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All Journal Jurnal Ilmiah Mahasiswa FEB SAINTIFIK@ : Jurnal Pendidikan MIPA Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Agroteksos Proceedings Series on Physical & Formal Sciences Sejahtera: Jurnal Inspirasi Mengabdi Untuk Negeri Nanggroe: Journal Of Scholarly Service Jurnal Manajemen Riset Inovasi Maeswara: Jurnal Riset Ilmu Manajemen dan Kewirausahaan Nanggroe: Journal of Scholarly Service Faedah: Jurnal Hasil Kegiatan Pengabdian Masyarakat Indonesia JEAS Jurnal Penelitian Teknologi Informasi dan Sains Saber: Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi Jurnal Inovasi Ekonomi Syariah dan Akuntansi Jurnal Bisnis Inovatif dan Digital Router : Jurnal Teknik Informatika dan Terapan Repeater: Publikasi Teknik Informatika dan Jaringan Algoritma: Jurnal Matematika, Ilmu Pengetahuan Alam, Kebumian dan Angkasa Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Karya Nyata: Jurnal Pengabdian Kepada Masyarakat Router : Jurnal Teknik Informatika dan Terapan
Andy Hermawan
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Other

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Implementing XGBoost Model for Predicting Customer Churn in E-Commerce Platforms Andy Hermawan; Aji Saputra; Muhammad Dhika Rafi; Syafiq Basmallah; Yilmaz Trigumari Syah Putra; Wafa Nabila
Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 3 No. 2 (2025): April: Repeater : Publikasi Teknik Informatika dan Jaringan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/repeater.v3i2.401

Abstract

Customer churn is a major challenge in e-commerce, directly affecting revenue and profit. This study aims to develop a machine learning model using XGBoost to predict churn probability. To handle class imbalance, SMOTE was applied as a resampling method, and hyperparameter tuning was performed to enhance performance. The model was evaluated using the F2-score, prioritizing recall while maintaining precision. The results show that the XGBoost model with SMOTE achieves strong performance, with an F2-score of 0.849 on the tuned test data. This model can help businesses identify at-risk customers early, enabling proactive retention strategies.
Predicting Hotel Booking Cancellations Using Machine Learning for Revenue Optimization Andy Hermawan; Aji Saputra; Nabila Lailinajma; Reska Julianti; Timothy Hartanto; Troy Kornelius Daniel
Router : Jurnal Teknik Informatika dan Terapan Vol. 3 No. 1 (2025): Maret: Router : Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v3i1.400

Abstract

Hotel booking cancellations pose significant challenges to the hospitality industry, affecting revenue management, demand forecasting, and operational efficiency. This study explores the application of machine learning techniques to predict hotel booking cancellations, leveraging structured data derived from hotel management systems. Various classification algorithms, including Random Forest, XGBoost, and LightGBM were evaluated to identify the most effective predictive model. The findings reveal that XGBoost model outperforms other models, achieving F2-score of 0.7897. Key influencing factors include deposit type, total number of special requests, and marketing segment. The results underscore the potential of predictive modeling in optimizing hotel revenue strategies by enabling proactive measures such as dynamic pricing, targeted customer engagement, and improved overbooking policies. This study contributes to the ongoing advancements in data-driven decision-making within the hospitality industry, offering insights into how machine learning can mitigate financial risks associated with booking cancellations.
Penerapan Metode RFM dengan Python dalam Segmentasi Pelanggan Andy Hermawan; Ravli Avdala Kahfi; Erwin Surya; Ulfatul Aini; Risky Hidayat
Jurnal Bisnis Inovatif dan Digital Vol. 1 No. 3 (2024): Juli : Jurnal Bisnis Inovatif dan Digital
Publisher : Asosiasi Riset Ilmu Manajemen Kewirausahaan dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/jubid.v1i3.222

