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tukino, tukino
Universitas Putera Batam
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Pembinaan Pemberdayaan Kelompok UKM Berbasis Teknologi Dan Pemasaran Digital Erlin Elisa; Tukino Tukino; Alfannisa Annurrallah Fajrin; Nanda Harry Mardika; Suvianto Wangdra
Prosiding Vol 5 (2023): SNISTEK
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/psnistek.v5i.8099

Abstract

The implementation of community service activities that will be carried out in the form of fostering Pemasaran Digital-Based Marketing Empowerment which is located at Rindang Garden Blok B2 No. 04 Buliang Batu Aji Village, Batam. Based on the results of interviews in the field that KUBE Jasmine SMEs have problems marketing their products. In general, SMEs have limitations in mastering the use of information technology facilities plus marketing media that are less well known by the public. SMEs or conventional entrepreneurs consider accounting records to be a hassle. The training method used is to provide training on training using an online website. The methods used in the development of KUBE Jasmine UKM that will be given are survey methods, lecture methods, discussion methods and training methods. The sustainability of the results of the coaching activities is that KUBE Jasmine SMEs are expected to be able to manage marketing through web-based Pemasaran Digital.
Pembinaan Sistem Akuntansi Serta Pelaporan Keuangan di SMK Kolese Tiara Bangsa Syahril Effendi; Tukino Tukino; Ronald Wangdra; Yvonne Wangdra; Baru Harahap
Prosiding Vol 5 (2023): SNISTEK
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/psnistek.v5i.8108

Abstract

Effective accounting and financial reporting systems are crucial for ensuring transparency, accuracy, and the sustainability of finances in vocational schools like SMK Kolese Tiara Bangsa. This research aims to examine the efforts in fostering and enhancing the accounting and financial reporting systems at SMK. The study involves data collection from various sources, including interviews with administrative staff, document analysis, and monitoring of accounting procedures. The research findings indicate that SMK Kolese Tiara Bangsa has undertaken significant efforts to improve their financial governance. These efforts include training for administrative staff, the utilization of state-of-the-art accounting software, and enhancing understanding of applicable accounting standards. Furthermore, the school has also revamped their financial reporting processes, encompassing the regular preparation of financial statements and strict budget monitoring. The improvement in the accounting and financial reporting system has aided SMK Kolese Tiara Bangsa in more effectively managing their finances, enhancing the accuracy of financial information, and increasing transparency and accountability. This study provides valuable insights into the importance of fostering and developing accounting systems in educational institutions, with the hope of setting an example for similar institutions aiming to improve their financial management.
Penerapan Metode Fuzzy Sugeno Untuk Menentukan Kelayakan Pengiriman Limbah Barang Berbahaya Dan Beracun Alfannisa Annurrallah Fajrin; Tukino Tukino
Prosiding Vol 5 (2023): SNISTEK
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/psnistek.v5i.8118

Abstract

PT Semesta Citra Alam Batam is engaged in waste management and is located in the city of Batam. The waste collected by PT Semesta Citra Alam Batam is gathered at a waste collection warehouse located in the Industrial Waste Management Area of Batam City. The collected waste must be transported to waste utilization or hazardous waste disposal facilities. The data collection technique in this research is through observation and interviews conducted at PT Semesta Citra Alam Batam. The data analysis method used is fuzzy logic with the Sugeno method, which involves four stages: fuzzification, forming a fuzzy knowledge base, inference engine, and defuzzification. The research results from the application of fuzzy logic to determine the shipment of hazardous waste (B3 waste) at PT Semesta Citra Alam Batam involve both input and output variables. The input variables consist of load, content, and the output variable is a decision made using Matlab. These variables will generate rules that will be used to determine whether to send the waste or not.
Pelatihan Membangun Keunggulan Bersaing UMKM Melalui Pemasaran Online Di Kota Batam Tukino Tukino; Erlin Elisa; Algifanri Maulana; Yvonne Wangdra; Ronald Wangdra; Suvianto Wangdra
Prosiding Vol 5 (2023): SNISTEK
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/psnistek.v5i.8133

