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Pengembangan Aplikasi Berbasis Android Untuk Sistem Kesejahteraan Sosial Terpadu Kesejahteraan Sosial Kabupaten Jember Maidah, Nova El; Juwita, Oktalia; Pandunata, Priza; Zarkasi, Mohammad; Nine Amalia, Karina; M Firmansyah, Diksy
TEKIBA : Jurnal Teknologi dan Pengabdian Masyarakat Vol. 2 No. 2 (2022): TEKIBA : Jurnal Teknologi dan Pengabdian Masyarakat
Publisher : Fakultas Teknik, Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/tekiba.v2i2.2262

Abstract

Validation of the Integrated Social Welfare Data (DTKS) needs to be carried out because the government uses this data as a basis for providing various forms of social assistance. Valid data is one of the efforts so that the social assistance provided is right on target. Jember Regency is one of the districts instructed to validate the data. The University of Jember through the Institute for Research and Community Service (LP2M) is working with the Regional Government of Jember Regency to carry out DTKS validation efforts. This activity then developed an Android-based application that enumerators used to validate in the field. The data used in the application is based on data already owned by the Jember District Social Service
SEGMENTASI PELANGGAN DAN PENARGETAN PEMBELI DENGAN MENGGUNAKAN METODE K-MEANS CLUSTERING: STUDI KASUS INDUSTRI REAL ESTATE Razanah, Muhammad Rashif; Pandunata, Priza
Melek IT : Information Technology Journal Vol. 11 No. 1 (2025): Melek IT: Information Technology Journal
Publisher : Informatics Department-Universitas Wijaya Kusuma Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30742/melekitjournal.v11i1.382

Abstract

Penelitian ini bertujuan untuk menganalisis segmentasi pelanggan dan penargetan pembeli dengan menggunakan metode K-Means Clustering pada industri real estate. Penelitian ini mengambil kasus PT Sembilan Bintang Lestari yang menghadapi tantangan dalam memahami karakteristik pelanggan secara mendalam. Data pelanggan dianalisis dengan pendekatan CRISP-DM melalui tahapan pemahaman bisnis, pemahaman data, persiapan data, pemodelan, dan evaluasi. Hasil segmentasi menggunakan algoritma K-Means dengan metode Elbow menunjukkan bahwa tiga cluster merupakan jumlah yang optimal. Setiap klaster dianalisis berdasarkan variabel usia, pendapatan, pekerjaan, tipe rumah, metode pembayaran, dan status pernikahan. Visualisasi data membantu mengidentifikasi pola pelanggan di dalam setiap klaster, yang digunakan untuk merancang strategi penargetan pembeli yang lebih efektif. Penelitian ini berkontribusi dalam meningkatkan efisiensi pemasaran melalui pendekatan berbasis data, yang diharapkan dapat membantu PT Sembilan Bintang Lestari dalam meningkatkan daya saingnya di pasar properti.
Comparative Analysis of LSTM, GRU and Meta Prophet Stock Forecasting Methods with Var-Es Risk Evaluation Wijaya, Anggito Karta; Pandunata, Priza; Hidayat, Muhamad Arief
Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) 2025: SNESTIK V
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/p.snestik.2025.7259

Abstract

This study compares the performance of Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Prophet models in predicting real estate stock prices on the Indonesia Stock Exchange (2019–2024) and evaluates investment risks using Value at Risk (VaR) and Expected Shortfall (ES). Historical stock data underwent normalization and dataset splitting (ratios of 70:30, 80:20, and 90:10), with time steps of 40, 60, and 100, and three dense layers (25 and 50 neurons). Performance was evaluated using MSE, RMSE, MAE, and MAPE. Results indicate that GRU achieved the highest accuracy, especially for PWON, ASRI, and DILD stocks, with the lowest MSE values (PWON: 120.7436, ASRI: 26.3150, DILD: 28.9713). LSTM showed competitive performance, while Prophet had the lowest accuracy for short-term predictions. Risk analysis revealed Prophet had the lowest historical risk but the highest risk for 150-day forecasts. LSTM demonstrated superior long-term risk mitigation. Comparison with actual prices revealed that LSTM and GRU more accurately captured stock price fluctuations than Prophet, particularly during sharp price changes. GRU provided the closest predictions in the 150-day forecast scenario, making it the most effective model for real estate stock forecasting. This study offers valuable insights for investors and portfolio managers in understanding stock price movements and managing investment risks in the real estate sector.
Implementasi K-Means dalam Segmentasi Pelanggan Usaha Aluminium dan Kaca Berdasarkan Perilaku Pembelian Ramadhani, Salsabilla; Pandunata, Priza; Arifin, Fajrin Nurman
Jurnal Teknik Informatika dan Sistem Informasi Vol 11 No 2 (2025): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v11i2.9533

