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All Journal Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) Dinamisia: Jurnal Pengabdian Kepada Masyarakat SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal Informatika Global Jurnal Abdimas Mandiri Reswara: Jurnal Pengabdian Kepada Masyarakat Journal of Computer Networks, Architecture and High Performance Computing Jurnal Generic RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Aptekmas : Jurnal Pengabdian Kepada Masyarakat Jurnal Software Engineering and Computational Intelligence
Sartika, Dewi
Universitas Indo Global Mandiri
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Workshop Pembuatan Video Pembelajaran Interaktif Menggunakan Microsoft Powerpoint Dan Editing Menggunakan Video Editor Imelda Saluza; Dewi Sartika; Indah Permata Sari; Yosef Yulius
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 6 No. 6 (2022): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/dinamisia.v6i6.11895

Abstract

PKM activities are carried out to improve teacher knowledge and skills regarding learning media, in this case interactive learning videos. And more specifically, there is an increase in teacher creativity in designing learning media so that they become interactive media that can be used for the learning process. The method used in the implementation of this PKM is in the form of lectures, demonstrations (simulations), and practices which are followed by 33 teachers at SMP Negeri 30 Palembang. This activity includes three stages, namely, observation with the aim of knowing the initial conditions of the school that will be given this activity. Based on the observations, it was found that most of the teachers at SMP Negeri 30 Palembang find it difficult to cope with the different levels of understanding of students and the media that can be used for repetitive learning. Then proceed to the second stage by sharing knowledge between the team and the teacher and the last stage evaluating the activities that have been carried out. Based on the results of the evaluation, it can be concluded that the activities carried out are able to increase the knowledge and skills of teachers in making interactive learning videos, this is indicated by the number of teachers whose knowledge increases by 30 people and will use them as learning media as many as 30 people.
Model Hybrid Menggunakan Dekomposisi-Neural Network Untuk Data Indeks Harga Saham Gabungan Imelda Saluza; Dewi Sartika; Ensiwi Munarsih
Jurnal Ilmiah Informatika Global Vol. 13 No. 3
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jiig.v13i3.2696

Abstract

 The development of Covid-19 has worsened the economy not only nationally but also globally. Since its spread, the price movement of the Jakarta Composite Index (IHSG) has continued to be volatile. JCI price volatility shows risk and uncertainty in investing. Volatility is used as a barometer to determine portfolio management strategies for financial actors. Therefore, financial actors should find a strategy to be able to predict JCI price movements to reduce risks and gain profits. One way that can be done is to predict the JCI price as a reference in investing. This study uses a hybrid model between the decomposition model and the Neural Network (NN) in predicting JCI price volatility. The decomposition uses two approaches, namely additive and multiplicative, the two approaches will then be combined with NN and the NN algorithm used is Feed Forward Neural Network (FFNN) where the results of the decomposition in the form of seasonal, trend, and random data are used as input in the FFNN architecture. The FFNN architecture in this study differs from the hidden layer nodes and the epochs used. Furthermore, the prediction results from the model are compared with a single NN. The performance of each architecture will be measured using the Mean Absolute Error (MAE) and Mean Square Error (MSE). The results show that the hidden layer with more nodes can provide good performance while the epoch used provides good performance depending on the learning process carried out. The prediction results using the hybrid model can outperform the performance of a single NN.Keywords : time series, volatilitas, studi perbandingan, kecerdasan buatan, statistik.
WORKSHOP MEMBUAT DAN MENGGUNGAH VIDEO PEMBELAJARAN SECARA ONLINE BAGI PARA GURU SMP NEGERI 30 PALEMBANG Indah Permatasari; Dewi Sartika; Imelda Saluza
Jurnal Abdimas Mandiri Vol. 6 No. 3
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jam.v6i3.2710

Abstract

Di era pandemic saat ini, metode pembelajaran mengalami perubahan yang cukup signifikan. Hal ini terjadi karena pemberlakukan pembatasan aktivitas dan berkumpul bagi peserta belajar. Kejadian ini mengakibatkan metode pembelajaran menggunakan daring (online) dimana siswa dapat tetap belajar dari rumah. Tuntutan inilah yang menjadikan para pengajar yaitu guru harus memiliki kemampuan dalam akses dan memanfaatkan internet serta kreatif dalam membuat konten materi pembelajaran. Oleh karena itu, SMP Negeri 30 Palembang, menyelenggarakan kegiatan workshop membuat dan mengunggah video pembelajaran pada Youtube Channel, guna memberikan peningkatan pengalaman para guru sebagai bentuk materi pembelajaran secara daring. Kegiatan pengabdian masyarakat ini dilakukan secara langsung dalam ruang rapat dengan mematuhi Protokol Kesehatan Pencegahan Penyebaran Covid-19 di SMP Negeri 30 Palembang pada tanggal 7 Desember 2021.Kata kunci : membuat akun, materi pembelajaran, video, youtube channel
STRATEGI PRODUK DENGAN PELATIHAN PENGEMASAN PRODUK PADA KELOMPOK USAHA KERIPIK SINGKONG RK Indah Permatasari; Dewi Sartika; Imelda Saluza; Roswaty Roswaty
Jurnal Abdimas Mandiri Vol. 7 No. 1
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jam.v7i1.2914

