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All Journal Jurnal Algoritma Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) Sinkron : Jurnal dan Penelitian Teknik Informatika Seminar Nasional Teknologi Informasi Komunikasi dan Industri Jurnal Ilmiah Matrik Jurnal Eksplora Informatika JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Voice Of Informatics Jurnal Sistem Cerdas CSRID (Computer Science Research and Its Development Journal) SENSITEK E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi IT (INFORMATIC TECHNIQUE) JOURNAL Aiti: Jurnal Teknologi Informasi Jurnal Scientia Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Jurnal Teknik Informatika (JUTIF) Informatics and Digital Expert (INDEX) Jurnal Kewarganegaraan Jurnal PkM MIFTEK Jurnal Algoritma Jurnal Teknologi Informasi
Yoga Handoko Agustin
Institut Teknologi Garut
Religion Aerospace Engineering Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Journal : Jurnal Algoritma

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Algoritma Regresi Linier Dalam Prediksi Jumlah Pendaftar Program Pendidikan Di Lingkungan Pesantren : Studi Kasus : Yayasan Al-Mustofa Tambakbaya Agustin, Yoga Handoko; Satria, Eri; Nasrulloh, Anas
Jurnal Algoritma Vol 22 No 1 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-1.1802

Abstract

Al-Mustofa Tambakbaya Foundation manages an Islamic boarding school as well as a Madrasah Aliyah (MA) and Madrasah Tsanawiyah (MTS). Over the past five years, the foundation has experienced fluctuations in the number of new students. This study aims to predict the number of applicants using a linear regression algorithm. The challenge of fluctuating enrollment affects resource planning and curriculum development. The data used includes the number of MA and MTS students from the 2019 to 2023 academic years. This research follows the CRISP-DM stages, starting from business understanding, data collection and preparation, to modeling using linear regression. Model evaluation is done with MAPE, MAE, RMSE, and R-squared. The results show that the model for Regional Domicile and Outside the Region has a MAPE of 8.44% and 12.76%, respectively. The model for MTS students has a MAPE of 6.26% and an R-squared of 91.27%, while the MA student model shows the lowest performance with a MAPE of 20.56% and an R-squared of 21.20%. Predictions for the 2024 academic year show significant growth, especially in regional domicile and MA students. This research offers a practical solution to address fluctuations in enrollment and educational planning at Al-Mustofa Tambakbaya Foundation, as well as highlighting the need for model improvements to increase accuracy in the future.
Prediksi Jumlah Pengunjung Pariwisata di Kabupaten Garut Menggunakan Algoritma Regresi Linear Agustin, Yoga Handoko; Satria, Eri; Siti Nursifa, Fadia
Jurnal Algoritma Vol 22 No 1 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-1.1807

Abstract

Tourism has great potential in driving economic growth through job creation, income enhancement, and positive impacts on various related sectors such as handicrafts, accommodation, and transportation. Garut Regency, located in the southern part of West Java Province, is increasingly recognized for its natural tourist destinations that remain unspoiled and attract many visitors. However, the surge in visitor numbers at these destinations has posed several challenges, including overcrowding that reduces comfort and safety, as well as a decline in service quality due to high demand. Inadequate infrastructure, such as transportation and parking facilities, is also an issue that needs to be addressed. To assist the local government in preparing for future increases in visitor numbers, this study utilizes the Linear Regression algorithm to predict the number of tourist visits to Garut Regency. This algorithm is chosen for its ability to measure the relationship between the dependent variable (number of visitors) and independent variables (factors influencing visits). Data collection is carried out by grouping the number of visitors based on tourist categories, resulting in more accurate and relevant prediction models. The research findings show that the linear regression model can generate predictions with a Mean Absolute Error (MAE) of 11,406.37, Mean Absolute Percentage Error (MAPE) of 6.449, Mean Squared Error (MSE) of 282,815,506.30, and Root Mean Squared Error (RMSE) of 16,817.12. The R-squared (R²) value of 0.9346 indicates that the model can explain approximately 93.46% of the data variance, demonstrating good predictive performance. However, the relatively high MAPE value indicates inconsistencies in the dataset, likely caused by very small or zero actual values. This prediction is expected to assist the Garut Regency Tourism Office in strategic planning and decision-making, such as infrastructure preparation, service quality improvement, and tourism promotion planning. This study also opens up opportunities for further development using other prediction algorithms to achieve more optimal results.
Pemetaan Toko Komputer Berbasis Web di Kabupaten Garut Fitriani, Leni; Agustin, Yoga Handoko; Fauzi, Bayu Muhammad
Jurnal Algoritma Vol 20 No 2 (2023): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.20-2.1304

Abstract

A computer shop is a place that sells equipment related to computers. As technology advances, people's needs for computer shop locations are also increasing. Computer shops themselves not only sell various computer needs such as hard disks, Random Access Memory, and accessories such as mice and keyboards, some computer shops also sell products in the form of services such as computer servicing, computer assembly, installing software, and buying and selling used computers. Currently, information about computer shops only consists of explanations about the shop and mapping of computer shop location points, there is no information based on completeness categories in the form of product services, computer accessories, computer buying and selling. This means that the public or potential consumers do not know much about the location and search for computer shops in the city of Garut. Because the level of public need for the availability of goods and services will be very necessary, an application system is needed that can help increase store sales and the needs of the public as consumers. The aim of this research is the design and development of web-based computer shop mapping in Garut Regency. The methodology used to design this application is Rational Unified Process (RUP) with several stages of inception, elaboration, construction, and using Unified Modeling Language (UML) modeling. The results of this research are a geographic information system mapping computer shops to help make it easier for users or potential consumers to choose a complete computer shop and recommended computer shop.
Penerapan Algoritma K-Means Untuk Pengelompokan Kepadatan Penduduk Berdasarkan Kecamatan di Kabupaten Garut Agustin, Yoga Handoko; Nur Faisal, Ridwan
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.1909

