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All Journal JSI: Jurnal Sistem Informasi (E-Journal) CIRCUIT: Jurnal Ilmiah Pendidikan Teknik Elektro Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Varian Jurnal Bumigora Information Technology (BITe) ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat
Lalu Ganda Rady Putra
Universitas Bumigora
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Nursing Social Sciences Other

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Impact of H-Index Toward Citations Using Linear Regression on Science and Technology Index Muriyatmoko, Dihin; Rady Putra, Lalu Ganda
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 3, No 3, August 2018
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (340.679 KB) | DOI: 10.22219/kinetik.v3i3.630

Abstract

Number of Journals in Indonesia is quite a lot and various disciplines. Until March 15, 2018, registered 50,889 online and print ISSN by Indonesian Institute of Science (LIPI). The government through Ministry of Research, Technology, and Higher Education of Republic Indonesia (Kemenristekdikti) set regulated on journal index, that is Science and Technology Index (SINTA) assigned to rank quality content and management divided by six categories called S1 to S6 which of the data is taken from Google Scholar and Scopus. This research applies S1 that these journals are accredited “A” by Kemenristekdikti and or index by Scopus. That’s data is shown ranking by sorted based on h-index and citations. S1 shown that journal which has highest h-index uncertain have highest citations too, even some have zeroes. That’s data on S1 become strange and awkward when compared with S2 to S6 because some value of h-index and citations S1 is lower than S2 to S6. This research focus to find how strong correlation or impact h-index toward citations using linear regression. The test result shows that value of Multiple R = 0.78 indicates the correlative is very close, a value of R Square = 0.61 indicates the impact of h-index toward citations achieve 61% and the rest 39% affected by others factor.
Rancang Bangun Sistem Monitoring Penggunaan Daya Listrik Berbasis Internet of Things Sirojul Hadi; Andi Sofyan Anas; Lalu Ganda Rady Putra
CIRCUIT: Jurnal Ilmiah Pendidikan Teknik Elektro Vol 6, No 1 (2022)
Publisher : PTE FTK UIN Ar-Raniry

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/crc.v6i1.10862

Abstract

The modern lifestyle of Indonesian people has influenced the level of increasing of the electricity consumption. The wasteful use of household electricity even uncontrolled due to the lack of monitoring of the amount of power used. It does not enough to monitor power depends on the kWh meter because the electricity users cannot monitor every room which excessive in terms of electricity consumption. In this study, a monitoring tool was designed to monitor power consumption in each room. The purpose of this study is to determine the power consumption in each room. Thus, it is easier to save electrical energy. Implementation of the internet of things (IoT) used the Blynk platform. The results showed that the tools (design) have been successful in monitoring the power consumption of each IoT-based room. At load the laptop charger produces 99.61% efficiency, at load two lamps produces efficiency 98.94%, at fan load produces efficiency 99.08% and at load two lamps and laptop charger produces efficiency 99.07%. It can be concluded that the system built has very good efficiency and can make it easier to monitor power consumption in household electronic equipment.
Pengenalan Teknologi Sensor Cahaya Untuk Meningkatkan Minat Belajar Siswa Sekolah Dasar Sirojul Hadi; Siti Soraya; Puspita Dewi; Khairan Marzuki; Lalu Ganda Rady Putra; Regina Pricilia Yunika
ADMA : Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol 1 No 1 (2020)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (395.787 KB) | DOI: 10.30812/adma.v1i1.818

Abstract

Education is an effort to build a better human civilization and eliminate human suffering caused by ignorance and underdevelopment in science and technology. In this research, a workshop was held to introduce light sensor technology to enhance elementary students' interest in learning about technology. This research was conducted at SDN 3 Mataram. The research was carried out by dividing 40 participants into 5 groups with each group guided by one mentor. Each group will be guided by a mentor to practice making light sensor technology until the light sensor circuit to turn on the lights can function properly. To find out students' interest in learning is done by making a questionnaire before and after doing the practice. The results obtained from the questionnaire that there is no significant difference between the understanding at the pre test and post test
Forecasting Foreign Tourist Visits to West Nusa Tenggara Using ARIMA Method Siti Soraya; Maulida Nurhidayati; Baiq Candra Herawati; Anthony Anggrawan; Lalu Ganda Rady Putra; Didiharyono D
Jurnal Varian Vol 5 No 1 (2021)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v5i1.1441

