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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA EDUMATIC: Jurnal Pendidikan Informatika CASHFLOW : CURRENT ADVANCED RESEARCH ON SHARIA FINANCE AND ECONOMIC WORLDWIDE PIKAT Global Education Journal Journal of Information Systems Management and Digital Business
Setiawan, Dicky
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Social Sciences Other

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Analisis Kompetensi Profesional Guru dalam Mengelola Proses Pembelajaran di SDN Gandong 1 Tahun 2022/2023 Setiawan, Dicky; Permata, Santy Dinar; Mashuri, Anwas
Global Education Journal Vol. 1 No. 1 (2023): Global Education Journal (GEJ)
Publisher : Civiliza Publishing, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59525/gej.v1i1.238

Abstract

This research aims to analyze teachers' professional competence in managing the learning process at SDN Gandong 1 in the 2022/2023 academic year. The type of research applied is descriptive qualitative research. Data was obtained through observation, interviews and documentation involving the principal, class teachers and students. Data analysis was carried out by referring to the framework introduced by Miles, Huberman, and Saldana, which includes the stages of data collection, data reduction, data presentation, and drawing conclusions. Findings from the research show that teachers at SDN Gandong 1 have succeeded in applying their professional competence in managing the learning process. They understand the material, structure and scientific concepts that support the learning process, as well as the core competencies and basic competencies of the subjects they teach well. In addition, they have the ability to produce learning materials in innovative ways, continue to improve their level of professionalism on an ongoing basis, and utilize technology, information and communication for self-development in the context of the learning process. Moreover, aspects of the learning process, such as communication during the teaching and learning process, management of learning implementation, responses from students, student participation in learning activities, and evaluation of student learning outcomes, have all been carried out effectively. All of this confirms the success of teachers in developing their competency skills in teaching brilliantly.
Peningkatan Performa Model Machine Learning XGBoost Classifier melalui Teknik Oversampling dalam Prediksi Penyakit AIDS Wicaksono, Duta Firdaus; Basuki, Ruri Suko; Setiawan, Dicky
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 2 (2024): April 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i2.7501

Abstract

The data shows that HIV (Human Immunodeficiency Virus) has caused tens of millions of global deaths, with 630,000 people dying from HIV-related illnesses in 2022 and 1.3 million people newly infected with HIV. Without treatment, HIV can progress to AIDS (Acquired Immune Deficiency Syndrome), weakening the immune system and increasing the risk of infections and other diseases. Despite advancements in treatment, early detection of AIDS remains a priority. This research develops an AIDS prediction model using machine learning, which proves to be an effective solution in providing future health predictions. However, data imbalance issues challenge the model in predicting rare AIDS cases. To solve this problem, oversampling techniques are employed to balance the distribution of minority classes. This study explores oversampling techniques such as SMOTE, ADASYN, and Random Oversampling, combined with the XGBoost algorithm. The results show that the combination of Random Oversampling technique with the XGBoost Classifier yields the best performance with an accuracy of 94.44%, precision of 90.72%, recall of 98.74%, and an f1_score of 94.65%. This research is expected to provide valuable insights for healthcare practitioners and the public in efforts to control the spread of AIDS globally.
Komparasi Teknik Feature Selection Dalam Klasifikasi Serangan IoT Menggunakan Algoritma Decision Tree Setiawan, Dicky; Nugraha, Adhitya; Luthfiarta, Ardytha
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 1 (2024): Januari 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i1.6987

