Pub Date : 2023-06-30DOI: 10.31961/eltikom.v7i1.648
Tiara Lailatul Nikmah, Nur Hazimah Syani Harahap, Gina Cahya Utami, Muhammad Mirza Razzaq
Customer experience is a key component in increasing sales numbers. Customers are important assets that must be kept up for a corporation or firm. Prioritizing customer service is one way to protect client loyalty. To ensure that service priority is right on target, this research was conducted on groups of consumers who are anticipated to have high business prospects. The 2011 retail online shop sales dataset with 379,980 records and eight char-acteristics was used. The length, recency, frequency, and monetary (LRFM) feature selection approach was used in the study process to select features for further segmentation using the K-Means data mining method to define consumer types. Following the completion of the research, clients were divided into four categories: Premium Loyalty, Inertia Loyalty, Latent Loyalty, and No Loyalty. The correct clustering results are displayed in the vali-dation test using the Silhouette Score Index technique, which yielded a score value of 0.943898. Based on the outcomes of this segmentation, business actors may prioritize providing clients with the proper service.
{"title":"Customer Segmentation Based on Loyalty Level Using K-Means and LRFM Feature Selection in Retail Online Store","authors":"Tiara Lailatul Nikmah, Nur Hazimah Syani Harahap, Gina Cahya Utami, Muhammad Mirza Razzaq","doi":"10.31961/eltikom.v7i1.648","DOIUrl":"https://doi.org/10.31961/eltikom.v7i1.648","url":null,"abstract":"Customer experience is a key component in increasing sales numbers. Customers are important assets that must be kept up for a corporation or firm. Prioritizing customer service is one way to protect client loyalty. To ensure that service priority is right on target, this research was conducted on groups of consumers who are anticipated to have high business prospects. The 2011 retail online shop sales dataset with 379,980 records and eight char-acteristics was used. The length, recency, frequency, and monetary (LRFM) feature selection approach was used in the study process to select features for further segmentation using the K-Means data mining method to define consumer types. Following the completion of the research, clients were divided into four categories: Premium Loyalty, Inertia Loyalty, Latent Loyalty, and No Loyalty. The correct clustering results are displayed in the vali-dation test using the Silhouette Score Index technique, which yielded a score value of 0.943898. Based on the outcomes of this segmentation, business actors may prioritize providing clients with the proper service.","PeriodicalId":33096,"journal":{"name":"Jurnal ELTIKOM Jurnal Teknik Elektro Teknologi Informasi dan Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43937987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.31961/eltikom.v7i1.618
I. K. N. Putra, Ni Putu Dita Ariani Sukma Dewi, Diah Ayu Pusparani, Dibi Ngabe Mupu
Signature is used to legally approve an agreement, treaty, and state administrative activities. Identification of the signature is required to ensure ownership of a signature and to prevent things like forgery from happening to the owner of the signature. In this study, data signatures were obtained from 25 people over the age of 50. The signers provided 20 signatures and were free to choose the stationery used to write the signature on white paper. The total data obtained in this study was 500 signature data. The obtained signature was scanned to create a signature image, which was then pre-processed to prepare it for feature extraction, which can characterize the signature images. The HOG method was used to extract features, resulting in a dataset with 4,536 feature vectors for each signature image. To identify the signature image, the classification methods SVM, Decision Tree, Nave Bayes, and K-NN were compared. SVM achieved the highest accuracy, which is 100%. When K=5, the K-NN method achieved a fairly good accuracy of 97.3%. Meanwhile, Naive Bayes and Decision Tree achieved accuracy significantly lower than K-NN (61%). Because the HOG method produced a large feature vector for each signature, it is recommended that important features that represent signatures be optimized or extracted to produce smaller features to speed up computation without sacrificing accuracy, and that the HOG method be compared to other extraction feature methods to obtain a better model in future research.