Abstract

The implementation of community service activities will take the form of Empowerment of E-Commerce-Based Marketing located at Rindang Garden Block B2 No. 04, Buliang Village, Batu Aji District, Batam. Based on the field interview results, the Small and Medium-sized Enterprises (UMKM) Rafflesia face challenges in marketing their products. In general, UMKM businesses have limitations in mastering information technology facilities and marketing media that are not well-known to the public. Conventional business owners feel that accounting recording is a cumbersome task. The training method used is to provide training through an online website. The methods used in the development of UMKM Rafflesia include survey methods, lecture methods, discussion methods, and training methods. The sustainability of the results of this coaching activity is expected to enable UMKM Rafflesia to manage online marketing effectively.
KLASIFIKASI DAN PREDIKSI ULASAN APLIKASI DANA PADA GOOGLE PLAY STORE MENGGUNAKAN ALGORITMA NAÏVE BAYES Hayati, Cucu; Tukino; Hilabi, Shofa Shofiah; Hananto, April Lia
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 7 No 2 (2025): EDISI 24
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v7i2.5691

Abstract

Di era digital saat ini, kemajuan teknologi yang pesat telah mendorong masyarakat beralih ke transaksi digital melalui financial technology (Fintech), salah satu inovasi fintech yaitu aplikasi DANA. Penelitian ini bertujuan untuk mengklasifikasi dan prediksi ulasan aplikasi DANA menggunakan Naïve Bayes. Dengan jumlah data 1.500 ulasan kemudian dilabeli berdasarkan kategori transaksi, keamanan, kinerja Aplikasi, pelayanan, serta aktivasi dan verifikasi. Tahapan penelitian ini dilakukan mulai dari pengumpulan data, pelabelan manual , preprocessing , pembobotan kata, model Naïve Bayes , dan evaluasi. Berdasarkan hasil analisis, tingkat akurasi yang diperoleh adalah sebesar 87%, dengan presisi mencapai 88%, recall sebesar 84%, dan f1-score sebesar 85%. Akurasi mengacu pada persentase prediksi yang benar dari keseluruhan data. Presisi menunjukkan seberapa tepat model dalam memprediksi suatu kelas tertentu, recall mengukur kemampuan model dalam menemukan seluruh data termasuk dalam suatu kelas tertentu, dan f1-score menggambarkan keseimbangan antara presisi dan recall. Maka, dapat disimpulkan model bawah pada penelitian ini mampu dalam mengklasifikasikan seluruh kategori dan dapat memberikan prediksi yang akurat, meskipun terdapat perbedaan nilai presisi, recall , dan f1-score . Diharapkan penelitian ini dapat bermanfaat bagi pengembang aplikasi DANA, dan juga dapat memberikan informasi mengenai efisiensi dan efektivitas algoritma Naïve Bayes dalam klasifikasi dan prediksi.
Penerapan Software Testing Life Cycle Pada Pengujian Otomatisasi Platform Dzikra Ruliansyah, Ruliansyah; Tukino; Baenil Huda; April Lia Hananto
CSRID (Computer Science Research and Its Development Journal) Vol. 15 No. 1: February 2023
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.15.1.2023.01-11

Abstract

PT Bejana Investidata Globalindo (BIGIO), as an IT consultant and software development company, develops an in-house product called Dzikra which is a platform to help users build good habits in worship. In order to develop this system, the company requires a daily worship content management system known as the Dzikra web admin. The Software Development Life Cycle (SDLC) has several stages, one of the important stages is the testing stage which has the goal of evaluating whether the software has been created in accordance with the specifications and detects bugs or errors. Black box testing automation with Robot Framework can provide good testing documentation and can reduce human errors during the testing process. The implementation of the Software Testing Life Cycle (STLC) in the testing process can also make the testing flow more structured and provide a better focus on each testing stage. The results of the testing show that of the six features tested, they have run as expected. It is hoped that this research will provide support to PT Bejana Investidata Globalindo (BIGIO) in automating software testing process.
Prediksi Penjualan Barang Menggunakan Metode K-Means dan Regresi Linear Henry Adam; Tukino; Elfina Novalia; Hananto, April Lia
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.541