Abstract

Presence of Internet of Things (IoT) has revolutionized how we interact with the world on our daily life by enabling various devices to connect the internet and transmit data. However, the increasingly widespread use of IoT technology also brings serious threats to cyber security and increases the number of IoT attacks. The need for robust classification models is becoming increasingly clear to anticipate these problems. This research focuses on developing an IoT attack classification model by comparing feature selection techniques that utilize data from the CIC IoT Dataset 2023. This research faces challenges such as data imbalance and the complexity of handling various features. To overcome these challenges, this research uses random undersampling techniques to balance the data and utilizes various feature selection methods, including filter based, wrapper based, and embedded based. Apart from that, this research also tries to use a decision tree algorithm. The findings reveal that the application of wrapper based techniques as feature selection together with a decision tree algorithm produces the highest accuracy of 87.32% in classifying IoT attack types. This emphasizes that the use of techniques and algorithms that are still rarely used can provide fairly good accuracy results.
Penerapan Random Oversampling dan Algoritma Boosting untuk Memprediksi Kualitas Buah Jeruk Ananda, Imanuel Khrisna; Fanani, Ahmad Zainul; Setiawan, Dicky; Wicaksono , Duta Firdaus
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.25836

Abstract

According to the 2019 data, global orange production has increased significantly, reaching 79 million tons. However, despite the availability of various types of oranges in Indonesian markets, many vendors still sell low-quality oranges. To address this issue, researchers have applied random oversampling and boosting algorithms to predict orange quality, using the public Orange Quality Analysis Dataset. This study uses random oversampling to address data imbalance and combines it with boosting algorithms like Adaboost, Gradient Boosting, Light GBM, and CatBoost. The data features considered include size, weight, sweetness level, acidity level, and others. The accuracy of the boosting algorithms used varied, with CatBoost showing the highest accuracy rate of 91.42%. The hope is that this research can help orange producers create high-quality products and reduce the occurrence of low-quality oranges, ultimately providing consumers with better oranges. Additionally, this can help producers market their oranges both domestically and internationally.
CUSTOMER PERCEPTIONS OF BANK SYARIAH INDONESIA MAGELANG SUDIRMAN SUB-BRANCH OFFICE FOR TELLER TRANSACTION SERVICES USING DIGITAL SYSTEMS Setiawan, Dicky; Bharata, Risma Wira; Setyawan, Supanji
CURRENT ADVANCED RESEARCH ON SHARIA FINANCE AND ECONOMIC WORLDWIDE Vol. 2 No. 1 (2022): OCTOBER
Publisher : Transpublika Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55047/cashflow.v2i1.484

Abstract

The aim of this study is to uncover the phenomenon underlying the slow growth and development of Bank Syariah Indonesia (BSI) customers in Magelang Sudirman Sub-branch Office. As such, the facts obtained will be more meaningful and can be used as a basis in developing Indonesian Islamic banking operations. The data analysis technique used is descriptive qualitative-interpretive conducted by controlled interviews through questionnaires. The population in this study were Magelang Sudirman Sub-branch Office customers in the Magelang area, Meanwhile, the sample in this research were Magelang Sudirman Sub-branch Office customers who deposit funds and/or borrow funds from Bank Syariah Indonesia Magelang Sudirman Sub-branch Office. Based on the results of research conducted, most of the informants stated that functionally digital teller services are very effective and make it easier for customers to carry out all types of banking transactions, because they are easy and fast to access.
Parameter Testing on Random Forest Algorithm for Stunting Prediction Mubarok, Ahmad Hasan; Pujiono, Pujiono; Setiawan, Dicky; Wicaksono, Duta Firdaus; Rimawati, Eti
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 1 (2025): Research Article, January 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.14264

Abstract

Stunting is a significant public health problem, especially in developing countries like Indonesia. It is often caused by chronic malnutrition in the first 1,000 days of life, which can impact a child's physical growth and cognitive development. To find risk factors and find effective solutions, data analysis was conducted by utilising machine learning to predict stunting. This research uses the Random Forest algorithm with a focus on setting parameters such as n_estimators, max_depth, and the number of features to optimise model efficiency and accuracy. Using the 2023 Indonesian Health Survey data consisting of 25,800 data, this study managed to get the highest accuracy of 91.65% by a combination of Random Forest with parameter settings n_estimators 200, max_depth 30, and Synthetic Minority Oversampling Technique (SMOTE). Despite the high accuracy results, there are limitations such as potential noise coming from synthetic data from SMOTE and the limited number of features analysed. It is hoped that this research can contribute to the field of machine learning model development that is practically used to predict stunting, and support the government's efforts to reduce the stunting prevalence rate to 14% as targeted. This model also provides strategic insights for policy makers to design more effective data-driven interventions, which can help in decision making.
PARTIKA: DESIGNING AR-BASED APPLICATIONS FOR THE SALE OF NUSANTARA FABRICS SURYAWIJAYA, TITO; SETIAWAN, DICKY; RAHMAWATI, LIA; LAURENT, FISICHELLA; PUTRA, FEBRIANUR
Journal of Information Systems Management and Digital Business Vol. 1 No. 2 (2024): Januari
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59407/jismdb.v1i2.299

