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All Journal BERKALA SAINSTEK JOIN (Jurnal Online Informatika) BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING ESTIMASI: Journal of Statistics and Its Application DedikasiMU: Journal of Community Service Narra J STATISTIKA InSTEM Tadulako Science and Technology Journal Indonesian Journal of Statistics and Its Applications
Iman Setiawan
Statistics Study Program, Mathematics And Natural Sciences Faculty, Tadulako University, Indonesia
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Automatic Plant Watering System for Local Red Onion Palu using Arduino Iman Setiawan; Junaidi Junaidi; Fadjryani Fadjryani; Fika Reski Amaliah
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.813

Abstract

Central Sulawesi Province in Indonesia has great potential for horticultural commodities, namely local red onion Palu. In the current climate change, local farmers are still watering plants in the conventional way. The automatic watering system simplifies the work of local farmers. This device uses a soil moisture sensor as a soil moisture detector and Arduino as a program brain. This study aims to determine the position of soil moisture sensor, the optimal length of watering time and analyze the quality of data stored. The experiment was carried out using a Completely Randomized Design (CRD). The position of the soil moisture sensor was analyzed by Profile Analysis. The optimal length of watering time was determined by Analysis of Variance (ANOVA) and Least Significant Difference (LSD). The quality of data stored was determined by a number of missing values and frequency of watering. The results showed that in soil planting media the position of soil moisture sensor had no significant effect, while in others planting media (water and combination of water and soil) the position of the sensor had a significant effect. The optimal watering time was 3 seconds. The stored data has low quality in terms of missing values and lack of consistency.
Internet of Things (IoT) for Soil Moisture Detection Using Time Series Model Iman Setiawan; Junaidi Junaidi; Fadjryani Fadjryani; Fika Reski Amaliah
JOIN (Jurnal Online Informatika) Vol 7 No 2 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i2.951

Abstract

Technology in agriculture has been widely and massively applied. One of them is automation technology and the use of big data through the Internet of Things (IoT). The use of IoT allows a process to run automatically without human intervention. Extreme weather changes and narrow land use are one of the main problems in agriculture. The development of IoT devices has been widely developed regarding this subject. One of them is a soil moisture detection system. This study aims to build an IoT soil moisture detection system. The system will use a sensor as input which is then processed in a microcontroller device and the prediction results are sent to the IoT cloud platform. Prediction results are obtained using a time series model and then its performance is evaluated using RMSE. This model was chosen because the structure of the observed soil moisture data is based on time. The results of this study indicate that the soil moisture IoT system can work well. This is supported by the results of the prediction evaluation value of the RMSE = 1.175682x10-5 model which is very small.
Pemodelan Topik pada Judul Berita Online Detikcom Menggunakan Latent Dirichlet Allocation Yayang Matira; Junaidi; Iman Setiawan
ESTIMASI: Journal of Statistics and Its Application Vol. 4, No. 1, Januari, 2023 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.vi.24843

Abstract

Detikcom is a very popular news portal today. The news on the portal continues to grow time to time, causing the existing news data to pile up. As a result, this is necessary to utilize this large amount of data. One of the ways that can be used is to extract topics from news text data through topic modeling using the Latent dirichlet allocation (LDA) method. This method is very popular because it can perform analysis on very large documents. This research aims to find certain patterns in a document by generating several different topics so that it does not specifically divide documents into a particular topic. This research has three topics obtained, with a coherence score is 0,7586. The first topic discusses conflicts and crises within a country, the second topic discusses issues related to humanitarian, and the third topic discusses the issues of corruption committed by state officials.
Peramalan Curah Hujan di Kota Makassar dengan Menggunakan Metode SARIMAX Nur Hazimah Latief; Nur’eni Nur’eni; Iman Setiawan
Statistika Vol. 22 No. 1 (2022): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v22i1.990