{"title":"Signature Identification using Digital Image Processing and Machine Learning Methods","authors":"I. K. N. Putra, Ni Putu Dita Ariani Sukma Dewi, Diah Ayu Pusparani, Dibi Ngabe Mupu","doi":"10.31961/eltikom.v7i1.618","DOIUrl":"https://doi.org/10.31961/eltikom.v7i1.618","url":null,"abstract":"Signature is used to legally approve an agreement, treaty, and state administrative activities. Identification of the signature is required to ensure ownership of a signature and to prevent things like forgery from happening to the owner of the signature. In this study, data signatures were obtained from 25 people over the age of 50. The signers provided 20 signatures and were free to choose the stationery used to write the signature on white paper. The total data obtained in this study was 500 signature data. The obtained signature was scanned to create a signature image, which was then pre-processed to prepare it for feature extraction, which can characterize the signature images. The HOG method was used to extract features, resulting in a dataset with 4,536 feature vectors for each signature image. To identify the signature image, the classification methods SVM, Decision Tree, Nave Bayes, and K-NN were compared. SVM achieved the highest accuracy, which is 100%. When K=5, the K-NN method achieved a fairly good accuracy of 97.3%. Meanwhile, Naive Bayes and Decision Tree achieved accuracy significantly lower than K-NN (61%). Because the HOG method produced a large feature vector for each signature, it is recommended that important features that represent signatures be optimized or extracted to produce smaller features to speed up computation without sacrificing accuracy, and that the HOG method be compared to other extraction feature methods to obtain a better model in future research.","PeriodicalId":33096,"journal":{"name":"Jurnal ELTIKOM Jurnal Teknik Elektro Teknologi Informasi dan Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44187117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.31961/eltikom.v7i1.767
Ahmad Zaki Ramadhani, M. Facta, S. Handoko
The need for electrical energy continues to increase over time. However, in Indonesia power plants are still dominated by fossil fuel power plants, and there are still many areas without access to electricity. The use of renewable energy is needed to replace fossil fuels considering that fossil fuels can run out one day. The coastal area of Batakan Village in Tanah Laut Regency, South Kalimantan Province, was chosen as the focus location for conducting hybrid power plant simulations because this village is located in a coastal area where wind and solar energy sources are abundant. Batakan Village is approximately 40 km from Pelaihari City. Medium-voltage network transmission system (JTM) is supplied from Pelaihari City, and it is almost certain that this village experiences large power losses over long distance. This power loss will be detrimental if an effort is not made to reduce it. The purpose of this research is first to determine the optimal hybrid power plant configuration design to reduce power loss in the electricity system in Batakan Village. Second, it will analyze the power loss of the hybrid power plant system in Batakan Village, and finally, this research is going to analyze the investment feasibility of the hybrid power plant system in Batakan Village. In this study, the design of renewable energy plants, such as solar power plants (PLTS) with a total capacity of 406.1 kW and wind power plants (PLTB) with a total capacity of 125 kW, and the electricity network (grid system) are used together in a hybrid power generation system. The ETAP software was used to analyze the power losses of the hybrid power generation system, while the HOMER software was used to determine the net present value (NPV) and cost of energy (COE) of the hybrid power generation system. The results show that the configuration of the solar, wind, and grid systems is the most optimal. It is obtained from the results of ETAP simulations that have been carried out during average load and peak load conditions that by including the Solar Power Plant and Wind Power Plant power losses in the electricity system in Batakan Village can be reduced from the previous one using the system configuration only connected to the PLN power grid (grid system only). The total power losses incurred was 269.1 kW of active power and 1613.5 kvar of reactive power at average load reduced to 266.9 kW of active power and 1568.9 kvar of reactive power. At peak load the total power losses were 423.4 kW of active power and 2573.0 kvar of reactive power and they deceased to 41.,5 kW of active power and 2510.5 kvar of reactive power. In terms of investment, the COE value decreased by IDR 111, and the NPC decreased by IDR 6,600,000,000 at the average load. At the peak load COE decreased by IDR 88, while NPC by IDR 7,000,000,000. The return of investment (ROI) value is 13.2%, which indicates that the investment is still in the profitable stage.
