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Pelatihan Sistem Akuntabilitas Kinerja Instansi Pemerintah berbasis Elektronik kepada Organisasi Perangkat Daerah Pemerintahan Banjarnegara Dimara Kusuma Hakim
Jurnal Pengabdian Teknik dan Sains (JPTS) Vol 4, No 1 (2024): Januari 2024
Publisher : Lembaga Publikasi Ilmiah dan Penerbitan (LPIP)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/jpts.v4i1.21307

E-SAKIP, atau Sistem Akuntabilitas Kinerja Instansi Pemerintah, dibangun sebagai respons terhadap tuntutan transparansi dan akuntabilitas dalam kinerja instansi pemerintah. Dalam era digital saat ini, masyarakat semakin menuntut transparansi dan akuntabilitas dari pemerintah dalam menjalankan tugas dan fungsinya. Oleh karena itu, pemerintah merespons tuntutan ini dengan membangun E-SAKIP, sebuah sistem yang memungkinkan masyarakat untuk memantau dan mengevaluasi kinerja instansi pemerintah secara elektronik. Dalam rangka pelaksanaan AKIP, dilakukan pelatihan dengan tujuan untuk meningkatkan pemahaman dan keterampilan aparatur pemerintah daerah dalam melakukan pemantauan dan evaluasi kinerja instansi pemerintah daerah, untuk pemantauan dan evaluasi kinerja instansi pemerintah daerah dalam rangka mengukur capaian tujuan, sasaran, indikator, target, dan strategi yang telah ditetapkan dalam perencanaan pembangunan daerah. Metode yang digunakan dalam pelatihan ini adalah difusi ilmu pengetahuan dan teknologi (DIPT), yaitu suatu proses penyebaran dan penerapan ilmu pengetahuan dan teknologi yang melibatkan interaksi antara sumber, saluran, dan penerima. DIPT dilakukan melalui empat tahap, yaitu: (1) penyadaran, (2) penilaian, (3) adopsi, dan (4) penguasaan. Dalam setiap tahap, peserta pelatihan mendapatkan informasi, demonstrasi, latihan, dan bimbingan dari para narasumber yang berkompeten di bidangnya. Kesimpulan dari pelatihan ini adalah bahwa kegiatan pelatihan telah dilaksanakan dengan baik dan sesuai dengan tujuan yang diharapkan. Peserta pelatihan merasa mendapatkan manfaat dari pelatihan ini dan berkomitmen untuk menerapkan ilmu dan keterampilan yang didapat di instansi masing-masing. Pelatihan ini juga diharapkan dapat memberikan kontribusi positif bagi peningkatan kualitas pelayanan publik dan pembangunan daerah.

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

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.

Rainfall forecasting using triple exponential smoothing for rice cultivation in lamongan, jawa timur Widyantri, Shafrila; Hakim, Dimara Kusuma; Pambudi, Elindra Ambar; Fitriani, Maulida Ayu
Journal of Soft Computing Exploration Vol. 6 No. 1 (2025): March 2025
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v6i1.519

Rice cultivation is a major agricultural activity that is heavily influenced by weather conditions. Extreme weather events, such as heavy rainfall, can cause farmers' productivity to decline. Rainfall forecasts are important for farmers to help them make the right decisions in managing their farming businesses. This research aims to predict rainfall in Lamongan Regency, East Java province, and provide valuable information to rice farmers to plan the optimal planting season. The method used in this study is Triple Exponential Smoothing (TES), an effective forecasting technique for processing time series data with seasonal patterns. Monthly rainfall data for the last five years formed the basis of the forecast, with data sourced from NASA's Power Data Access Viewer. The analysis results include a Mean Absolute Percentage Error (MAPE) value of 97.559% for rainfall. This rainfall forecast can assist farmers in increasing rice productivity and minimizing the risk of crop failure due to unpredictable weather conditions. With the rainfall weather forecast, farmers are expected to know the suitable months for rice cultivation so that productivity increases

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

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

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

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.

