20 research outputs found
Forecasting Air Temperature Using the Triple Exponential Smoothing Method
No full textChanges in air temperature are a major challenge in Indonesian agriculture. Erratic air temperatures hurt plant growth, so farmers must adjust planting schedules and plant selection according to the air temperature at a certain period. The author aims to predict minimum and maximum air temperatures in Temanggung district in 2024 using the Triple Exponential Smoothing (TES) method. Monthly air temperature data in Temanggung district for the period 2020 to 2023 is used for air temperature forecasting using the TES method. The analysis results show that the TES model can predict air temperature with fairly good accuracy. The minimum temperature is expected to be 23°C, maximum 26-27°C. The research results provide benefits for the agricultural sector in Temanggung. Farmers can use the results of air temperature predictions to adjust planting schedules based on crops that suit the air temperature to minimize the negative impact of air temperature on plant growth and agricultural yields
Forecasting Rainfall in Planting Onion Crops in Brebes District, Brebes District Using Holt-Winters Exponential Smoothing
No full textPlanting shallots is very dependent on rainfall. High rainfall when planting shallots can result in shallot plants not growing well, resulting in reduced selling value at harvest time and low rainfall. Therefore, this study aims to determine the rainfall forecasting process for planting shallot plants in Brebes District, Brebes Regency. The data used in rainfall forecasting is monthly data in Brebes District from January 2019 to December 2023 using the Holt-Winters Exponential Smoothing method. Data sourced from NASA's Power Data Access Viewer. In the surface data, get the MAPE value0.05241. Earth Skin Temperature data gets a MAPE value of 2.34346. Wind Speed data gets a MAPE value of 14.5396. DataPrecipitationgot a value of 138.829583. These findings contribute to further understanding regarding rainfall forecasting in shallot planting, which can support the planting process so that the harvest is good and produces high selling value
Comparison of Double and Triple Exponential Smoothing Methods for Rainfall Prediction
No full textRainfall is water that falls to the ground surface over a certain period and is measured in millimeters (mm). Rainfall is essential for the life of living things. Forecasting plays a significant role in decision-making in modern times, with two main methods: causal models and time series. Time series models have five types of data patterns: random, constant, seasonal, cyclical, and trend. For rainfall forecasting, the Double Exponential Smoothing and Triple Exponential Smoothing methods are used for trend pattern data. This research compares the two approaches based on error values using average rainfall data in Bojonegoro. The results show that Double Exponential Smoothing has a Mean Absolute Percentage Error (MAPE) of 0.6996%, while Triple Exponential Smoothing has a MAPE of 119.1497%. So, Double Exponential Smoothing is more accurate
DASAR PERTIMBANGAN HAKIM PENGADILAN NIAGA DALAM PUTUSAN NOMOR 05/Pdt.Sus-PKPU/2014/PN.Niaga.Smg DAN PUTUSAN MAHKAMAH AGUNG NOMOR 707K/Pdt.Sus-Pailit/2015 MENGENAI PEMENUHAN SYARAT PERDAMAIAN
No full textYessi Mayangsari Putri Marendra, Amelia Sri Kusuma Dewi, SH., MKn., Dr.Reka Dewantara, SH., MH. Fakultas Hukum Universitas Brawijaya Email: [email protected]  ABSTRAK Bermula saat PT. Kusuma Putra Santosa dalam keadaan penundaan kewajiban pembayaran utang berdasarkan putusan Pengadilan Niaga No. 05/Pdt.Sus-PKPU/2014/PN.Niaga.Smg. Terdapat salah satu kreditur separatis yang tidak menyetujui rencana perdamaian. Namun, hakim pengadilan niaga semarang mengambil keputusan menyetujui rencana perdamaian dengan dasar pertimbangan bahwa mayoritas kreditur menyetujui rencana perdamaian melalui hasil pemungutan suara. Hingga PT Bank Negara Indonesia mengajukan upaya hukum tingkat kasasi karena Pertimbangan hukum Pengadilan Niaga dinilai keliru tidak sesuai dengan Pasal 281 Undang-Undang No. 37 Tahun 2004 tentang Undang-Undang Kepailitan dan Penundaan Kewajiban Pembayaran Utang. Putusan Kasasi Mahkamah Agung Nomor 707K/Pdt.Sus-Pailit/2015 bahwa, Pengadilan Niaga pada Pengadilan Negeri Semarang tidak ditemukan kekeliruan dalam penerapan hukum oleh pengadilan niaga. Permohonan