Abstract

West Nusa Tenggara (NTB) is one of the provinces in Indonesia that has its own charm in the world of tourism and is known as a pioneer of halal tourism. In addition to domestic tourists, NTB tourism always has an attraction for foreign tourists. This is evidenced by the increasing number of foreign tourists visiting NTB from year to year before the Covid-19 pandemic. This condition certainly has a positive impact on increasing NTB’s economic growth in the tourism sector and indirectly on the optimization of existing infrastructure. The purpose of the study is to predict the number of foreign tourist visits to NTB so that it can assist the government in making decisions in preparing adequate facilities and infrastructure in the event of a surge in tourist visits. The method used in this study is the Box-Jenkins-ARIMA model. The ARIMA method is based on 3 models that are formed from the results of plot data. The data used in this study is secondary data sourced from the Central Statistics Agency (BPS) of West Nusa Tenggara (NTB), from January 2010 to June 2019. The results show that the ARIMA (4,1,1) model is the most widely used model. This model is suitable for predicting the number of foreign tourists visiting NTB because this model produces the lowest SSE and MSE values compared to other models.
Pengelompokan Penerima Bantuan Sosial Masyarakat dengan Metode K-Means Lalu Ganda Rady Putra; Anthony Anggrawan
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 21 No 1 (2021)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (367.744 KB) | DOI: 10.30812/matrik.v21i1.1554

Abstract

Pada umumnya bantuan yang di berikan oleh pemerintah kepada masyarakat terkadang tidak tepat sasaran, karena sebagian masyarakat yang mampu secara ekonomi mendapatkan bantuan sedangkan masih banyak masyarakat yang tidak mampu justru tidak menerima bantuan dari pemerintah. Tujuan dari penelitian ini adalah mengelompokan penerima bantuan sosial yang layak menerima bantuan dan kurang layak menerima bantuan. Solusi yang di berikan dengan menggunakan tahapan penelitian yaitu pengumpulan data, data preprossesing, implementasi metode klasifikasi dan analisa hasil untuk mengetahui hasil akhir. Analisis yang di gunakan adalah data penerima bantuan sosial yang belum di kelompokan dan berdasarkan hasil dalam pengelompokan penerima bantuan sosial menggunakan metode K–means, dari 257 data terdapat 196 data yang termasuk cluster 1 dengan status penerima bantuan sosial tepat sasaran dan 61 data yang termasuk cluster 2 dengan status penerima bantuan sosial tidak tepat sasaran. Dari hasil analisis data dapat ditarik sebuah kesimpulan yaitu masyarakat yang menerima bantuan sudah tepat sasaran karena mayoritas penerima bantuan diterima oleh masyarakat yang benar-benar membutuhkan bantuan dari pemerintah, dimana penerima bantuan bekerja sebagai buruh, tidak memiliki aset dan memiliki penghasilan di bawah Rp 500.000.
Impact of H-Index Toward Citations Using Linear Regression on Science and Technology Index Dihin Muriyatmoko; Lalu Ganda Rady Putra
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 3, No 3, August 2018
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v3i3.630

Abstract

Number of Journals in Indonesia is quite a lot and various disciplines. Until March 15, 2018, registered 50,889 online and print ISSN by Indonesian Institute of Science (LIPI). The government through Ministry of Research, Technology, and Higher Education of Republic Indonesia (Kemenristekdikti) set regulated on journal index, that is Science and Technology Index (SINTA) assigned to rank quality content and management divided by six categories called S1 to S6 which of the data is taken from Google Scholar and Scopus. This research applies S1 that these journals are accredited “A” by Kemenristekdikti and or index by Scopus. That’s data is shown ranking by sorted based on h-index and citations. S1 shown that journal which has highest h-index uncertain have highest citations too, even some have zeroes. That’s data on S1 become strange and awkward when compared with S2 to S6 because some value of h-index and citations S1 is lower than S2 to S6. This research focus to find how strong correlation or impact h-index toward citations using linear regression. The test result shows that value of Multiple R = 0.78 indicates the correlative is very close, a value of R Square = 0.61 indicates the impact of h-index toward citations achieve 61% and the rest 39% affected by others factor.
Deteksi Kegawatan Pasien Covid-19 Berbasis Android Menggunakan Algoritma C45 Kartarina Augustin; Miftahul Madani; Lalu Ganda Rady Putra; Lalu Naufal Azmi; Ibjan Syarif Hidayatullah
Jurnal Bumigora Information Technology (BITe) Vol 4 No 1 (2022)
Publisher : Prodi Ilmu Komputer Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v4i1.1772