Segmentasi Provinsi di Indonesia Berdasarkan Akses Fasilitas Dasar dan Pengeluaran Rumah Tangga Menggunakan K-Means Saputri, Devi; Mustafidah, Hindayati; Wibowo, Feri; Hakim, Dimara Kusuma
Jurnal Sistem Komputer dan Informatika (JSON) Vol 6, No 4 (2025): Juni 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v6i4.8630

Pemerataan akses terhadap fasilitas dasar dan peningkatan kesejahteraan masyarakat di Indonesia masih menjadi tantangan besar, khususnya antarprovinsi. Meskipun dalam satu dekade terakhir telah terjadi kemajuan pembangunan, ketimpangan antarwilayah masih tampak nyata. Ketimpangan ini tercermin dari perbedaan signifikan dalam akses terhadap air minum layak, sanitasi, listrik, tempat tinggal yang layak, serta pengeluaran rumah tangga per kapita per bulan. Penelitian ini bertujuan untuk mengelompokkan 34 provinsi di Indonesia berdasarkan indikator akses terhadap fasilitas dasar dan pengeluaran rumah tangga guna mengidentifikasi pola ketimpangan pembangunan wilayah. Metode yang digunakan adalah algoritma K-Means Clustering dengan variabel mencakup kepemilikan rumah, akses air minum layak, sanitasi, listrik, penggunaan gas, serta pengeluaran rumah tangga yang berkaitan dengan fasilitas tersebut. Hasil segmentasi menunjukkan terbentuknya dua klaster: Klaster 1 terdiri dari 29 provinsi dengan akses yang lebih baik terhadap fasilitas dasar dan tingkat pengeluaran rumah tangga yang lebih tinggi, namun dengan tingkat kepemilikan rumah yang relatif lebih rendah. Klaster 2 mencakup 5 provinsi dengan akses terbatas terhadap infrastruktur dasar dan tingkat pengeluaran yang lebih rendah, namun dengan tingkat kepemilikan rumah yang lebih tinggi. Temuan ini memberikan gambaran mengenai ketimpangan pembangunan antarprovinsi di Indonesia yang dapat menjadi acuan bagi pemerintah dalam perumusan kebijakan pembangunan wilayah yang lebih merata.

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

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

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.

Segmentasi Provinsi di Indonesia Berdasarkan Akses Fasilitas Dasar dan Pengeluaran Rumah Tangga Menggunakan K-Means Saputri, Devi; Mustafidah, Hindayati; Wibowo, Feri; Hakim, Dimara Kusuma
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 6 No. 4 (2025): Juni 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v6i4.8630

Pemerataan akses terhadap fasilitas dasar dan peningkatan kesejahteraan masyarakat di Indonesia masih menjadi tantangan besar, khususnya antarprovinsi. Meskipun dalam satu dekade terakhir telah terjadi kemajuan pembangunan, ketimpangan antarwilayah masih tampak nyata. Ketimpangan ini tercermin dari perbedaan signifikan dalam akses terhadap air minum layak, sanitasi, listrik, tempat tinggal yang layak, serta pengeluaran rumah tangga per kapita per bulan. Penelitian ini bertujuan untuk mengelompokkan 34 provinsi di Indonesia berdasarkan indikator akses terhadap fasilitas dasar dan pengeluaran rumah tangga guna mengidentifikasi pola ketimpangan pembangunan wilayah. Metode yang digunakan adalah algoritma K-Means Clustering dengan variabel mencakup kepemilikan rumah, akses air minum layak, sanitasi, listrik, penggunaan gas, serta pengeluaran rumah tangga yang berkaitan dengan fasilitas tersebut. Hasil segmentasi menunjukkan terbentuknya dua klaster: Klaster 1 terdiri dari 29 provinsi dengan akses yang lebih baik terhadap fasilitas dasar dan tingkat pengeluaran rumah tangga yang lebih tinggi, namun dengan tingkat kepemilikan rumah yang relatif lebih rendah. Klaster 2 mencakup 5 provinsi dengan akses terbatas terhadap infrastruktur dasar dan tingkat pengeluaran yang lebih rendah, namun dengan tingkat kepemilikan rumah yang lebih tinggi. Temuan ini memberikan gambaran mengenai ketimpangan pembangunan antarprovinsi di Indonesia yang dapat menjadi acuan bagi pemerintah dalam perumusan kebijakan pembangunan wilayah yang lebih merata.

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