Abstract

ABSTRAK Peramalan adalah memprediksi kejadian yang akan datang dengan melihat data dari masa lalu. Salah satu metode peramalan yaitu ARIMA yang dibedakan menjadi 2 yaitu ARIMA non-musiman dan ARIMA musiman. Penelitian ini menggunakan metode ARIMA musiman yang dikembangkan untuk mengatasi keterbatasan pada metode tersebut yang dikenal dengan SARIMAX (Seasonal Autoregressive Integrated Moving Average with Exogeneous Input) dengan menganalisis curah hujan di Kota Makassar dengan variabel eksogen yaitu suhu udara. Hasil yang dipakai dari penelitian ini adalah mendapatkan model SARIMAX yaitu SARIMAX (2,0,2)(1,0,0)12 dengan persamaan Zt = 0,5552Zt-12 - 0,2097Zt-1 + (0,2097)(0,5552)Zt-13 + 0,6135Zt-2 - (0,6135)(0,5552)Zt-14 + et - 0,614et-2 – 0,3859et-2 – 194,883X1t dengan hasil peramalan curah hujan di Kota Makassar Januari sampai Desember 2021 yaitu 868 mm3, 985 mm3, 848 mm3, 848 mm3, 731 mm3, 829 mm3, 868 mm3, 829 mm3, 712 mm3, 614 mm3, 790 mm3 dan 926 mm3 dimana terjadi kenaikan curah hujan tahun sebelumnya dengan curah hujan terendah terjadi pada bulan Oktober 2021 sebesar 614 mm3 dan terbanyak terjadi pada bulan Februari 2021 sebesar 985 mm3 dengan nilai MAPE sebesar 17,75%. ABSTRACT Forecasting is predicting data events from the future by looking at data from the past. One of the forecasting methods is ARIMA which is divided into 2, namely non-seasonal ARIMA and seasonal ARIMA. This study uses the seasonal ARIMA method which was developed to overcome the limitations of the method known as SARIMAX (Seasonal Autoregressive Integrated Moving Average with Exogeneous Input) by analyzing rainfall in Makassar City with an exogenous variable, namely air temperature. The purpose of this study is to obtain the results of forecasting rainfall in 2021. The results obtained are the SARIMAX model (2.0,2)(1,0,0)12 with the lowest rainfall forecasting results in Makassar City occurring in October 2021 at 614 mm3 and the most occurred in February 2021 at985 mm3 with a MAPE value of 17.75%.
SOSIALISASI SISTEM WEB UNTUK MENDIAGNOSA HAMA DAN PENYAKIT TANAMAN BAWANG MERAH LOKAL PALU PADA KELOMPOK PETANI BINAAN Junaidi Junaidi; Iman Setiawan; Mohammad Fajri; Hajra Rasmita Ngemba; Nurpati Nurpati
DedikasiMU : Journal of Community Service Vol 5 No 3 (2023): DedikasiMU September
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30587/dedikasimu.v5i3.6268

Abstract

Sistem guna mendiagnosa gejala awal serangan hama dan penyakit tanaman yang berbasis Web bagi petani bawang merah lokal Palu perlu disosialisasikan. Hal ini dilakukkan agar petani dapat dengan cepat mengetahui jenis hama dan penyakit apa yang menyerang tanaman tersebut. Sehingga hal ini dapat membantu para petani dengan cepat untuk memberikan penanganan dalam mengatasi serangan hama dan penyakit tersebut. Kemudahan dalam mengakses web yang berbasis pengambilan keputusan berdasarkan metode Bayesain dapat membantu para petani sehingga dapat lebih baik, ideal dan bijaksana dalam menentukan aktivitas prioritas yang akan dilakukan guna mendukung produksi tanaman bawang merah lokal Palu. Dengan demikian, tujuan dari kegiatan ini adalah membantu petani bawang merah lokal Palu sebagai mitra guna mengetahui dengan cepat gejala awal serangan hama dan penyakit pada tanaman bawang merah lokal Palu yang berbasis web. Hal ini berdampak pada produksi bawang yang dihasilkan lebih baik dan berkualitas. Adapun kegiatan sosialisasi yang dilakukan adalah dengan pemberian materi, pelatihan system web serta diskusi dengan mitra. Sosialisasi yang telah dilakukan sangat bermanfaat bagi para petani bawang merah untuk mengetahui dengan cepat dan tepat dalam mendeteksi jenis hama dan penyakit yang menyerang bawang merah melalui sistem web. Hal ini terbukti dengan ketercapaian hasil yang ditargetkan oleh tim pengabdi berupa pengaplikasian secara langsung penggunaan sistem web dengan baik. Kegiatan sosialisasi ini sangat menarik karena para petani sangat antusias mengikuti pelatihan web secara mandiri. Melalui kegiatan pengabdian ini, petani dapat memahami konsep dalam menentukan hama dan penyakit serta penanganannya.
INTERPOLTION OF SULFUR DIOXIDE (SO2) AND NITROGEN DIOXIDE (NO2 ) IN YOGYAKARTA SPECIAL PROVINCE USING THE COKRIGING METHOD Andina Aulia Pramesti; Nur’eni; Iman Setiawan
Tadulako Science and Technology Journal Vol. 4 No. 1 (2023): TADULAKO SCIENCE AND TECHNOLOGY JOURNAL
Publisher : LPPM Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/sciencetech.v4i1.16392