{"title":"Analysis of Power Generation and Distribution of Hybrid Energy for Electricity Loads in Batakan Village","authors":"Ahmad Zaki Ramadhani, M. Facta, S. Handoko","doi":"10.31961/eltikom.v7i1.767","DOIUrl":"https://doi.org/10.31961/eltikom.v7i1.767","url":null,"abstract":"The need for electrical energy continues to increase over time. However, in Indonesia power plants are still dominated by fossil fuel power plants, and there are still many areas without access to electricity. The use of renewable energy is needed to replace fossil fuels considering that fossil fuels can run out one day. The coastal area of Batakan Village in Tanah Laut Regency, South Kalimantan Province, was chosen as the focus location for conducting hybrid power plant simulations because this village is located in a coastal area where wind and solar energy sources are abundant. Batakan Village is approximately 40 km from Pelaihari City. Medium-voltage network transmission system (JTM) is supplied from Pelaihari City, and it is almost certain that this village experiences large power losses over long distance. This power loss will be detrimental if an effort is not made to reduce it. The purpose of this research is first to determine the optimal hybrid power plant configuration design to reduce power loss in the electricity system in Batakan Village. Second, it will analyze the power loss of the hybrid power plant system in Batakan Village, and finally, this research is going to analyze the investment feasibility of the hybrid power plant system in Batakan Village. In this study, the design of renewable energy plants, such as solar power plants (PLTS) with a total capacity of 406.1 kW and wind power plants (PLTB) with a total capacity of 125 kW, and the electricity network (grid system) are used together in a hybrid power generation system. The ETAP software was used to analyze the power losses of the hybrid power generation system, while the HOMER software was used to determine the net present value (NPV) and cost of energy (COE) of the hybrid power generation system. The results show that the configuration of the solar, wind, and grid systems is the most optimal. It is obtained from the results of ETAP simulations that have been carried out during average load and peak load conditions that by including the Solar Power Plant and Wind Power Plant power losses in the electricity system in Batakan Village can be reduced from the previous one using the system configuration only connected to the PLN power grid (grid system only). The total power losses incurred was 269.1 kW of active power and 1613.5 kvar of reactive power at average load reduced to 266.9 kW of active power and 1568.9 kvar of reactive power. At peak load the total power losses were 423.4 kW of active power and 2573.0 kvar of reactive power and they deceased to 41.,5 kW of active power and 2510.5 kvar of reactive power. In terms of investment, the COE value decreased by IDR 111, and the NPC decreased by IDR 6,600,000,000 at the average load. At the peak load COE decreased by IDR 88, while NPC by IDR 7,000,000,000. The return of investment (ROI) value is 13.2%, which indicates that the investment is still in the profitable stage.","PeriodicalId":33096,"journal":{"name":"Jurnal ELTIKOM Jurnal Teknik Elektro Teknologi Informasi dan Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48558309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.31961/eltikom.v7i1.729
Ashri Shabrina Afrah, Merinda Lestandy, Juwita P. R. Suwondo
The public needs information about the predicted inflation rate for education costs to manage family finances and prepare education funds. This information is also beneficial for the government to create policies in education. Malang is one of the educational cities in Indonesia, but research on the prediction of the inflation rate of education costs in the city still needs to be made available. Besides, the researchers have yet to find previous studies on forecasting that used the specific inflation rate for education costs in Indonesia by applying the Deep Learning method, especially those using the Consumer Price Index (CPI) data for the Education Expenditure Group. This research aims to develop a model to forecast the inflation of education costs in Malang using the Deep Learning Method. This research was conducted using Consumer Price Index (CPI) data for the Education Expenditure Group in Malang during 1996-2021s taken from the Central Bureau of Statistics (BPS) Malang. The forecasting method used is the Long and Short-Term Memory (LSTM) method, which is a development of the Recurrent Neural Network (RNN). The results showed that it achieved the best accuracy by a model with one hidden layer and four hidden nodes, namely MAPE=2.8765% and RMSE=8.37.