Abstract

In a competitive business environment, understanding customer behaviour and improving retention strategies are critical to a company's success. Many companies struggle to identify valuable customers, understand their needs, and develop effective marketing strategies. One method that has proven effective is Recency, Frequency, and Monetary (RFM) analysis, which measures customer value based on three dimensions: when the customer last made a purchase, how often they transact, and how much money they spend. This research focuses on applying the RFM method with Python for customer segmentation in a retail company. By analysing customer transaction data, this research shows how RFM analysis can provide deep insights into customer behaviour and assist in the development of more targeted marketing strategies. The ultimate goal is to improve customer retention and maximise the return on investment (ROI) of marketing activities. This research offers practical solutions to common challenges in customer relationship management and contributes to the development of more efficient data-driven marketing methods.
Bedah Kisi-Kisi Olimpiade IPA pada Materi Besaran, Satuan dan Pengukuran Melalui Media YouTube Aji Saputra; Hijrasil Hijrasil; Sumarni Sahjat; Nurlaela Muhammad; Hutri Handayani Isra; Masrifah Masrifah; Indah Kristiani Siringo Ringo; Dewi Amiroh; Mirda Prisma Wijayanto; Andy Hermawan; Palti Maretto Caesar Manalu; Hilya Wildana Sofia; Riris Idiawati; Khoironi Fanana Akbar; Ferdiana Ferdiana; Nurul Hidayah
Sejahtera: Jurnal Inspirasi Mengabdi Untuk Negeri Vol. 4 No. 2 (2025): Sejahtera: Jurnal Inspirasi Mengabdi Untuk Negeri
Publisher : Universitas Maritim AMNI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58192/sejahtera.v4i2.3168

Abstract

This activity aims to analyze the results of the study of Science Olympiad content outline on the subject of Quantities, Units and Measurement. This video was made using the PowerPoint application for the content, and the Ice Cream screen recorder to record. The research method uses a descriptive qualitative method with a sample of all viewers, the majority of whom are junior high school students. This activity can be concluded as effective by looking at the number of viewers reaching more than 28 thousand, the number of likes 920 without dislikes and 40 positive comments from viewers who accessed on March 12, 2025 at 21:37.
TOWR Stock Forecasting From 2021-2025 Using Machine Learning Andy Hermawan; Angga Sukma Budi Darmawan; Muhammad Iqbal; Mochammad Rivan Akhsa; Nila Rusiardi Jayanti; Zidan Amukti Rajendra
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 3 No. 1 (2025): JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v3i1.3136

Abstract

Accurate stock price forecasting is a crucial yet challenging task due to the complex and dynamic nature of financial markets. This study employs the Prophet model to predict the stock prices of PT Sarana Menara Nusantara Tbk (TOWR) from 2021 to 2025. The research leverages historical stock data, incorporating dividend distribution dates and Annual General Meeting (AGM) events as external regressors to enhance predictive accuracy. The model was developed using machine learning-based time series forecasting, with hyperparameter tuning applied to optimize performance. The evaluation metrics indicate a Mean Absolute Error (MAE) of Rp49.92 and a Mean Absolute Percentage Error (MAPE) of 6.47%, demonstrating the model’s robustness in capturing long-term stock price trends. The findings suggest that stock prices exhibit significant movements around dividend announcement periods and AGM events, highlighting the impact of corporate actions on market behavior. This study reinforces the importance of incorporating fundamental financial indicators into forecasting models to improve decision-making for investors and financial analysts. The results offer practical implications for investment strategy formulation, risk management, and market trend analysis.
Faktor yang Mempengaruhi Peran Pusat Pelatihan Pertanian dan Pedesaan Swadaya (P4S) dalam Meningkatkan Pengetahuan dan Keterampilan Petani di Kabupaten Banyumas Hermawan, Andy; Wakhidati, Yusmi Nur; Sari, Lilik Kartika
Proceedings Series on Physical & Formal Sciences Vol. 8 (2025): Prosiding Seminar Nasional Fakultas Pertanian dan Perikanan
Publisher : UM Purwokerto Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/pspfs.v8i.1475