kasasi yang diajukan oleh Pemohon PT. Bank Negara Indonesia tersebut harus ditolak. Adanya ketidak sinkronan antara dasar pertimbangan hakim dengan peraturan per-undang-undang an,oleh karena itu meneliti dan menganalisa hal tersebut. Kata Kunci: Dasar Pertimbangan Hakim, Penundaan Kewajiban Pemabayaran Utang, Rencana Perdamaian. ABSTRACT This research started with the case when PT. Kusuma Putra Santosa was in its suspension of debt payment obligation according to the Decision of Commercial Court Number 05/Pdt.Sus-PKPU/2014/PN.Niaga.Smg. During the case, one of the separatist creditors disagreed with reconciliation, while the judges of the commercial court all agreed with the reconciliation simply because this step was agreed by the majority of creditors from voting. Reacting to this, PT. Bank Negara Indonesia decided to propose a petition for appeal, as the bank argued that the consideration made by the commercial court was acceptable and not in line with Article 281 of Law No. 37 of 2004 on Law of Bankruptcy and Suspension of Debt Payment Obligations. Based on the Decision made by Supreme Court Number 707K/Pdt.Sus-Pailit/2015, it was decided that the commercial court correctly implemented the existing legal system, leading to the rejection of appeal proposed by PT. Bank Negara Indonesia. Disharmony between the consideration made by the judges and the legislation serves as the reason why the author analyzed this case. Keywords: basic consideration made by judges, suspension of debt payment obligations, reconciliation.Â
Rainfall, Wind Speed, and Temperature Forecast Using Triple Exponential Smoothing and Gradient Descent
No full textThe global community strives to minimize the impact of disasters through various actions, for example, mapping flood-prone areas. Flood-prone areas need to be identified correctly, predicted, understood, and socialized to minimize risks when a disaster occurs regarding death, property damage, and socio-economic losses. This type of data-based prediction has been developed and implemented widely and can be applied to predictions related to hydrology. Data mining approaches (estimation, classification, clustering, and time-series forecast) have significantly influenced research related to flood prediction in recent years. The time-series flood forecast has been widely used in previous research using various statistical and data-mining methods. Predicting floods that occur in coastal areas is less discussed than river floods. One method that is often used is exponential smoothing. Determining damping factor values (alpha, beta, and gamma) in the triple exponential smoothing method, in general, is to use all values from 0 to 1 to find the most optimal damping factor, this takes quite a long time and results generally appear with less accuracy. So, a combination of the triple exponential smoothing algorithm is proposed to perform tTimeseries forecast, and the gradient descent algorithm is used as an optimization algorithm to obtain optimal weight values for alpha, beta, and gamma in triple exponential smoothing.
Keywords: triple exponential smoothing, gradient descent, flood forecast, flood prediction, time-series forecas
Analytical Hierarchy Process (AHP) untuk Zona Kerentanan Tanah Longsor di Daerah Gumelar
No full textLandslides 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 areaTanah longsor merupakan bencana geologi yang sering terjadi di daerah dengan topografi curam dan vegetasi minim, termasuk di Kecamatan Gumelar, Kabupaten Banyumas. Penelitian ini bertujuan untuk memetakan zona kerentanan tanah longsor dengan pendekatan multikriteria menggunakan metode Analytical Hierarchy Process (AHP) yang diintegrasikan dalam Sistem Informasi Geografis (SIG). Empat parameter utama yang dianalisis meliputi kemiringan lereng, curah hujan, litologi, dan tutupan lahan, dengan bobot ditentukan melalui matriks perbandingan berpasangan oleh para ahli. Hasil perhitungan menunjukkan kemiringan lereng (49,2%) dan curah hujan (30,9%) sebagai faktor dominan dalam menentukan tingkat kerentanan. Peta kerawanan yang dihasilkan menunjukkan distribusi wilayah dengan risiko rendah, sedang, dan tinggi, yang divalidasi menggunakan data kejadian longsor lapangan. Penelitian ini memberikan dasar spasial yang akurat untuk perencanaan mitigasi bencana tanah longsor di wilayah studi