Abstract

Coronavirus merupakan keluarga besar virus yang menyebabkan penyakit mulai darigejala ringan, sedang atau berat. Virus Corona adalah Zoonosis (ditularkan antara hewan danmanusia), dari virus ini melahirkan penyakit baru yang diberi nama Coronavirus Disease 2019atau yang disingkat menjadi COVID-19. Early Warning Scoring System(EWSS) adalah sebuah sistem peringatan dini yang menggunakan penanda berupa skor untukmenilai perburukan kondisi pasien sebelum masalah terjadi sehingga dengan penanganan yanglebih dini diharapkan kondisi mengancam jiwa dapat diatasi lebih cepat dan mampumeningkatkan pengelolaan perawatan penyakit secara menyeluruh. Salah satu strategi EWSSuntuk deteksi dini kegawatan pasien adalah dengan penerapan teknologi informasi android dan data mining sebagai sistem peringatan dini yang bermanfaat bagi perawat untuk mengetahuitingkat kegawatan pasien yang ditandai berupa skor untuk menilai perburukan kondisi pasienselain itu juga meningkatkan pengelolaan perawatan penyakit secara menyeluruh. Skorperingatan dini yang direkomendasikan sebagai bagian dari pengkajian awal dan responterhadap kerusakan organ pasien. Sistem deteksi dini kegawatan pasien dapat mengidentifikasikeadaan pasien yang beresiko lebih awal dan menggunakan multi parameter. DeteksiKegawatan Pasien Covid-19 Menggunakan teknologi Mobile yaitu teknologi android dan tools WEKA untuk menganalisa inputan sebagai kemanfaatan untuk kebutuhan dalam penelitianpelayanan kesehatan
Klasifikasi Jenis Client Menggunakan Algoritma Decision Tree Cart Lalu Ganda Rady Putra; Mayadi Mayadi; I Nyoman Darmawan Setiaji
Jurnal Sistem Informasi Vol 14, No 2 (2022)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/jsi.v14i2.18826

Abstract

Influencer marketing adalah sebuah metode pemasaran secara digital yang dimana seseorang atau figure yang memiliki pengaruh dimasyarakat atau target konsumen yang dituju dan dirasa bisa menjadi tempat untuk promosi. PT. Lombok Media Utama (Inside Lombok) merupakan perusahaan media independen berbasis media sosial yang menyajikan informasi, berita dan influencer marketing bagi online shop dan UMKM lokal. Permasalahan yang timbul adalah dengan banyaknya client yang bekerja sama dengan Inside Lombok memiliki rata-rata 2000-3000 client tiap tahunnya, Inside Lombok masih manual dalam menentukan jenis client, seperti hanya melihat toko fisik saja atau berdasarkan jumlah follower yang di miliki oleh client. Yang dimana hal itu tidak efektif dalam menentukan jenis client yang terbagi menjadi 3 yaitu: usaha mikro, usaha kecil, dan usaha menengah. Perancangan dan pembuautan sistem klasifikasi jenis client ini menggunakan metodologi CRISP-DM, yaitu metode mengembangan perangkat lunak terdiri dari 6 fase yaitu pemahaman bisnis, pemahaman data, pengolahan data, pemodelan, evaluasi dan penyebaran. Hasil atau keluaran yang akan dicapai yaitu sistem dapat menampilkan jenis client berdasarkan atribut yang telah dimasukan. Kesimpulan dari penelitian ini adalah pertama sistem dapat menampilkan jenis client degan akurasi sebesar 95% hal ini dapat membantu pihak Inside Lombok dalam memilih jenis client dengan cepat dan akurat.
Peningkatan Kinerja Metode Random Forest Berbasis Smote-Tomek Link Pada Sentimen Analisis Pariwisata Lombok Marzuki, Khairan; Rady Putra, Lalu Ganda; Hairani, Hairani; Mardedi, Lalu Zazuli Azhar; Guterres, Juvinal Ximenes
Jurnal Bumigora Information Technology (BITe) Vol 5 No 2 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v5i2.3166