Abstract

Pusat Pelatihan Pertanian dan Pedesaan Swadaya (P4S), sebagai perpanjangan tangan Kementerian Pertanian, memiliki peran strategis dalam transfer ilmu kepada petani. Berdasarkan Renstra Kementan 2016, P4S berfungsi sebagai fasilitator pelatihan, mediator dalam penyuluhan dan pengembangan teknologi, serta pengembang jejaring usaha tani. Melalui perannya, P4S mendukung pemberdayaan petani dengan meningkatkan pengetahuan teknis, memberikan akses ke pasar, dan menyediakan dukungan finansial. Penelitian ini bertujuan untuk menganalisis faktor- faktor yang memengaruhi peran P4S dalam meningkatkan pengetahuan dan keterampilan petani di Kabupaten Banyumas. Faktor internal mencakup tata kelola lembaga, kapasitas lembaga, manajemen lembagan, dan kerja sama dengan dinas pertanian, sedangkan faktor eksternal meliputi karakteristik petani peserta P4S. Penelitian dilakukan pada Juli–Agustus 2024 dengan melibatkan 75 responden petani peserta P4S. Metode yang digunakan adalah survei, yang bertujuan memperoleh fakta dan informasi faktual dari sampel populasi dengan menggunakan kuesioner sebagai alat pengumpul data. Data yang digunakan dalam penelitian ini adalah data primer, yang dikumpulkan melalui wawancara. Analisis data dilakukan menggunakan metode PLS (Partial Least Square) dengan perangkat lunak SmartPLS. Hasil penelitian menunjukkan bahwa tata kelola kelembagaan, kerja sama dengan dinas pertanian, dan karakteristik petani berpengaruh signifikan terhadap peran P4S. Faktor-faktor ini juga berkontribusi pada peningkatan pengetahuan dan keterampilan petani. Kerja sama dengan dinas pertanian ditemukan sebagai faktor paling penting, yang memberikan pengaruh signifikan baik secara langsung maupun tidak langsung terhadap efektivitas P4S dalam pelatihan, penyuluhan, dan pendampingan petani di Kabupaten Banyumas.
Exploring Artificial Intelligence for Physics Learning in Indonesia: A Scoping Review Saputra, Aji; Sambiri, Usman; Hermawan, Andy
SAINTIFIK@: Jurnal Pendidikan MIPA Vol 10, No 1 (2025): SAINTIFIK@: Jurnal Pendidikan MIPA EDISI MARET 2025
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/saintifik.v10i1.10037

Abstract

The integration of Artificial Intelligence (AI) into education has opened new opportunities to enhance learning effectiveness, particularly in science subjects such as physics, which often involve abstract and complex concepts. In Indonesia, the application of AI in physics education is emerging, yet its scope, challenges, and potential have not been comprehensively mapped. This study aims to identify and map existing literature on the implementation of AI in physics education in Indonesia, as well as to explore the challenges and opportunities related to its integration. Using a scoping review method, this research analyzed nine selected articles published between 2018 and 2024. The review followed the PRISMA-ScR protocol and focused on studies involving AI tools such as ChatGPT, Google Bard, and intelligent tutoring systems across different educational levels. The findings indicate that AI has been implemented in various forms, including chatbots, virtual assistants, and automated assessment systems. These tools have supported student engagement, enhanced conceptual understanding, and improved teacher efficiency in planning instruction. However, several challenges persist, such as limited digital literacy among educators, dependency on AI-generated responses, and the need for validation of AI outputs. The review also identifies promising opportunities for future research and development, especially in adaptive learning and culturally contextual AI applications. In conclusion, while the use of AI in physics education in Indonesia is still in its early stages, it demonstrates significant potential. A strategic and pedagogically sound integration, supported by training and collaboration, is essential to maximize its impact
ANALISIS DAYA SAING DAN FAKTOR-FAKTOR YANG MEMPENGARUHI KAKAO INDONESIA DI PASAR GLOBAL Biky, Muhammad Amir; Hermawan, Andy
AGROTEKSOS, Jurnal Ilmiah Ilmu Pertanian Vol 35 No 1 (2025): Jurnal Agroteksos April 2025
Publisher : Fakultas Pertanian Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/agroteksos.v35i1.1283

