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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 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 Jurnal Penelitian Teknologi Informasi dan Sains Jurnal Inovasi Ekonomi Syariah dan Akuntansi 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 Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika Karya Nyata: Jurnal Pengabdian Kepada Masyarakat Router : Jurnal Teknik Informatika dan Terapan Jurnal Publikasi Teknik Informatika JEAS: Journal of Educational and Applied Science
Andy Hermawan
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ANALISIS PENGARUH UMK DALAM PENGENTASAN KEMISKINAN DI JAWA TIMUR ANDY HERMAWAN
Jurnal Ilmiah Mahasiswa FEB Vol 7, No 2: Semester Genap 2018/2019
Publisher : Fakultas Ekonomi dan Bisnis Universitas Brawijaya

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

Abstract

Penelitian bertujuan untuk mengetahui pengaruh dari Upah Minimum Kabupaten/Kota(UMK) di provinsi Jawa Timur pda tahun 2012 dan 2016. Kemiskinan merupakan isu nasionaldimana tiap provinsi memiliki strategi yang berbeda beda untuk menyikapinya. Jawa timurmerupaka salah satu provinsi dengan kepadatan penduduk yang tinggi yaitu pada posisi kelimadan posisi kedua menurut jumlah pnduduk tiap provinsi di Indonesia. keadaan demograi tersebutmenyebabkan Jawa Timur menjadi Provinsi yang sangat potensial dalam pengembangan ekonomidikarnakan melimpahnya Sumber Daya Manusia yang tersedia. Namun pada kenyataannya diProvinsi Jawa Timur pada satu dekade terakhir menjadi salah satu penyumbang angkakemiskinan nasional, yaitu 10.85 persen pada tahun 2018 dan UMK provinsi Jawa Timur masihberada dibawa rata rata nasional padahal pertumbuhan cenderung selalu berada diatas nasional.Penelitian menggunakan data panel 38 kabupaten/kota pada tahun 2012-2016. Hasil penelitianmenunjukkan ditemukan bukti bahwa kenaikan upah minimum dan investasi dapat menurunkantingkat kemiskinan yang ada di Jawa Timur, namun terdapat elastisitas daerah dengan IPM yangtinggi cenderung memerlukan kenaikan yang tinggi untuk dapat menurunkan kemiskinandibandingkan daerah dengan IPM rendah. Maka dari itu, peningkatan UMK masih dapatdilakukan namun dengan mempertimbangkan karakteristik tiap tiap daerah.Kata kunci: Kemuskinan, UMK, IPM, Pertumbuhan Ekonomi, Investasi. 
Adaptation of Working Culture in Police Culture in Pandemic Times Ayi Satria Yuddha; Vita Mayastinasari; Andy Hermawan; Muhammad Mustofa
Budapest International Research and Critics Institute-Journal (BIRCI-Journal) Vol 5, No 3 (2022): Budapest International Research and Critics Institute August
Publisher : Budapest International Research and Critics University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33258/birci.v5i3.5940

Abstract

The COVID-19 pandemic through the spread of the SARS-CoV-2 virus since approximately two years ago, perhaps these two fields have never been directly related. Currently, the police and health are closely related. The spread of the epidemic in the community inevitably affects how the police adapt in carrying out their duties, functions, and roles. This pandemic has changed the social order system, including the work culture. The methodology used is by using a qualitative approach. On the other hand, the pandemic situation has created challenges in adapting to the working culture within the police organization. How police officers are able to adapt their work culture to the emergency situation of the pandemic. learning organization where organizational performance will increase supported by individual performance starting from the support of organizational commitment, organizational culture and leadership. With regard to working culture during the pandemic, leaders are at the forefront of bringing about change and need support from subordinates.
Pemanfaatan Youtube Dalam Mendukung Persiapan Olimpiade IPA Jenjang SMP Aji Saputra; Ismi Musdalifah Darsan; Saprudin Saprudin; Fatma Hamid; Nurdin Abdul Rahman; Dewi Amiroh; Sitti Mukarramah; Syahrial Maulana; Zandy Pratama Zain; Nurul Ainun Tangge; Nasrun Balulu; Usman Sambiri; Nur Fajrhi; Hutri Handayani Isra; Iqbal Limatahu; Chumidach Roini; Sumarni Sahjat; Krishna Aji; Andy Hermawan
Faedah : Jurnal Hasil Kegiatan Pengabdian Masyarakat Indonesia Vol. 2 No. 2 (2024): Jurnal Hasil Kegiatan Pengabdian Masyarakat Indonesia
Publisher : FKIP, Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59024/faedah.v2i2.811