Abstract

Sales data analysis plays an important role in supporting business decision making, especially to optimise stock management and improve operational efficiency. the main problem faced by Vapestore XYZ in Karawang is the difficulty in accurately predicting the number of product sales, so there is often an imbalance between inventory and market demand. This can cause losses due to overstocks or shortages of goods. Currently, the estimation of stock requirements still relies on intuition and personal experience, without the support of objective data analysis. This research aims to build a sales prediction model by combining the K-Means method for product clustering and Linear Regression for sales quantity prediction. Sales data is taken directly from the store POS application, then goes through the stages of cleaning, labelling, and clustering into three groups, namely ‘Less Sold’, “Sold”, and ‘Very Sold’. Sales prediction is performed using Linear Regression by utilising the clustering results and time variables as inputs. Model performance evaluation is performed using error metrics, namely Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE). Based on the test results, the developed Linear Regression model obtained MAE of 3.20, MSE of 52.34, and RMSE of 7.23. These error values indicate that the model is able to provide sales estimates that are close enough to the actual data to be reliable in stock planning. Visualisation of the prediction results in the form of tables and heatmaps makes it easy to identify sales trends and compare performance between products. The findings of this study prove that the combination of K-Means and Linear Regression methods is effectively used to support stock decision making and marketing strategies in vape retail stores. Further development is recommended by enriching the dataset and exploring other prediction methods to improve model performance.
Pengenalan Enterpreunership Multimedia Pada Santri Pondok Pesantren At-Taubah Tirta Mulya Agustia Hananto; Elfina Novalia; Tukino Tukino
Masyarakat Berkarya : Jurnal Pengabdian dan Perubahan Sosial Vol. 2 No. 2 (2025): Mei : Masyarakat Berkarya : Jurnal Pengabdian dan Perubahan Sosial
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/karya.v2i2.1384

Abstract

This community service activity aims to introduce the concept of multimedia entrepreneurship to students of the At-Taubah Tirta Mulya Islamic Boarding School, Karawang, in order to improve their knowledge and skills in utilizing multimedia as a tool for entrepreneurship. Held on March 2, 2024, this activity involved 50 students who attended lecture sessions, discussions, and multimedia content creation practices. The research method used was participatory action research, which allowed participants to be actively involved in the learning process. Data were collected through observation, interviews, and questionnaires to measure changes in knowledge before and after the activity. The results of the analysis showed a significant increase in students' understanding and skills related to multimedia entrepreneurship. The implications of this activity highlight the importance of collaboration between higher education institutions and Islamic boarding schools to create a creative and independent generation in the digital era.
Prediksi Barang Sering dan Jarang Terjual Dengan Menggunakan Algorithma K-Mean Clustering (Studi Kasus Toko Bina Mulia) Muhammad khaerudin; Imam Zaenuddin; Tukino
Journal of Informatic and Information Security Vol. 3 No. 1 (2022): Juni 2022
Publisher : Program Studi Informatika, Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/72dwrc41

Abstract

The rapid increase in the population in the buffer zone of the capital city has an effect on the lifestyle of the people in the area, including in the Bekasi district. Likewise, the growth of small and medium community businesses, one of which is the Bina Mulia cooperative shop. This study was made to determine which types of goods are often sold and which types of goods arerarely sold. The algorithm used is K-Means Clustering, where data grouped based on the same characteristics will be included in the same group and the data sets entered into the groups do not overlap. The information displayed is in the form of groups of product names and the amount sold in one week for two months, namely April and May as a sample. The results of this study will help the store in analyzing which types of goods are often sold and which are rarely sold. The software used to help this grouping is Rapid Miner.
Klasifikasi Sentimen Komentar Pengguna pada Aplikasi Ruangguru Menggunakan Algoritma Naive Bayes Yovika Aprianti; Tukino; Hananto, April Lia; Hilabi, Shofa Shofiah
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 1 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v9i1.1023