Abstract

Kakao merupakan komunitas perkebunan subsektor pertanian yang menyumbang pertumbuhan perekonomian Indonesia. Tujuan dari penelitian ini adalah menganalisis daya saing dan faktor-faktor yang mempengaruhi ekspor kakao Indonesia di pasar internasional. Metode dalam penelitian ini menggunakan data sekunder. Data diperoleh dari Badan Pusat Statistik (BPS), databoks, UN Comtrade, dan International Cocoa Organization (ICCO). Untuk menilai daya saing kakao Indonesia di pasar global, data diolah secara kuantitatif dengan menggunakan analisis Revealed Comparative Advantage (RCA). Kemudian dilanjutkan dengan analisis Regresi Linier Berganda yang mengidentifikasi variabel-variabel yang mempengaruhi daya saing dan fakto-faktor yang mempengaruhi ekspor kakao Indonesia di pasar global. Hasil penelitian menunjukkan bahwa tingkat daya saing ekspor kakao Ekuador dan Nigeria jauh di atas Indonesia. Namun, karena Indonesia memiliki nilai RCA rata-rata 2.255, maka Indonesia lebih berdaya saing dibandingkan negara lain yang mengekspor biji kakao, seperti Jerman dan Kolombia. Volume Ekspor Kakao Indonesia-Global adalah satu-satunya faktor yang mempengaruhi ekspor kakao indonesia secara signifikan dengan nilai Sig. 0,000 dan nilai t hitung 7,774. Harga ekspor kakao dan nilai tukar AS tidak memiliki dampak yang terlihat. Daya saing kakao Indonesia harus ditingkatkan, demikian pula bantuan dan keterlibatan pemerintah, termasuk diseminasi teknologi budidaya kepada petani kakao di indonesia.
Pengaruh Penggunaan Keywords Pada Penamaan Listing Airbnb Terhadap Tingkat Popularitas Di Kota Bangkok Andy Hermawan; Fatika Rahma Sanjaya; Gregorius Aldo Primantono; Muhammad Syahirul Alim
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 2 No. 3 (2024): Agustus : Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v2i3.179

Abstract

This study aims to explore the impact of keyword usage in Airbnb listing names on their popularity in Bangkok. Using regular expression (re) and tokenization methods, we identified the top 100 keywords from the listing name column. These keywords were then categorized based on business knowledge. Subsequently, the relationship between keyword usage and popularity was analyzed using the chi-square test, with popularity measured by the number of reviews in the last 12 months. The data used were sourced from Open Data Airbnb and underwent data cleaning and exploratory data analysis (EDA). The results of this study are expected to provide insights for Airbnb hosts to enhance the appeal of their listings through effective naming strategies.
Sosialisasi dan Pendampingan Pendaftaran Kartu Indonesia Pintar Kuliah (KIP-K) Bagi Siswa-Siswi Tidak Mampu di Kepulauan Sula Maluku Utara Aji Saputra; Mirda Prisma Wijayanto; Andy Hermawan; Ismi Musdalifah Darsan; Roni Kurniawan; Hutri Handayani Isra; Krishna Aji; Zandy Pratama Zain; Sheila Kusumaningrum; Rusandry Rusandry; Sartika Putri Sailuddin; Firmansyah Firmansyah; Agatha Christy Situru; Syahrial Maulana; Iwan Abdy
Karya Nyata : Jurnal Pengabdian kepada Masyarakat Vol. 1 No. 3 (2024): September : Karya Nyata : Jurnal Pengabdian kepada Masyarakat
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/karyanyata.v1i3.694