Abstract

Berdasarkan data Badan Pusat Statistik (BPS) tentang data survei sosial ekonomi nasional tahun 2018 menyatakan bahwa persentase masyarakat yang mengakses internet dalam kurun lima tahun terakhir terjadi peningkatan yang signifikan. Sebesar 77,48 persen masyarakat pedesaan dan perkotaan yang mengakses internet, sebanyak 10,82 persen diantaranya memanfaatkan internet untuk melakukan pembelian dan penjualan barang dan jasa secara online. Hal tersebut menunjukkan besarnya potensi media digital sebagai media pemasaran. Berdasarkan hasil observasi diperoleh gambaran umum permasalahan yang dihadapi oleh Usaha Keripik Singkong RK, yaitu salah satunya masih lemahnya strategi produk dalam kemasan sehingga produk belum mampu menjangkau masyarakat luas dan menarik perhatian serta minat masyarakat. Oleh karena itu tim PKM Universitas Indo Global Mandiri (UIGM) menawarkan solusi dari permasalahan yang dihadapi Usaha Keripik Singkong RK selaku mitra dalam kegiatan ini yaitu berupa strategi produk. Strategi produk dilakukan dengan meningkatkan kualitas kemasan produk dengan label yang dilengkapi logo usaha dan informasi penting berkaitan produk. Adapun kegiatan yang dilakukan tim PKM UIGM adalah memberikan pelatihan pengemasan produk. Melalui pelatihan ini diharapkan dapat memberikan pemahaman mengenai petingnya memperhatikan kemasan produk guna menarik minat masyarakat terhadap produk keripik singkong RK.  
Implementasi Algoritma K-Nearest Neighbour dalam Menganalisis Sentimen Terhadap Program Merdeka Belajar Kampus Merdeka (MBKM) Dewi Sartika
Jurnal Buana Informatika Vol. 14 No. 01 (2023): Jurnal Buana Informatika, Volume 14, Nomor 1, April 2023
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jbi.v14i01.7178

Abstract

K-Nearest Neighbor Algorithm Implementation in sentiment analysis towards Merdeka Belajar Kampus Merdeka (MBKM) Program. Merdeka Belajar Kampus Merdeka (MBKM) is a program that supports students to improve their skills by having direct experience in the work environment to prepare for competition and a future career. MBKM program has been implemented by Indonesia's Ministry of Education, Culture, Research, and Technology (Kemendikbudristek) since  2020. Every policy needs to be evaluated; a simple evaluation can be done through sentiment analysis to determine public responses to the MBKM program. The results are used as suggestions for program improvement. Sentiment analysis is done by applying the Natural Language Processing (NLP) algorithm to process crawled data from Twitter, then classified using the K-NN Algorithm. Based on the results, the sentiment is neutral. This illustrates that people are only partially interested in the MBKM program policy. The accuracy of the classification model using the K-NN algorithm is 95%, and an F1-score value of 0.96 for the classification model with a ratio of 80% training data and 20% test data.Keywords: MBKM, NLP, K-NN, F1-Score   Program Merdeka Belajar Kampus Merdeka (MBKM) merupakan suatu kebijakan dalam mendukung pemberian kebebasan terhadap mahasiswa untuk mengasah kemampuan dengan merasakan langsung pengalaman di dunia kerja sebagai bekal untuk menghadapi persaingan dan persiapan berkarir di masa mendatang. Program MBKM mulai diberlakukan oleh Kementerian Pendidikan Kebudayaan Riset dan Teknologi (Kemendikbudristek) Republik Indonesia sejak tahun 2020. Setiap kebijakan tentunya perlu dievaluasi, evalusi sederhana dapat dilakukan melalui analisis sentimen untuk mengetahui tanggapan masyarakat mengenai program MBKM. Hasilnya digunakan sebagai saran perbaikan untuk pengembangan program. Analisis sentimen dilakukan dengan menerapkan algoritma Natural Language Processing (NLP) untuk memproses data hasil crawling dari Twitter, selanjutnya diklasifikasikan menggunakan algoritma K-NN. Berdasarkan hasil analisis diperoleh bahwa sentimen masyarakat bersifat netral. Hal ini menggambarkan bahwa masyarakat tidak sepenuhnya tertarik terhadap kebijakan program MBKM, sedangkan untuk tingkat akurasi model klasifikasi menggunakan algoritma K-NN sebesar 95% dan nilai F1-score sebesar 0,96 untuk model klasifikasi dengan perbandingan 80% data latih dan 20% data uji.Kata Kunci: MBKM, NLP, K-NN, F1-Score
APLIKASI PENGENALAN ANATOMI SISTEM PENCERNAAN PADA TUBUH MANUSIA MENGGUNAKAN TEKNOLOGI AUGMENTED REALITY Ratna Meilinda; Dewi Sartika; Nazori Suhandi
Jurnal Software Engineering and Computational Intelligence Vol 1 No 1 (2023)
Publisher : Informatics Engineering, Faculty of Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jseci.v1i1.3043