{"title":"The Utilization of Deep Learning in Forecasting The Inflation Rate of Education Costs in Malang","authors":"Ashri Shabrina Afrah, Merinda Lestandy, Juwita P. R. Suwondo","doi":"10.31961/eltikom.v7i1.729","DOIUrl":"https://doi.org/10.31961/eltikom.v7i1.729","url":null,"abstract":"The public needs information about the predicted inflation rate for education costs to manage family finances and prepare education funds. This information is also beneficial for the government to create policies in education. Malang is one of the educational cities in Indonesia, but research on the prediction of the inflation rate of education costs in the city still needs to be made available. Besides, the researchers have yet to find previous studies on forecasting that used the specific inflation rate for education costs in Indonesia by applying the Deep Learning method, especially those using the Consumer Price Index (CPI) data for the Education Expenditure Group. This research aims to develop a model to forecast the inflation of education costs in Malang using the Deep Learning Method. This research was conducted using Consumer Price Index (CPI) data for the Education Expenditure Group in Malang during 1996-2021s taken from the Central Bureau of Statistics (BPS) Malang. The forecasting method used is the Long and Short-Term Memory (LSTM) method, which is a development of the Recurrent Neural Network (RNN). The results showed that it achieved the best accuracy by a model with one hidden layer and four hidden nodes, namely MAPE=2.8765% and RMSE=8.37.","PeriodicalId":33096,"journal":{"name":"Jurnal ELTIKOM Jurnal Teknik Elektro Teknologi Informasi dan Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49155672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.31961/eltikom.v7i1.583
Ilham Firman Ashari, Lkhsanudin Raka Siwi, Hafizh Londata, Ihtiandiko Wicaksono
Pada zaman digital saat ini, memberikan keamanan dan kerahasiaan informasi sangat penting ketika melakukan pertukaran informasi melalui jaringan komunikasi. Hal ini bertujuan agar informasi yang dikirimkan oleh pengirim dapat diterima secara utuh oleh penerima tanpa adanya campur tangan pihak ketiga yang tidak berhak atas informasi tersebut. Kriptografi dan Steganografi merupakan teknik yang dapat digunakan untuk mengamankan sebuah pesan rahasia, salah satu jenis metode yang dapat digunakan adalah algoritma RC4 yang digunakan untuk mengamankan pesan asli menjadi pesan rahasia yang acak agar tidak diketahui orang lain. Pada steganografi yang digunakan sebagai media untuk mengamankan pesan antara lain gambar, audio, video, dan dokumen, dimana salah satu metode yang digunakan adalah algoritma least significant bit (LSB). Berdasarkan pengujian yang dilakukan terkait pada penyisipan pesan pada media gambar dan audio didapatkan analisis terkait enkripsi dan dekripsi algoritma rc4. Pengujian aspek imperceptibility, dari histogram gambar dan spektrum audio terlihat tidak ada perbedaaan antara gambar dan audio sebelum dan setelah penyisipan. Pengujian aspek fidelity, dari PSNR dihasilkan rata-rata nilai > 30 dB. Pengujain aspek recovery, menunjukan bahwasanya aspek recovery berhasil 100 % karena tidak ada perbedaan antara pesan asli dan setelah ekstraksi. Pengujian aspek capacity, menunjukkan bahwasanya semakin besar ukuran media penampung maka semakin besar pesan yang bisa disisipkan.