Abstract

Indonesia faces challenges of uneven population distribution, including in Garut Regency, which has a population of 2,585,607 people. This disparity leads to overcrowding issues in several areas. This study aims to cluster population density based on districts using the K-Means algorithm and the CRISP-DM (Cross-Industry Standard Process for Data Mining) approach. CRISP-DM consists of six main stages: business understanding, data understanding, data preparation, modeling, evaluation, and deployment, which are systematically applied in this research. The data used was obtained from the Central Bureau of Statistics of Garut Regency in 2023, covering population numbers and the area of each district. At the modeling stage, the K-Means algorithm is applied to group districts based on population density similarity. The optimization of the number of clusters was carried out using the elbow method, resulting in the optimal number of three clusters (k=3). Evaluation using the Davies-Bouldin Index (DBI) yielded a value of 0.5794, indicating that the clusters formed have good separation. The clustering results show that cluster 0 includes districts with high density, cluster 1 with medium density, and cluster 2 with low density. The results of this study have the potential to be implemented in regional development planning, assisting the Central Bureau of Statistics (BPS) of Garut Regency and related agencies in formulating policies for equitable development, public service distribution, and more effective infrastructure planning. With population density mapping based on data mining, policies can be more evidence-based, enabling better decision-making in addressing demographic issues in Garut Regency.
Prediksi IHSG Dengan Algoritma Autoregressive Integrated Moving Avarage (ARIMA) Ibrahim, Roby; Agustin, Yoga Handoko
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.1963

Abstract

Capital market development is one of the main indicators of a country's economy. Therefore, the ability to predict the movement of the Composite Stock Price Index (JCI) is very important for investors and capital market players. The purpose of this research is to develop a JCI model using the Autoregressive Integrated Moving Average (ARIMA) algorithm with the support of RapidMiner software. Simulation test results show that the ARIMA model can be a useful tool for investors and market researchers to make more meaningful decisions. The research methodology used is CRISP-DM (Cross-Industry Standard Process for Data Mining) which includes the following steps: First, collecting historical JCI data from the relevant period. Second, analyze the time series to understand the characteristics of JCI. Third, applying the ARIMA model with parameters (p;2, d;1 q;2) with MSE 2461.572, using statistical analysis methods and evaluating model performance. Fourth, run the ARIMA model on Colabolatory software to predict JCI activity. Fifth, evaluate model performance using metrics. The results of this study have successfully created the best ARIMA model implemented with Colabolatory and can provide accurate information. This research produces a prediction model with evaluation metrics of RMSE 1.43 and MAE 1.13.
Co-Authors Ade Sutedi Adha, Sherly Nabila Afifah, Via Nur Andi Fikri Nugraha Andi Sanjaya Andyarini, Ervina Dwi Anggi Rihadisha Anisa Devisa Putri Arbi Yuan Aspahany Asep Sugiharto Asgara, Zidan Asri Mulyani Aulia, Husni Ayu Latifah B. Balilo Jr , Benedicto Baswardono, Wiyoga Cahya Setia Ningrum, Asni Cici Mulyani, Neng Dani Rohpandi Dede Kurniadi Dendi Ramdani Deni Heryanto Ditdit Putuwenda Egi Badar Sambani, Egi Badar Eni Suryeni, Eni Eri Satria Evi Dewi Sri Mulyani Fahmi Fadlillah Falah Insan Pratama Fauzi, Bayu Muhammad Firmanto, Alam Fitri Nuraeni Hari Ilham Nur Akbar HELFY SUSLAWATI Ibrahim, Roby Ida Farida Imas Dewi Ariyanti Indri Tri Julianto Intan Hartanti Rahman Ningsih Iwan Setiawan Jungjunan, Aditya Rahma Kusrini, Kusrini Kustiana, Ruli M Leni Fitriani Leni Fitriani, Leni Luthfi, Emha Taufiq Marlina, Rina Miftahul Hidayat, Miftahul Mohamad Fikri Haekal Muhammad Farhan Muhammad Ramdan Rahmatillah Muhammad Rikza Nashrulloh Multajam, Sri Intan Nabil Nur Afrizal Nasrulloh, Anas Nensi Mardhiani Surgawi Nisa, Ziadatun Khoirun Nugraha, Insan Satia Nur Faisal, Ridwan Nur'aeni, Irma Oktapiani, Vini Pratama, Fajri Rahayu, Raden Erwin Gunadi Raisman Raisman Ridwan Setiawan Ridwan Setiawan Ridwan Setiawan Rika Lestari Shinta Siti Sundari Sidiq, Repi Fahmi Sindu Prasetya, Wahyu Siti Nursifa, Fadia Sopandi, Pendi Sri Fitrya Kamellia Sri Rahayu Sri Sulastri Srihermaning, Nova _ Susanto Susanto Wahyu Sindu Prasetya Wildan Nugraha Wiyoga Baswardono Yosep Septiana Yuli Nurfitria, Yuli Yusuf Abdul Fatah