Abstract

Natural Sciences (IPA) is a science related to human endeavors in understanding and finding out about the universe through precise observations and using procedures that can be explained by reasoning so as to get a clear conclusion. There are 5 main branches in Natural Sciences, namely Astronomy, Biology, Chemistry, Earth Sciences, and Physics. Science learning should be able to provide direct experience so as to increase the ability to understand and apply the concepts that have been learned. Anatomy is a branch of biology that deals with the structure of living things, in the anatomy of the human body, there are organs that support the formation of the body as a whole. The organs of the body such as bones, joints, skeletal muscles, brain, digestive system, and circulatory system and other organs. The digestive system is a process of mechanically and chemically breaking food into a form that is easier for the body to absorb. interactively in real time. The existence of technology in the form of Augmented Reality will facilitate the process of introducing information and displaying Anatomy Learning objects. This research aims to introduce anatomy to a digestive system in the human body using Augmented Reality technology which can facilitate students in the learning process. The software development method used to design and implement traditional musical instrument recognition applications is the Rational Unified Process method. Application testing is carried out using black-box testing and user testing. User testing was carried out by distributing questionnaires at SMP Negeri 2 Pedamaran Timur. Testing user satisfaction is calculated using a Likert scale and the results of questionnaire questions which can have a final score of 87% which is included in the strongly agree category
APLIKASI PENGENALAN ALAT MUSIK TRADISIONAL SUMATERA SELATAN MENGGUNAKAN TEKNOLOGI AUGMENTED REALITY M. Fadhil Ramadhan Nurbani; Dewi Sartika; Juhaini Alie
Jurnal Software Engineering and Computational Intelligence Vol 1 No 1 (2023)
Publisher : Informatics Engineering, Faculty of Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jseci.v1i1.3044

Abstract

South Sumatra has several traditional musical instruments in the form of Burdah OKU, Gong, Kolintang, Flute, Gambus, Trumpet, Weaving, Genggong, Tambourine, Kenong Basemah. In this research, an application for recognizing traditional South Sumatran musical instruments has been designed and implemented by utilizing Augmented Reality technology. Augmented Reality is a combination of real objects and virtual objects that run interactively in real time. With the existence of technology in the form of Augmented Reality, it will facilitate the process of recognizing information and displaying objects of traditional musical instruments in South Sumatra. This research aims to help reintroduce residents to increase their knowledge of traditional musical instruments in South Sumatra. The software development method used to design and implement traditional musical instrument recognition applications is the Rational Unified Process method. Application testing is carried out using black-box testing and user testing. User testing was carried out by distributing questionnaires at Madrasah Ibtidaiyah Marfu'ah to grade 5 students. User satisfaction testing was calculated using a Likert scale and the results of the questionnaire questions obtained had a final score of 91% which was included in the strongly agree category
Prediksi Calon Mahasiswa Penerima KIP Pada Universitas Indo Global Mandiri menggunakan Algoritma Decision Tree Zakaria Saputra; Dewi Sartika; Muhammad Haviz Irfani
Resolusi : Rekayasa Teknik Informatika dan Informasi Vol. 4 No. 3 (2024): RESOLUSI January 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/resolusi.v4i3.1501