Abstract

— Mulia Jasa Aluminium dan Kaca is a business in the retail and service sector, offering Aluminium and glass materials and services for manufacturing, installation, and repair. Currently, competition in this field is quite intense, leading the business owner to admit difficulties in increasing sales. Therefore, the business owner needs to implement marketing and service strategies to boost sales. However, the diversity of customers with varying characteristics and behaviors makes it challenging to establish effective marketing and service strategies. Thus, this study conducts customer segmentation based on purchasing behavior. The aim is to understand customer behavior and loyalty using sales report data from the business. The variables used to assess a customer's value are Length, Recency, Frequency, and Monetary (LRFM). These variables are grouped using the K-means clustering algorithm. The objective of this study is to group customers based on their purchasing behavior, thereby assisting the business in developing more effective marketing and service strategies, enhancing customer satisfaction, and ultimately increasing sales and loyalty. Using the Silhouette method to determine the optimal number of clusters, three customer groups were identified, with the highest coefficient value of 0.663063. Cluster 0 is the “Lost Customer Group”, Cluster 1 is the “New Customer Group”, and Cluster 2 is the “Core Customer Group”.  
Pelatihan Pemrograman Visual Kodular Bagi Siswa SMPS Mitra Patrang Jember Furqon, Muhammad Ariful; Hidayat, Muhamad Arief; Pandunata, Priza; Zarkasi, Mohammad; Nurdiansyah, Yanuar; Leba, Katarina
Abdiformatika: Jurnal Pengabdian Masyarakat Informatika Vol. 4 No. 1 (2024): Mei 2024 - Abdiformatika: Jurnal Pengabdian Masyarakat Informatika
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/abdiformatika.v4i1.211

Abstract

Pelatihan pemrograman visual menggunakan platform Kodular di SMPS Mitra Patrang Jember bertujuan untuk meningkatkan pemahaman siswa terhadap konsep pemrograman komputer. Metode yang digunakan dalam kegiatan pengabdian ini mencakup: (1) spesifikasi tujuan dan identifikasi masalah; (2) desain pelatihan; (3) implementasi pelatihan; serta (4) evaluasi dan umpan balik. Desain pelatihan yang terstruktur melibatkan partisipasi siswa dalam serangkaian sesi yang mencakup konsep dasar pemrograman visual dan penggunaan platform Kodular. Hasil menunjukkan peningkatan signifikan dalam pemahaman siswa setelah pelatihan, dengan mayoritas menyatakan kepuasan dan minat yang tinggi. Pelatihan ini efektif dalam meningkatkan pemahaman pemrograman visual dan merangsang minat siswa dalam teknologi. Studi ini memberikan kontribusi penting dalam memperluas pemahaman tentang pendekatan pembelajaran inovatif dalam konteks pendidikan sekolah menengah.
UI/UX Design of Waste Management Application Using Design Thinking Method Saraswati, Devy; Adnan, Fahrobby; Pandunata, Priza
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.2845

Abstract

Anyelir Waste Bank is one of the waste banks assisted by PLN's Jakarta Main Distribution Unit which is located in East Jakarta Regency. Ongoing activities are still carried out manually, resulting in various problems. Therefore, the role of technology is needed to overcome problems related to waste management through scientific media designing the fields of User Interface (UI) and User Experience (UX) by designing waste management applications using design thinking. Design thinking was chosen because it combines priorities based on user needs with appropriate technological capabilities and business needs. Application design is designed on a mobile platform for customers while management is on a website platform. This research produces solutions for application design and usability testing has been carried out. Usability testing according to the ISO 9241-11 standard includes aspects of effectiveness, efficiency and satisfaction. In carrying out usability testing to measure aspects of effectiveness and efficiency using task scenarios, while to measure aspects of satisfaction using System Usability Scale (SUS).
Analisi Data Eksploratori Kritis untuk Dataset Prediksi Stroke Ariful Furqon, Muhammad Arif; Najwa, Nina Fadilah; Zarkasi, Mohamad; Pandunata, Priza; Fajariyanto, Gama Wisnu
Jurnal Komputer Terapan Vol 10 No 1 (2024): Jurnal Komputer Terapan
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35143/jkt.v10i1.6307