Abstract

The advancement of digital technology has encouraged the increasing use of online learning applications such as Ruangguru, while simultaneously fostering various innovations in the field of education. Ruangguru, as one of the most popular educational applications in Indonesia, receives thousands of user comments that can be analyzed to reflect user satisfaction and perception. This study aims to automatically classify user comments based on the sentiments they contain using the Naïve Bayes Classifier algorithm. This approach is expected to help Ruangguru developers better understand user needs and preferences, thereby improving service quality. The dataset was obtained from the Google Play Store platform, consisting of approximately 5,000 comments collected during the period from October 28 to December 31, using the google-play-scraper tool. The application of the Multinomial Naïve Bayes algorithm with TF-IDF weighting was employed to analyze the data, resulting in four sentiment categories: Baik Sekali, Baik, Cukup Baik, and Kurang Baik. Evaluation of the model was conducted using accuracy, precision, recall, and F1-score metrics. With an accuracy rate of 84.83%, the model correctly predicted the actual labels in approximately 85% of the test data. The model also achieved an F1-score of 85%, a precision of 86%, and a recall of 85%. The classification results revealed that the “Baik” category dominated with a proportion of 28.3%, followed by “Baik Sekali” at 24.3%, “Cukup Baik” at 24.0%, and “Kurang Baik” at 23.4%. These findings indicate that the model maintains a reasonable balance between sensitivity and accuracy in sentiment classification. Therefore, the Naïve Bayes Classifier method is capable of automatically identifying user opinions and has the potential to serve as a valuable tool in sentiment analysis for online learning services.
Co-Authors Abdul Latif Agustian, Adittia alfannisa annurrallah fajrin Alfannisa Annurrallah Fajrin Alfannisa Annurrullah Fajrin Alfannisa Annurullah Fajrin Alfannisa Fajrin Algifanri Maulana, Algifanri Algifari Maulana Ali Abrar Amrizal . Amrizal Amrizal Amrizal Amrizal Anggia Arista Anggia Dasa Putri April Lia Hananto Argo Putra Prima Arif Rahman Hakim Arif Rahman Hakim Arnomo, Sasa Ani Arsyad, Fachry Baenil Huda Bahariandi Aji Prasetyo Baru Harahap Bayu Priatna Bayu Yoga Astario Citra Indah Asmarawati Dede Kuswanda Dharmawan, Hafizh Dian Efriyenti Dian Efriyenti Difa Prakoso Fuadi, Muhammad Djumhadi Djumhadi Elisa, Erlin Elsya Tarigan Paskaria Loyda Tarigan Elva Susanti Erlin Elisa Fitria Nurapriani Hananto, Agustia Handoko, Koko Harman, Rika Hasanah, Haprilianh Hayati, Cucu Henry Adam Hibatullah, Muhammad Hafizh Hilabi, Shofa Shofiah Huban Kabir Huda, Baenil Ihsan, Mohammad Maftuh Ilham Fariz Asya Mubarok Imam Zaenuddin Jabar Sanjaya Juniardi Karniawulan, Ismi Lestari, Renita M Irhash Erlangga Meiti Subardhini Melisa Mildawati, Milly Muhamad Bayu Aditya Pratama Muhammad Khaerudin Muhammad Taufik Syastra NANDA HARRY MARDIKA Nofriani Fajrah, Nofriani Novalia, Elfina Nurafriani, Fitria Nurapriani, Fitria Olvia Nursaadah P, Shafira Putri Kusuma Priyatna, Bayu Purnomo, Andromedo Cahyo Ratna Juwita, Ayu Realize, Realize Rizki Prakasa Hasibuan Rohana, Tatang Rohman Nurafan Putra Pratama Ronald Wangdra Roza Yenita Ruliansyah Ruliansyah, Ruliansyah Sabrina Amanda Salsabila Saepul Aripiyanto Sama, Hendi Sandi Ahmad Shidiq, Faisal Shofa Shofia Hilabi Shofia Hilabi, Shofa Shofiah Hilabi, Shofa Silvana Nazuah Sri Watini Steven Famy Subarkah, Ade Surala, Lyvia Suvianto Wangdra Syaeful Akbar Syahril Effendi Tony Wibowo, Tony Versanudin Hekmatyar Wibisono, Eko Gunawan Widyanti, Tyas Winarni Winda Yohanna Siahaan Young, Filbert Yovika Aprianti Yvonne Wangdra Zulkifli, Mohamad