Abstract

Indo Global Mandiri University has accepted Smart Indonesia Card students since 2020. Financing for Smart Indonesia Card students is obtained from government subsidies on the condition that students are required to complete lectures for less than or equal to four years and maintain academic achievement with a minimum cumulative grade point average of 3.00. As in the Informatics Engineering study program, 31 prospective Smart Indonesia Card recipient students must be selected first to fill the available quota. Students who have passed the selection will be ranked to determine the number of prospective students who are entitled to receive assistance carried out by the university's Cooperation Bureau. The purpose of the research is to do programming that can predict the number of students receiving this assistance using the Decision Tree algorithm. Decision Tree (C4.5 version) is one of the classification methods that uses a tree structure representation where each node represents an attribute, the branch represents the value of the attribute, and the leaf represents the class. The attributes used are skill program, average score, KK status, income, and aid card. Based on calculations carried out using the decision tree method, the value of the percentage of accuracy is quite good with a value of 73% for predicting prospective KIP recipient students at Indo Global Mandiri University Palembang, while the performance of the classification model still has a fairly low performance with a precision value of 40%, a recall value of 56% and an F1-score value of 47%.
Toddlers’ Nutritional Status Prediction Using the Multinomial Logistics Regression Method Rendra Gustriansyah; Nazori Suhandi; Shinta Puspasari; Ahmad Sanmorino; Dewi Sartika
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3372

Abstract

Malnutrition is one of the foremost health problems experienced by children under five in many countries, especially in low and middle-income countries. Meanwhile, the target of Sustainable Development Goals (SDGs) 2.2 is that all forms of malnutrition must end by 2025. Therefore, this study aims to predict the toddlers’ nutritional status (malnutrition, undernutrition, overnutrition, and normal nutrition) based on age, body mass index (BMI), weight, and length using the Multinomial Logistic Regression (MLR) classification method. The dataset consists of two hundred toddlers obtained from the Kaggle site. Following pre-processing, the dataset is divided, with 80 percent of the data for training and the remaining 20 percent for testing. The model was trained using 10-fold cross-validation (CV). In Addition, the MLR model performance was evaluated using the confusion matrix (CM), the area under the curve (AUC), and the Kappa coefficient (KC). The evaluation results using CM show that the accuracy, sensitivity, and specificity values are 0.9412, 0.9375, and 0.9790, respectively. AUC and KC also show excellent results. It indicates that the MLR method is an esteemed and recommended method for predicting the nutritional status of toddlers. Therefore, this research can contribute to providing early information so that the Government can immediately determine the necessary treatment.
Pemanfaatan Canva untuk Guru Sekolah Dasar sebagai Media Penyusunan Materi. Indah Permatasari; Dewi Sartika; Rudi Heriansyah; Imelda Saluza
RESWARA: Jurnal Pengabdian Kepada Masyarakat Vol 5, No 2 (2024)
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/rjpkm.v5i2.4347

Abstract

Di sekolah, saat ini telah memanfaatkan teknologi untuk menyampaikan informasi pembelajaran kepada peserta didik. Selain faktor infrastuktur dan pemahaman penggunaan internet, peningkatan pada kemampuan para pendidik dalam memberikan materi juga perlu diperhatikan. Pengembangan materi yang menyesuaikan pemanfaatan teknologi dirasa akan menjadi modal penting untuk tetap menarik perhatian peserta didik agar tetap berminat belajar secara mandiri. Modal materi inilah yang saat ini sering dibuat bervariasi karena harus bersaing dengan era generasi peserta didik yang lebih tertarik dengan teknologi. Dengan tujuan untuk memberikan pemahaman kepada para pendidik/Guru agar dapat membuat materi dengan tampilan yang lebih menarik hanya dengan memanfaatkan aplikasi Canva, tim PkM mengusulkan diperlukan kegiatan pelatihan. Metode workshop dipilih sebagai solusi agar dapat berinteraksi langsung dengan para pendidik selain pemberian pelatihan. Hasil dari kegiatan menunjukkan sebanyak 13 peserta belum pernah menggunakan aplikasi Canva serta sebanyak 22 peserta merasa tertarik dengan aplikasi Canva. kegiatan workshop ini sebagai bagian dari pengabdian masyarakat (PkM) telah diselesaikan dengan baik dan dapat disimpulkan bahwa saat ini kegiatan dianggap penting dilakukan karena masih rendahnya jangkauan pemahaman peserta/Guru terkait beberapa aplikasi pendukung penyusunan materi pembelajaran
Co-Authors Agustina Heryati Ahmad Sanmorino Anggraini, Leriza Desitama Dhamayanti Dhamayanti Dona Marcelina Endah Dewi Purnamasari Ensiwi Munarsih, Ensiwi Faradillah Faradillah Imelda Saluza, Imelda Indah Permata Sari Indah Permatasari Indah Pratiwi Putri Juhaini Alie Kesuma, Hendra Di Lastri Widya Astuti M. Fadhil Ramadhan Nurbani Muhammad Haviz Irfani Muhammad Haviz Irfani Nazori Suhandi Ratna Meilinda Rendra Gustriansyah Roswaty Roswaty Rudi Heriansyah Shinta Puspasari Sunardi, Hastha Yulianti, Evi Yulius, Yosef Zakaria Saputra