Abstract

The post-pandemic has forced Indonesian cloth sellers in Indonesia to face changes in consumer behavior who tend to shop online. They need to find innovative ways to market products and reach potential customers. One of the problems faced is how to present traditional fabrics effectively to potential buyers. Therefore, a more creative and interactive marketing approach is needed. Using the needs analysis method to design innovative augmented reality (AR) integration in the sale of Indonesian fabrics could be an interesting solution. With AR, which will later be called PARTIKA, sellers can show potential buyers how the fabric looks in various situations, provide virtual interaction with the product, and provide detailed information. This application can thus provide a more in-depth and convincing experience, helping customers make better purchasing decisions.
Peran Iklan Video Konten Reels Instagram dalam Meningkatkan Brand Awareness Produk UMKM TUKUTACO.ID Maimunah Nur Nazahah, Mai; Septyanto, Arif Wicaksono; Panji, Ajianto; Pali, Romesal; Setiawan, Dicky; Ramadhan, Gilang Rahmattillah
PIKAT Jurnal Pengabdian Kepada Masyarakat ITK Vol. 6 No. 1 (2025): PIKAT : Jurnal Pengabdian Kepada Masyarakat
Publisher : LPPM Institut Teknologi Kalimantan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35718/pikat.v6i1.1041

Abstract

Penelitian ini bertujuan untuk mengeksplorasi dan menganalisis sejauh mana iklan video konten Reels Instagram dapat mendukung peningkatan brand awareness TUKUTACO.ID. Metode pelaksanaan meliputi analisis target audience, pemilihan platform media sosial, pembuatan konten, penjadwalan posting, dan analisis hasil kinerja. Dalam kurun waktu 24 jam setelah promosi dilakukan, akun Instagram mencapai jangkauan sebanyak 6.190 akun, dengan 133 kunjungan profil dari akun pribadi dan TUKUTACO.ID. Hasil Retention Time menunjukkan bahwa video konten diputar total 8.914 kali, dengan 7.033 pemutaran dari awal hingga selesai dan 1.881 pemutaran ulang. Meskipun pemasaran digital berhasil mencapai 8.914 kali pemutaran, interaksi konten masih terbilang rendah, mencakup 73 like, 4 penyimpanan konten, 2 komentar, dan 0 pembagian konten. Meskipun demikian, data pemutaran yang tinggi menunjukkan efektivitas dalam mencapai audiens, sementara hasil interaksi yang perlu diperhatikan menunjukkan potensi perbaikan dalam strategi interaksi konten. Kata kunci: Reels Instagram, Kesadaran Merk, Camilan, Audiens Target, Media Sosial, Konten Promosi, Pemasaran Digital, Iklan Instagram, Paparan merk, Waktu retensi
Co-Authors Adhitya Nugraha Ahmad Zainul Fanani Ananda, Imanuel Khrisna Ardytha Luthfiarta Arif Wicaksono Septyanto Bharata, Risma Wira Eti Rimawati LAURENT, FISICHELLA Lia Rahmawati, Lia Maimunah Nur Nazahah, Mai Mubarok, Ahmad Hasan Pali, Romesal Panji, Ajianto Pujiono Pujiono PUTRA, FEBRIANUR Ramadhan, Gilang Rahmattillah Ruri Suko Basuki Santy Dinar Permata Supanji Setyawan, Supanji SURYAWIJAYA, TITO Wicaksono , Duta Firdaus Wicaksono, Duta Firdaus