Optimization of Double Exponential Smoothing Model for Daily Earth Temperature Forecasting in Dayeuhluhur, Cilacap
No full textGlobal 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
PEMBANGUNAN APLIKASI PELAPORAN PERIJINAN DENGAN ONLINE ANALYTICAL PROCESSING
No full textBusiness licensing data in a district that has been collected in a database, itÂ
will be useful when it is analyzed, so a lot of important information will beÂ
obtained. The government need a system that can help them to analyze dataÂ
easily. Online Analytical Processing (OLAP) is an implementation ofÂ
Datawarehousing that can help reporting and analyzing well. OLAP can map theÂ
data with cube dimensions, each dimension can be easily compared, so theÂ
decision maker can find the problems that faced easily and quickly.Â
Some of the problems that solved in this research are : Progress Report onÂ
Company Registration in several years, the Number of Companies by the type ofÂ
business, Development of Investment, the number of SIUP by District, , theÂ
number of SIUP by business class, the number of license based on itâ��s type,Â
Construction Permit (IMB) in several years, and the Number of Disorders PermitsÂ
(HO) by several classification. Â
Reporting application in data Licensing are built in this research with OLAPÂ
technology.  Based on the Chiâ��Square testing performed for business licensingÂ
data which contain 100â��1161 records, the Chiâ��Square value are 45,89 â�� 80,Â
greater than Chiâ��Square table (13,28), there is significantly different for timeÂ
consuming between SQL and OLAP.  But,  when data are reducet untuk 90Â
records, the Chiâ��Square value is 2,01, less than Chiâ��Square table, there is noÂ
significantly different for time consuming between SQL and OLAP. Â
Pengembangan Media Pembelajaran Interaktif Berbasis Augmented Reality untuk Klasifikasi Hewan Vertebrata dan Invertebrata Menggunakan Metode GDLC
No full textThis study introduces an innovative Augmented Reality (AR)-based learning media for teaching ani-mal classification, specifically visualizing vertebrates and invertebrates in interactive three-dimensional form. Developed using Unity 3D and Vuforia with the Game Development Life Cy-cle (GDLC) waterfall model, the application offers an engaging learning experience through mark-er-based scanning that displays 3D animal objects, instructional materials, and evaluative quizzes. The novelty of this research lies in the integration of 3D visualization and interactive learning that enables students to explore and test their understanding in real time. Functional testing using the Black Box method confirmed that all features operated correctly, while field trials involving 20 students from SD Negeri Karanggintung 04 showed a high satisfaction rate of 88.75% (strongly agree category). Fur-thermore, post-test results demonstrated a significant improvement compared to pre-test scores, with students’ performance increasing from the 2–3 range to 4–5. With its visual and interactive approach, this AR-based learning media effectively enhances student comprehension and engagement, offering a promising and innovative solution for biology education at the elementary level
Optimization of Gamification Type Selection in Pop-Up Campaigns to Enhance Customer Engagement on E-Commerce Platform XYZ Using the Analytical Hierarchy Process Method
No full textOne 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.Penerapan gamifikasi dalam campaign sudah terbukti memiliki dampak signifikan terhadap customer engagement dalam e-commerce. Penelitian ini bertujuan untuk mengoptimalkan pemilihan jenis gamifikasi dalam pop-up campaign untuk meningkatkan consumer engagement pada platform e-commerce XYZ. Pemilihan jenis gamifikasi yang tepat sangat penting, namun sering kali dipengaruhi oleh subjektivitas dalam penilaian. Untuk itu, penelitian ini menggunakan metode analytic hierarchy process yang mengintegrasikan data historis sebagai acuan dalam pengisian alternatif berdasarkan kriteria untuk mengurangi subjektivitas metode AHP dalam menentukan jenis gamifikasi yang paling efektif berdasarkan kriteria Click-Through Rate (CTR), Conversion Rate (CR), dan Impression. Hasil penelitian menunjukkan jenis gamifikasi Memory Card merupakan jenis yang paling efektif berpotensi untuk meningkatkan consumer engagement. Pendekatan ini diharapkan dapat menjadi acuan bagi platform e-commerce dalam merancang strategi gamifikasi yang lebih efektif
