalu kesulitan melakukan perhitungan yang rumit, dimana membutuhkan waktu yang lama untuk menyelesaikannya dan hasilnya belum tentu akurat. Salah satu aplikasi yang dapat digunakan untuk membantu menyelesaikan perhitungan pada mata kuliah Mekanika Tanah adalah aplikasi Plaxis. Oleh karena itu perlu diadakan pelatihan penggunaan aplikasi Plaxis, pelatihan ini penulis laksanakan bersama tim di Program Studi Teknik Sipil Fakultas Teknik Universitas Tridinanti Palembang. Pelatihan di Aula Fakultas Teknik Universitas Tridinanti Palembang yang dihadiri oleh dosen dan mahasiswa Program Studi Teknik Sipil Fakultas Teknik Universitas Tridinanti Palembang. Pelatihan ini mendapat respon yang baik dari para peserta. Diharapkan dosen dan mahasiswa dapat menerapkan aplikasi The Plaxis setelah mengikuti kegiatan tersebut
RELATIONSHIP BETWEEN KNOWLEDGE OF REPRODUCTIVE HEALTH WITH THE PREVENTION OF EARLY MARRIAGE IN ADOLESCENT WOMEN IN RW 002 CIBEUTEUNG VILLAGE, UDIK, BOGOR DISTRICT Simarmata, Agnes Defvi; Hasanah, Uswatun; Rusbandi, Rusbandi; Marsiwi, Andini Restu; Ardi, Ni Bodro; Ningrum, Mita Widya; Fasimi, Rizki Handayani; Nurhaeti, Ade
NURSING ANALYSIS: Journal of Nursing Research Vol 5, No 1 (2025): NURSING ANALYSIS: JOURNAL OF NURSING RESEARCH
Publisher : Sekolah Tinggi Ilmu Kesehatan Widya Dharma Husada Tangerang

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

Abstract

According to the World Health Organization adolescents are residents aged 10-19 years, the United Nation Fund for Population Activities (UNFPA) in 2020 the increase in early marriage every year reached 14.2 million, West Java in 2021 is one of the other provinces with a fairly high underage marriage rate of 20.93%. Knowledge is very instrumental in the Prevention of early marriage because with bad knowledge is very influential on adolescents who are at risk of reproductive health. The purpose of this study was to determine the relationship of reproductive health knowledge with the Prevention of early marriage in adolescent girls in RW 002 Cibeuteung Village Udik Bogor regency. This research method uses descriptive analytical research design cross sectional method with a quantitative approach using purposive sampling technique with a population and a sample of 60 respondents, this research instrument uses a questionnaire, the sample criteria are young women aged 15-19 years. The results of the study: univariate: half of respondents have sufficient knowledge of reproductive health, namely 29 respondents 48.3% and more than half of respondents have sufficient prevention of early marriage, namely 38 respondents 63.3%. Bivariate: this is obtained from Spearman rho test results obtained obtained value (p-value 0.000) so that (p-value a 0.05) then ha is accepted. The conclusion of this study is that there is a significant relationship between reproductive health knowledge with the Prevention of early marriage in adolescent girls in RW 002 Village Cibeuteung Udik Bogor regency. This research suggestion is expected to be useful, especially in the community to know more about reproductive health knowledge and Prevention of early marriage.
Co-Authors Andini Restu Marsiwi Anggraeni, Ganung Chandra B, Leonardo Dedy Hermanto Derry Alamsyah Desy Iba Ricoida Dian Anggraeni Dien Novita gasim, Gasim Gian Hawara Handoko, Wisnu Iba Ricoida, Desy Jerin, Nathaniel Jumatina, Jumatina Maharani, Sanila Marcellino, Alwin Mardiani Mardiani Moniung, Yosefa Camilia Muhammad Rizky Pribadi Ni Bodro Ardi Ningrum, Mita Widya Nurhaeti, Ade Paniza, Mehri Pibriana, Desi Putra, Ivan Pratama Rizani Teguh Rizki Handayani Fasimi Simarmata, Agnes Defvi Sudiadi, Sudiadi Syafara, Selsa Ziera Uswatun Hasanah Wulan, Rahayu Nawang