Abstract

This community service aims to provide learning videos to all participants in the National Science Olympiad in Natural Sciences. This learning video is a free learning resource that can be accessed anytime and anywhere via the YouTube platform. These learning videos consist of 9 videos containing OSN Science grids and are collected into one playlist entitled KSN IPA (Fisika) SMP. The use of YouTube in supporting preparations for the science olympiads at junior high school level can be said to be effective by looking at the number of viewers, the number of likes and that no one gave a dislike. Ease of access and targeted material content can be something that attracts students participating in OSN. Even the comments column can also be used as a medium for discussion and correction of each material presented.
Analisis Customer Retention Dalam Ritel Online Data United States E-Commerce Records 2020 Andy Hermawan; Muhamad Fauzi Hakim; B Hilda Nida Alistiqlal; Bagas Dio Hanggoro
Jurnal Inovasi Ekonomi Syariah dan Akuntansi Vol. 1 No. 4 (2024): Juli: Jurnal Inovasi Ekonomi Syariah dan Akuntansi (JIESA)
Publisher : Asosiasi Riset Ekonomi dan Akuntansi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/jiesa.v1i4.276

Abstract

This study investigates the level of customer loyalty in e-commerce in the United States in 2020. Using e-commerce customer data from 2020 available on Kaggle, this research analyzes cohort retention to understand the number of customers from each cohort who continue to make purchases in subsequent months. Additionally, this study evaluates the implementation of data analysis to assess the effectiveness of promotional strategies and their impact on customer loyalty and retention. The results show that retention percentages decline over time, with the number of active customers decreasing after registration. However, some cohorts exhibit better retention performance. For instance, the April cohort saw a significant increase from 18.46% to 29.23%, and the May cohort experienced the highest increase from 14.29% to 30.16%. On the other hand, the January cohort showed the most drastic retention drop from 100% to 10.42% after the first month, with the largest monthly decline from 23.96% in April to 7.29% in May. These findings provide practical guidance for e-commerce companies in developing more effective strategies to improve customer retention. Further analysis is recommended to understand the specific causes of these retention trends and to develop more holistic strategies to support better business decisions and increase long-term profitability.
Optimalisasi Strategi Pemasaran Melalui Analisis RFM pada Dataset Transaksi Ritel Menggunakan Python Andy Hermawan; Nila Rusiardi Jayanti; Aji Saputra; Cahaya Tambunan; Dzaky Muhammad Baihaqi; Muhammad Alif Syahreza; Zacharia Bachtiar
Jurnal Manajemen Riset Inovasi Vol. 2 No. 4 (2024): Oktober : Jurnal Manajemen Riset Inovasi
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/mri.v2i4.3246

Abstract

This study aims to optimize marketing strategies through RFM (Recency, Frequency, Monetary) analysis on a retail transaction dataset obtained from Kaggle. The dataset contains 64,682 transactions from 5,242 SKUs involving 22,625 customers over one year. Data cleaning and RFM analysis were conducted to segment customers based on recency, frequency, and monetary values. The findings reveal that customers were segmented into groups such as Champions, Loyal Customers, and At Risk. These segments provide valuable insights for developing targeted marketing strategies, such as loyalty programs for high-value customers and retention campaigns for at-risk customers. The study demonstrates that RFM analysis is effective in identifying valuable customer segments and optimizing marketing efforts based on customer behavior. This approach can increase customer retention and improve the return on investment (ROI) in marketing campaigns.
Pelatihan Teknologi Dalam Pemanfaatan Internet of Things (IoT) Kontrol Jarak Jauh Peralatan Elektronik Jayanti, Nila Rusiardi; Agustina, Amaliasyifa; Sandy, Agung Ferdinan; Hermawan, Andy
Nanggroe: Jurnal Pengabdian Cendikia Vol 3, No 7 (2024): Oktober
Publisher : Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.13987868

Abstract

Teknologi Internet of Things (IoT) menjadikan internet sebagai jembatan penghubung berbagai pekerjaan manusia, melakukan monitoring dengan Smartphone dapat mempermudah User dalam mengendalikan perangkat elektronik, terintergrasi dalam satu sistem sehingga lebih efisien, hemat waktu dan listrik. Terutama pada bangunan yang memiliki banyak lantai yang akan memakan waktu dan tenaga yang lebih besar. Beberapa perusahaan telah bermigrasi memanfaatkan teknologi yang lebih canggih dengan peralatan elektronik yang berbasis IoT dan tidak lagi melakukan dengan cara tradisional, oleh karena itu keterampilan dan pemahaman terkait dengan teknologi dan informasi ini cukup penting dimiliki oleh semua pekerja tanpa terkecuali. Berangkat dari perusahaan telah bermigrasi dalam pengembangan dan pemanfaatan teknologi IoT yang tengah dilakukan oleh banyak perusahaan jasa dalam pemasangan  peralatan elekronik, khususnya oleh PT.Trijaya Maju Bersama Jakarta Barat. Mendorong Kami tim abdimas Universitas Indraprasta PGRI untuk melakukan Pelatihan implementasi peralatan elektronik berbasis IoT pada PT.Trijaya Maju Bersama Jakarta Barat.
Pelatihan Teknologi Dalam Pemanfaatan Internet of Things (IoT) Kontrol Jarak Jauh Peralatan Elektronik Jayanti, Nila Rusiardi; Agustina, Amaliasyifa; Sandy, Agung Ferdinan; Hermawan, Andy
Nanggroe: Jurnal Pengabdian Cendikia Vol 3, No 7 (2024): Oktober
Publisher : Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.13987868