Abstract

Background: Tourists visiting Lombok Island can access various sources of tourist information and can share their views and tourist experiences through social media such as positive and negative experiences. Objective: This research aims to analyze the sentiment of Lombok tourism reviews using the Smote-Tomek Link and Random Forest algorithms.Methods: The research was carried out in several stages, namely collecting the Lombok tourism dataset, text preprocessing, text weighting using the Term Frequency-Inverse Document Frequency (TF-IDF) method, data sampling using SMOTE-Tomek Link, text classification using Random Forest, and the final stage was performance testing based on accuracy. Result: The research results obtained using the Smote-Tomek Link and Random Forest methods in sentiment analysis analysis of tourist reviews about Lombok were 94%. Conclusion: The use of the Smote-Tomek Link and Random Forest methods in Lombok tourism sentiment analysis produces very good accuracy.
Enhancing Semantic Similarity in Concept Maps Using LargeLanguage Models Wiryawan, Muhammad Zaki; Prasetya, Didik Dwi; Handayani, Anik Nur; Hirashima, Tsukasa; Pratama, Wahyu Styo; Putra, Lalu Ganda Rady
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 24 No. 3 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i3.4727

Abstract

This research uses advanced models, Generative Pre-trained Transformer-4 and Bidirectional Encoder Representations from Transformers, to generate embeddings that analyze semantic relationships in open-ended concept maps. The problem addressed is the challenge of accurately capturing complex relationships between concepts in concept maps, commonly used in educational settings, especially in relational database learning. These maps, created by students, involve numerous interconnected concepts, making them difficult for traditional models to analyze effectively. In this study, we compare two variants of the Artificial Intelligence model to evaluate their ability to generate semanticembeddings for a dataset consisting of 1,206 student-generated concepts and 616 link nodes (Mean Concept = 4, Standard Deviation = 4.73). These student-generated maps are compared with a reference map created by a teacher containing 50 concepts and 25 link nodes. The goal is to assess the models’ performance in capturing the relationships between concepts in an open-ended learning environment. The results show that demonstrate that Generative Pretrained Transformers outperform other models in generating more accurate semantic embeddings. Specifically, Generative Pre-trained Transformer achieves 92% accuracy, 96% precision, 96% recall, and 96% F1-score. This highlights the Generative Pretrained Transformer’s ability to handle the complexity of large, student-generatedconcept maps while avoiding overfitting, an issue observed with the Bidirectional Encoder Representationsfrom Transformer models. The key contribution of this research is the ability of two complex models and multi-faceted relationships among concepts with high precision. This makes it particularly valuable in educational environments, where precise semantic analysis of open-ended data is crucial, offering potential for enhancing concept map-based learning with scalable and accurate solutions.
Co-Authors Andi Sofyan Anas Anik Nur Handayani Anthony Anggrawan Dewi, Puspita Didiharyono, D. Didik Dwi Prasetya Dihin Muriyatmoko Guterres, Juvinal Ximenes Hairani Hairani Herawati, Baiq Candra Hirashima, Tsukasa I Nyoman Darmawan Setiaji Ibjan Syarif Hidayatullah Kartarina, Kartarina Khairan marzuki Lalu Naufal Azmi Mardedi, Lalu Zazuli Azhar Mardedi, Lalu Zazuli Azhar Mayadi Mayadi Mayadi Mayadi, Mayadi Miftahul Madani Nurhidayati, Maulida Pratama, Wahyu Styo Regina Pricilia Yunika Setiaji, I Nyoman Darmawan Sirojul Hadi Siti Soraya Triyanna Widyaningtyas, Triyanna Wiryawan, Muhammad Zaki