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All Journal Sainteks Techno (Jurnal Fakultas Teknik, Universitas Muhammadiyah Purwokerto) Jurnal Informatika JRST (Jurnal Riset Sains dan Teknologi) Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Teknologi Informasi dan Multimedia Jurnal E-Komtek Jurnal Sistem Komputer dan Informatika (JSON) Journal of Soft Computing Exploration Jurnal Pengabdian Teknik dan Sains (JPTS)
Dimara Kusuma Hakim
Universitas Muhammadiyah Purwokerto
Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Mechanical Engineering Medicine & Pharmacology

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Journal : Jurnal E-Komtek

 1 
Prakiraan Kecepatan Angin Menggunakan Metode Triple Exponential Smoothing di Pantai Pangandaran Hakim, Dimara Kusuma; Yuana Wangsa Putri Setiawan; Supriyono; Maulida Ayu Fitriani4
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 8 No 2 (2024)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v8i2.2243

Abstract

Indonesia as a maritime country with a long coastline, holds significant potential in the marine and tourism sectors. However, these sectors are often disrupted by adverse weather conditions, particularly irregular wind speeds. Accurate wind speed forecasting is therefore essential for disaster mitigation. This study aims to forecast wind speed at Pantai Pangandaran using the Triple Exponential Smoothing (TES) method, which is more effective in handling data fluctuations with trend and seasonal patterns. The data used includes daily data from January 2014 to September 2024. The results show that the TES method provides highly accurate forecasts, with a low error rate evaluated through an RMSE of 0.51 and a MAPE of 17.85% for wind speed. These forecasts are expected to support disaster mitigation, enhance safety, and improve the efficiency of activities in coastal areas, particularly at Pantai Pangandaran, in facing adverse weather conditions.
Optimization of Gamification Type Selection in Pop-Up Campaigns to Enhance Customer Engagement on E-Commerce Platform XYZ Using the Analytical Hierarchy Process Method Kesy Apriansyah; Hakim, Dimara Kusuma; Feri Wibowo; Supriyono
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 9 No 1 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v9i1.2265

Abstract

One of the key success factors in the e-commerce industry is the increase in consumer engagement. High engagement has been proven to drive sales growth and customer loyalty. To achieve this goal, the application of gamification in marketing campaigns has been shown to have a significant impact on customer engagement in e-commerce. This study aims to optimize the selection of gamification types in pop-up campaigns to enhance consumer engagement on the XYZ e-commerce platform. The selection of the right type of gamification is crucial, but it is often influenced by subjectivity in assessment. To that end, this research uses the Analytic Hierarchy Process (AHP) method, which integrates historical data as a reference in filling alternatives based on criteria to reduce the subjectivity of the AHP method in determining the most effective type of gamification based on the criteria of Click-Through Rate (CTR), Conversion Rate (CR), and Impression. The research results show that the Memory Card type of gamification is the most effective type with the potential to increase consumer engagement. This approach is expected to serve as a reference for e-commerce platforms in designing more effective and data-driven gamification strategies.
Optimization of Double Exponential Smoothing Model for Daily Earth Temperature Forecasting in Dayeuhluhur, Cilacap Ridzna Asep Purwanto; Hakim, Dimara Kusuma; Supriyono; Harjono
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 9 No 1 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v9i1.2396

Abstract

Global warming has caused an increase in the Earth's surface temperature, which has a significant impact on the environment and human life. This study aims to predict the daily surface temperature in Dayeuhluhur District, Cilacap, for the next one year using the Double Exponential Smoothing (DES) method. The data used comes from the NASA POWER platform with a time span of 2015 to 2025, including three main variables: earth surface temperature (TS), solar radiation (ALLSKY_SFC_SW_DWN), and maximum 10-meter wind speed (WS10M_MAX). Preprocessing was done by removing February 29 in leap years and applying annual differencing (lag 365) to stabilize the seasonal pattern. Smoothing parameters α and β were optimized based on Mean Absolute Percentage Error (MAPE) values. Results show a moderate and consistent increasing trend in temperature, with the best accuracy in the temperature variable (MAPE 2.41%), followed by solar radiation (21.56%) and wind speed (30.18%). This method proves effective in forecasting temperature with clear seasonal patterns and contributes to supporting data-driven climate change mitigation policies.
Clustering of Earthquakes on The Island of Java Using K-Means Algorithm Based on Magnitude and Depth Viki Flendiansyah; Hakim, Dimara Kusuma; Feri Wibowo; Agung Purwo Wicaksono
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 9 No 1 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v9i1.2397