Abstract

Air is a mixture of gases found in the layer that surrounds the earth. The cokriging method is the development of the kriging method to estimate a variable that minimizes estimation errors by utilizing cross-correlation between several variables. This research was conducted using data from 45 coordinate locations for air monitoring by the Department of Environment and Forestry of the Special Region of Yogyakarta in 2017. The results showed that the best model for estimating sulfur dioxide and nitrogen dioxide air pollution was the spherical model with the smallest Mean Square Error (MSE) value. which is 317,527. Interpolation of sulfur dioxide and nitrogen dioxide content values using cokringing resulted in 100,390 new points. The value of air pollution is in the range of 0-40, which according to ISPU means that at that point, good air quality has no impact on humans but causes a certain smell and injury to some plant species.
Grouping of Provinces in Indonesia Based on Infrastructure Development Indicators Using the Ward Method with a Multiscale Bootstrap Approach Nurfatra; Junaidi; Iman Setiawan
Tadulako Science and Technology Journal Vol. 4 No. 1 (2023): TADULAKO SCIENCE AND TECHNOLOGY JOURNAL
Publisher : LPPM Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/sciencetech.v4i1.16393

Abstract

Infrastructure plays an important role in improving the quality of life and human welfare. Infrastructure is a facility that is needed by every country, including Indonesia, to support various community activities in general in everyday life. However, the problem of inequality in infrastructure development in Indonesia is still a challenge for the government. This study aims to classify provinces in Indonesia based on indicators of infrastructure development. The method used in this grouping is the ward method with the multiscale bootstrap approach to determine the validity of the formed cluster. The results of the grouping show that we obtained 7 clusters where clusters with poor infrastructure development status are cluster 7, clusters with fairly good infrastructure development status, are cluster 6, clusters with good infrastructure development status, are cluster 1, cluster 2, cluster 3 and cluster 4, while cluster with a very good infrastructure development status, are cluster 5. From the 7 clusters formed, we obtained 4 clusters with an approximately unbiased (AU) value greater than and equal to 95, defined as valid clusters and 3 clusters with an AU value of less than and equal to 95, defined as invalid clusters
Sales Prediction of Palu Arshop Clothing Using the High Order Chen Fuzzy Time Series Method Marni Sagap; Nur'eni; Iman Setiawan
Tadulako Science and Technology Journal Vol. 3 No. 2 (2023): Tadulako Science and Technology Journal
Publisher : LPPM Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/sciencetech.v3i2.17313

Abstract

Introduction: Arshop is one of the clothing stores in Palu City that is in great demand by the community. As one of the many clothing stores in Palu City Arshop to find a strategy to increase sales. One way that can be used is to make predictions to determine strategies to increase sales. Method: Higher-order Chen fuzzy time series method to predict the time series data of Arshop Palu clothing sales. Chen's high-order fuzzy time series is a time series analysis that can capture varied data patterns, one of which is seasonal patterns, and is formed based on two or more data in the past. Results and Discussion: The results of this study indicate that the high-order Chen fuzzy time series method has an accuracy rate of MAPE 15.59%, which is categorized as good the prediction results of the comparison between various orders show that the fourth-order Chen fuzzy time series is the best for predicting clothing sales of Arshop Palu. Conclusion: The prediction of clothing sales at Arshop Palu using the higher-order Chen fuzzy time series method resulted in a MAPE of 15.59%, which shows good accuracy because it is less than 20%. Based on the comparison of the accuracy values of the four orders, the fourth-order FTS proved to be the most effective for predicting the clothing sales of Arshop Palu.
Implementation of the Fuzzy Time Series Singh Method for Forecasting Non-Oil and Gas Export Values in Indonesia Borahima, Maharani Safira B.; Sain, Hartayuni; Setiawan, Iman; Fadri, Firda
BERKALA SAINSTEK Vol 12 No 3 (2024)
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/bst.v12i3.52663