Abstract

Teknologi Internet of Things (IoT) menjadikan internet sebagai jembatan penghubung berbagai pekerjaan manusia, melakukan monitoring dengan Smartphone dapat mempermudah User dalam mengendalikan perangkat elektronik, terintergrasi dalam satu sistem sehingga lebih efisien, hemat waktu dan listrik. Terutama pada bangunan yang memiliki banyak lantai yang akan memakan waktu dan tenaga yang lebih besar. Beberapa perusahaan telah bermigrasi memanfaatkan teknologi yang lebih canggih dengan peralatan elektronik yang berbasis IoT dan tidak lagi melakukan dengan cara tradisional, oleh karena itu keterampilan dan pemahaman terkait dengan teknologi dan informasi ini cukup penting dimiliki oleh semua pekerja tanpa terkecuali. Berangkat dari perusahaan telah bermigrasi dalam pengembangan dan pemanfaatan teknologi IoT yang tengah dilakukan oleh banyak perusahaan jasa dalam pemasangan  peralatan elekronik, khususnya oleh PT.Trijaya Maju Bersama Jakarta Barat. Mendorong Kami tim abdimas Universitas Indraprasta PGRI untuk melakukan Pelatihan implementasi peralatan elektronik berbasis IoT pada PT.Trijaya Maju Bersama Jakarta Barat.
Analisis Segmentasi Pelanggan Berbasis RFM dan Evaluasi Efektivitas Kampanye Pemasaran untuk Meningkatkan Retensi Andy Hermawan; Fachmi Aditama; Lintang Rizki Ramadhani; Nuur Muhammad Ilham; Aji Saputra; Nila Rusiardi Jayanti
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 2 No. 4 (2024): November: Neptunus: 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.v2i4.400

Abstract

This research implements RFM (Recency, Frequency, Monetary) analysis to perform customer segmentation and evaluate the effectiveness of marketing campaigns in a retail company. Using a Kaggle dataset, this study identifies customers based on purchasing behaviour and assesses marketing campaign responses for each segment. The analysis reveals that Loyal, VIP, and New Customer segments showed the highest responses, especially in Campaign 6. The findings emphasize the importance of targeting resources on effective segments and campaigns to optimize marketing strategies and maximize ROI. Personalized campaigns based on segmentation can enhance customer retention and align product offerings with customer needs.
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 Profesi Telekomunikasi 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.
Co-Authors Abda Abda Agatha Christy Situru Aji Saputra Aji Saputra Aji, Krishna Amaliasyifa Agustina Angga Sukma Budi Darmawan Antonius Andriyanto Army Putera Parta Ayi Satria Yuddha B Hilda Nida Alistiqlal Bagas Dio Hanggoro Bagas Surya Prakasa Bayu Wicaksono cahaya Tambunan Chumidach Roini Cindana, Adinda Prilly Dewi Amiroh Dzaky Muhammad Baihaqi 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 Iwana Amalia Jasico Dacomoro Aruan Jayanti, Nila Rusiardi Khoironi Fanana Akbar Limatahu, Iqbal Lintang Rizki Ramadhani Masrifah, Masrifah Mirda Prisma Wijayanto Mochammad Rivan Akhsa Muhamad Fauzi Hakim Muhammad Abizar Algiffary Thahir Muhammad Alif Syahreza Muhammad Amir Biky Muhammad Dhika Rafi Muhammad Mustofa Muhammad Rafif Muhammad Syahirul Alim, Muhammad Syahirul Mukarramah, Sitti Nabila Avicenna Azzahra 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 Reinaldi Ragasa Reska Julianti Riris Idiawati Roni Kurniawan Rusandry Rusandry Ryandri Alif Pratomoputra Safryan, Rizky Jemal Sandy, Agung Ferdinan Saprudin, Saprudin Sartika Putri Sailuddin Sheila Kusumaningrum Sumarni Sahjat, Sumarni Syafiq Basmallah Syahrial Maulana Taufiqurrahman Taufiqurrahman Tigfhar Ahmadjayadi Timothy Hartanto Troy Kornelius Daniel Usman Sambiri Vita Mayastinasari Wafa Nabila William Armand Rahardjo Yilmaz Trigumari Syah Putra Yogga Prastya Wijaya Zacharia Bachtiar Zandy Pratama Zain Zidan Amukti Rajendra