Abstract

Stroke is a significant global health concern, requiring an in-depth understanding of the complex factors contributing to its occurrence. Age, body mass index (BMI), and average glucose levels are critical factors in stroke etiology. This study employed exploratory data analysis techniques to investigate the relationships between variables in a stroke prediction dataset. The research methodology included (1) dataset description, (2) data preprocessing, (3) exploratory data analysis, and (4) interpretation. Descriptive statistical analysis provided insights into the dataset's composition and variability, while data preprocessing techniques handled missing values and facilitated feature extraction. Based on exploratory data analysis, significant relationships were found between age, hypertension, heart disease, average glucose levels, and stroke. However, BMI showed a less significant role in stroke. These findings contribute to a better understanding of the factors contributing to stroke risk and may aid in developing more effective prevention strategies.
Case Based Reasoning for Diagnosing Tuberculosis (TB) Saputri, Yunita Maulida; Nurdiansyah, Yanuar; Pandunata, Priza
Journal of Informatics Development Vol. 4 No. 1 (2025): Oktober 2025
Publisher : Institut Teknologi dan Bisnis Widya Gama Lumajang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30741/jid.v4i1.1759

Abstract

Tuberculosis, often referred to as TB, is a contagious disease caused by the bacterium Mycobacterium tuberculosis. TB primarily affects the lungs but can also affect other organs, a condition known as Extra-pulmonary TB. The disease is transmitted through the air, with the source of transmission being individuals with TB who are Acid-Fast Bacilli (AFB) positive and who sneeze or cough, releasing the bacteria into the air in the form of sputum droplets. TB can affect anyone. This research utilizes the Case- Based Reasoning (CBR) method to aid in the diagnosis of Tuberculosis. The diagnostic process involves inputting or selecting a new case that contains the symptoms to be diagnosed within the system. Then, the system calculates the similarity values between the new case and the cases stored in the case base using the Nearest Neighbor algorithm, normalized with the level of expert confidence. Testing was conducted using 50 cases from the case base and 38 new cases. The results of the system testing, using patient medical records and data obtained from literature studies, with diagnoses validated by experts, demonstrate that the system is capable of identifying 12 types of Tuberculosis with an accuracy rate of 92.3%.
Penerapan Metode AHP–Borda dalam Menentukan Peminatan Siswa SMA Negeri Balung Fajarianto, Gama Wisnu; Pradana Febrian Murtadlo; Pandunata, Priza; Wijonarko, Dwi
Jurnal Transformasi Digital Masyarakat (DIGIMAS) Vol. 1 No. 3 (2025): DIGIMAS: Transformasi Digital Masyarakat
Publisher : Fakultas Ilmu Komputer, Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/digimas.v1i3.6424

Abstract

Peminatan siswa merupakan bagian penting dalam sistem pendidikan menengah atas untuk memastikan peserta didik belajar sesuai dengan kemampuan akademik dan minatnya. Di SMA Negeri Balung, Kabupaten Jember, peminatan masih dilakukan secara konvensional dengan mempertimbangkan nilai rapor dan angket minat, sehingga rentan menimbulkan subjektivitas dan ketidakakuratan. Kegiatan pengabdian ini bertujuan untuk memperkenalkan sistem pendukung keputusan berbasis metode Analytical Hierarchy Process (AHP) dan Borda sebagai alternatif penentuan peminatan siswa. Data penelitian mencakup 390 siswa kelas XI dengan empat kriteria utama, yaitu nilai rapor, hasil tes psikologi, minat kelas, dan minat kuliah. Data diolah menggunakan aplikasi berbasis Python, sedangkan hasil peminatan dibandingkan dengan metode konvensional melalui analisis korelasi Pearson. Hasil menunjukkan sistem AHP–Borda memiliki akurasi 96% dengan korelasi Pearson 0,9396 (sangat kuat), sedangkan metode konvensional hanya 64% dengan korelasi 0,3429 (lemah). Hasil sistem kemudian disampaikan kepada pihak sekolah disertai penjelasan mengenai perbedaan dengan metode konvensional. Guru menilai sistem lebih cepat, konsisten, dan transparan sehingga bermanfaat sebagai alat bantu pengambilan keputusan. Dengan demikian, sistem ini dapat mendukung proses peminatan siswa secara lebih objektif dan akuntabel.