Abstract

Kartu Indonesia Pintar Kuliah (KIP-K) is a scholarship given by the government to high school graduates and equivalent who excel but have economic limitations to continue their studies at university level, both at state and private universities. The Indonesian government has issued the KIP-K since 2020 as a form of educational assistance. In North Maluku Province, especially on Sula Island, there is still minimal information regarding KIP-K. This service activity aims to share information regarding the benefits of higher education and how to obtain a KIP-K scholarship for students who have financial limitations. This community service is carried out at SMAN 1 Kepulauan Sula, MAN 1 Kepulauan Sula, SMAN 7 Kepulauan Sula, SMAN 9 Kepulauan Sula and SMAN 11 Kepulauan Sula. This activity was carried out in two stages, namely socialization and mentoring. The implementation of this activity went well, smoothly and was full of enthusiasm from the participants, especially students who wanted to continue their studies at university level. The final result of this socialization and mentoring is that the participants have succeeded in creating their own accounts, filling in data and registering for KIP-K.
Co-Authors Adam Praharsya Rahmadian Agatha Christy Situru Aji Saputra Aji Saputra Aji, Krishna Amaliasyifa Agustina Amira Afdhal Angga Sukma Budi Darmawan Army Putera Parta Ayi Satria Yuddha B Hilda Nida Alistiqlal Bagas Dio Hanggoro Bagas Surya Prakasa Bayu Wicaksono Biky, Muhammad Amir cahaya Tambunan Chumidach Roini Cindana, Adinda Prilly Dewi Amiroh Dzaky Muhammad Baihaqi Erwin Surya Fachmi Aditama Fatika Rahma Sanjaya Fatma Hamid Ferdiana Ferdiana Firmansyah Firmansyah Gregorius Aldo Primantono Hijrasil Hijrasil Hilya Wildana Sofia Hutri Handayani Isra Indah Kristiani Siringo Ringo Ismi Musdalifah Darsan Iwan Abdy Jasico Dacomoro Aruan Jayanti, Nila Rusiardi Kerin Aurelia Khoironi Fanana Akbar Lilik Kartika Sari, Lilik Kartika Limatahu, Iqbal Lintang Rizki Ramadhani Masrifah, Masrifah Mirda Prisma Wijayanto Mochammad Rivan Akhsa Muhamad Fauzi Hakim Muhammad Abizar Algiffary Thahir Muhammad Alif Syahreza Muhammad Dhika Rafi Muhammad Hafizh Bayhaqi Muhammad Iqbal Muhammad Mustofa Muhammad Syahirul Alim, Muhammad Syahirul Nabila Lailinajma Nainggolan, Dian Margaretha Nasrun Balulu Nila Rusiardi Jayanti Nur Fajrhi Nurdin Abdul Rahman Nurlaela Muhammad Nurul Ainun Tangge Nurul Hidayah Nuur Muhammad Ilham Palti Maretto Caesar Manalu Ravli Avdala Kahfi Reska Julianti Riris Idiawati Risky Hidayat Roni Kurniawan Rusandry Rusandry Safryan, Rizky Jemal Sandy, Agung Ferdinan Saprudin, Saprudin Sartika Putri Sailuddin Sheila Kusumaningrum Sitti Mukarramah Sumarni Sahjat, Sumarni Syafiq Basmallah Syahrial Maulana Taufiqurrahman Taufiqurrahman Tigfhar Ahmadjayadi Timothy Hartanto Troy Kornelius Daniel Ulfatul Aini Usman Sambiri Vita Mayastinasari Wafa Nabila Wakhidati, Yusmi Nur Yilmaz Trigumari Syah Putra Zacharia Bachtiar Zandy Pratama Zain Zidan Amukti Rajendra