Abstract

Indonesia is one of the countries with a high level of earthquake vulnerability because it is located in the Pacific Ring of Fire. Java Island, as the most populous region and the center of the national economy, has a great risk of earthquake impacts. This study aims to analyze earthquakes in Java Island during the 2019-2024 period using the K-Means algorithm. Clustering the data based on magnitude, depth, location, and time of occurrence resulted in three clusters that reflect the characteristics of earthquakes in the region. This clustering provides important insights into the distribution and intensity of earthquakes in Java. The information obtained can be used to support disaster mitigation efforts more strategically. The government and community are expected to be able to increase preparedness for disaster risks and design effective mitigation policies to minimize the impact of future earthquakes. This research shows the great potential of applying data-driven technology as a basis for decision-making in disaster mitigation in Indonesia.
An Analysis and Forecasting of Electricity Demand Using the Triple Exponential Smoothing Method Aulia Nur Aini; Hakim, Dimara Kusuma; Feri Wibowo; Elindra Ambar Pambudi
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 9 No 1 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v9i1.2483

Abstract

Electricity is a basic necessity required in daily life, supporting various activities, including economic development. The growing demand for electricity requires reliable and efficient planning and management of the power system. Electricity demand forecasting is essential due to its fluctuating nature and seasonal patterns. This study aims to forecast electricity demand using the Triple Exponential Smoothing method with data from the Australian Energy Market Operator (AEMO) for the New South Wales region, Australia, covering the period from January 2015 to February 2025. This method is chosen because it effectively handles time series data patterns consisting of level, trend, and seasonal components. The forecasting results show that this method is capable of closely following the actual data patterns and produces a Mean Absolute Percentage Error (MAPE) of 2.89%, indicating a very good performance. This model is expected to serve as a basis for decision-making in anticipating future fluctuations in electricity demand.
Forecasting Water Pollution in Cengklik Reservoir Using Triple Exponential Smoothing Method Nooriza Modistira Sakti; Hakim, Dimara Kusuma; Elindra Ambar Pambudi; Maulida Ayu Fitriani
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 9 No 1 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v9i1.2414

Abstract

Water quality is a crucial element for the sustainability of ecosystems and human life, yet it is often threatened by pollution resulting from human activities. Cengklik Reservoir in Boyolali Regency has shown increasing levels of pollution influenced by domestic waste, agricultural fertilizers, and residual fish feed from Floating Net Cages (KJA). This study aims to predict water pollution levels to support more effective management efforts by applying the Triple Exponential Smoothing (TES) method to pollution index data from 2016 to 2023. The forecasting results reveal a clear seasonal pattern, with a Mean Absolute Percentage Error (MAPE) of 34.36%, indicating a moderately good level of accuracy. These findings suggest that TES is capable of identifying general pollution patterns, although further approaches are needed to fully capture the dynamics of water pollution. As a follow-up, the study recommends optimizing the number and placement of KJA units, improving waste management, and implementing community education programs to preserve water quality and ensure the sustainability of the reservoir ecosystem.
Analytical Hierarchy Process (AHP) untuk Zona Kerentanan Tanah Longsor di Daerah Gumelar Reza Fahmi Pahlevi; Hakim, Dimara Kusuma; Tito Pinandita; Muhammad Hamka
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 9 No 2 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v9i2.2556

Abstract

Landslides are geological disasters that frequently occur in areas with steep topography and minimal vegetation, including in Gumelar Subdistrict, Banyumas Regency. This study aims to map landslide vulnerability zones using a multi-criteria approach with the Analytical Hierarchy Process (AHP) method integrated into a Geographic Information System (GIS). Four main parameters analyzed include slope gradient, rainfall, lithology, and land cover, with weights determined through a pairwise comparison matrix by experts. The results indicate that slope gradient (49.2%) and rainfall (30.9%) are the dominant factors in determining vulnerability levels. The resulting vulnerability map shows the distribution of areas with low, moderate, and high risks, validated using field landslide event data. This study provides an accurate spatial basis for landslide disaster mitigation planning in the study area
Co-Authors Abid Yanuar Badarudin Achmad Fauzan Achmad Fauzan Agung Purwo Wicaksono Anggi Restu Perdana Aulia Nur Aini Dwi Yoga Yulianto elindra ambar pambudi Elindra Ambar Pambudi Ermadi Satriya Wijaya Feri Isnanto Feri Wibowo Fitriani, Maulida Ayu Harjono Hidayahtullah, Muhammad Iqbal Hidayat Abdul Aziz Hindayati Mustafidah Johan Kun Riyanto Kesy Apriansyah Maulida Ayu Fitriani Maulida Ayu Fitriani4 Muhammad Hamka Nooriza Modistira Sakti pambudi, elindra ambar Reza Fahmi Pahlevi Ridzna Asep Purwanto Saputri, Devi Septian Adi Nugroho Sigit Sugiyanto Sigit Sugiyanto SUPRIYONO Tito Pinandita Tito Pinandita Viki Flendiansyah Widyantri, Shafrila Yuana Wangsa Putri Setiawan