Abstract

Export activities drive a country's economic growth by increasing revenue and strengthening trade relations between countries. In Indonesia, non-oil and gas products are the primary contributors of export performance. In 2022, non-oil and gas exports values reached 275.96 million USD, marking an increase of 25.80% compared to the previous year's export value. This growth in export value was influenced by various external factors, leading to substantial changes. The government requires further analysis to forecast future trends in non-oil and gas export values due to the uncertain and fluctuating patterns. The Singh Fuzzy Time Series method, an advancement of FST, utilizes fuzzy sets to forecast volatile economic data, yielding more accurate predictions. This research used the Singh FST method and achieved a low MAPE value of 1.31%, indicating a high level of accuracy. Forecasts for Indonesia's non-oil and gas export value over the next three months are projected to reach USD 22,263.02 million in January 2023, followed by USD 22,217.21 million in February 2023, and USD 22,243.68 million in March 2023. These export value forecasts can aid the government in policy-making related to exports and sustain the stability of the country’s economic growth rate.
Re-Calibration of Model-Based Capacitive Sensor for IoT Soil Moisture Measurements Setiawan, Iman; Musa, Mohammad Dahlan Th.; Putri, Saskia Amalia
Journal of Applied Informatics and Computing Vol. 7 No. 2 (2023): December 2023
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v7i2.6809

Abstract

Low-cost automatic irrigation systems require quality calibrated soil moisture sensors. The sensor is an indirect method of soil moisture measurement. The sensor works based on the change in the dielectric constant. So, it requires to be calibrated in terms of the soil water content. Polynomial and linear models are frequently used to calibrate soil moisture sensor data in the gravimetric test method. However, computational effort is required. This study aims to obtain a sensor calibration application that can provide the best model of the available models for model-based capacitive soil moisture sensor. This research was conducted using primary data from gravimetric test experiment on Internet of things (IoT) based soil moisture sensor. Web-based re-calibration application produced best model based on adjusted R Squared. Finally, model-based capacitive soil moisture sensor set up using best model coefficient. The results show that the web-based re-calibration application can provide the best model for model-based capacitive soil moisture sensor. Based on gravimetric test experiments and web applications, the best model is a polynomial regression model order 3 with 0.945 adjusted R Squared. The model predicted value for soil moisture is in the range 0 "“ 1.2 for raw sensor data values of 100 "“ 530. When the model coefficient configured in capacitive soil moisture sensor and Blynk application, soil moisture measurement can be done via mobile phone in real time.
Co-Authors A. Prasetiyo, Nugraha Afriza, Dini Aprilia Alfina, Alfina Alkaff, Sylmina D. Andina Aulia Pramesti Ariza, Moh Borahima, Maharani Safira B. Bustanul Arifin Damayanti, Virga Elly Wahyudin Fadjriyani Fadjryani, Fadjryani Fadri, Firda Fika Reski Amaliah Hafidah, Siti Nur Hajra Rasmita Ngemba Hartayuni Hartayuni Sain Junaidi Junaidi Junaidi Junaidi Marni Sagap Mohammad Fajri Musa, Mohammad Dahlan Th. Nur Hazimah Latief Nur'Eni Nur’eni Nur’eni Nurfatra Nurpati Nurpati Nurrahma, Andi Nur’eni Nur’eni Nur’eni Nur’eni Nur’eni Purba, Fredrick D. Putri, Saskia Amalia Rachman, Rohis Rais Rais Sanusi, Mayamariska Sritasarwati Putran Yayang Matira