{"title":"ANALISIS DAN PERBANDINGAN STEGANOGRAFI PADA MEDIA AUDIO DAN GAMBAR MENGGUNAKAN LSB DAN RC4","authors":"Ilham Firman Ashari, Lkhsanudin Raka Siwi, Hafizh Londata, Ihtiandiko Wicaksono","doi":"10.31961/eltikom.v7i1.583","DOIUrl":"https://doi.org/10.31961/eltikom.v7i1.583","url":null,"abstract":"Pada zaman digital saat ini, memberikan keamanan dan kerahasiaan informasi sangat penting ketika melakukan pertukaran informasi melalui jaringan komunikasi. Hal ini bertujuan agar informasi yang dikirimkan oleh pengirim dapat diterima secara utuh oleh penerima tanpa adanya campur tangan pihak ketiga yang tidak berhak atas informasi tersebut. Kriptografi dan Steganografi merupakan teknik yang dapat digunakan untuk mengamankan sebuah pesan rahasia, salah satu jenis metode yang dapat digunakan adalah algoritma RC4 yang digunakan untuk mengamankan pesan asli menjadi pesan rahasia yang acak agar tidak diketahui orang lain. Pada steganografi yang digunakan sebagai media untuk mengamankan pesan antara lain gambar, audio, video, dan dokumen, dimana salah satu metode yang digunakan adalah algoritma least significant bit (LSB). Berdasarkan pengujian yang dilakukan terkait pada penyisipan pesan pada media gambar dan audio didapatkan analisis terkait enkripsi dan dekripsi algoritma rc4. Pengujian aspek imperceptibility, dari histogram gambar dan spektrum audio terlihat tidak ada perbedaaan antara gambar dan audio sebelum dan setelah penyisipan. Pengujian aspek fidelity, dari PSNR dihasilkan rata-rata nilai > 30 dB. Pengujain aspek recovery, menunjukan bahwasanya aspek recovery berhasil 100 % karena tidak ada perbedaan antara pesan asli dan setelah ekstraksi. Pengujian aspek capacity, menunjukkan bahwasanya semakin besar ukuran media penampung maka semakin besar pesan yang bisa disisipkan.","PeriodicalId":33096,"journal":{"name":"Jurnal ELTIKOM Jurnal Teknik Elektro Teknologi Informasi dan Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45724095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.31961/eltikom.v7i1.604
Uvi Desi Fatmawati, M. Pratami, Wahyu Hidayat, Kurdianto Kurdianto
The need for organic rice among the people continues to increase in line with the declining level of public health due to the COVID-19 pandemic. Consuming organic rice is one way to maintain body immunity, but organic rice is susceptible to attack by Sitophilus Oryzae L, a type of rice weevil which is the main pest in postharvest commodities. Proper storage of rice is one way to address food security during a pandemic. In this study, a prototype of an anti-rice weevil (Sytophilus Oryzae L) organic rice storage was made using a Raspberry Pi controller and several additional sensors such as a camera sensor and temperature and humidity sensors. UV Hydroponic Lamp and LED Grow Light are used to reduce the growth rate of rice bugs during storage. The results showed that the whole system was running well and the rice bugs on rice were drastically reduced within 36 hours and 18 minutes of storage.
{"title":"Smart Rice Box - The Prototype of Organic Rice Storage Anti-Rice Weevil for Food Security during Pandemic","authors":"Uvi Desi Fatmawati, M. Pratami, Wahyu Hidayat, Kurdianto Kurdianto","doi":"10.31961/eltikom.v7i1.604","DOIUrl":"https://doi.org/10.31961/eltikom.v7i1.604","url":null,"abstract":"The need for organic rice among the people continues to increase in line with the declining level of public health due to the COVID-19 pandemic. Consuming organic rice is one way to maintain body immunity, but organic rice is susceptible to attack by Sitophilus Oryzae L, a type of rice weevil which is the main pest in postharvest commodities. Proper storage of rice is one way to address food security during a pandemic. In this study, a prototype of an anti-rice weevil (Sytophilus Oryzae L) organic rice storage was made using a Raspberry Pi controller and several additional sensors such as a camera sensor and temperature and humidity sensors. UV Hydroponic Lamp and LED Grow Light are used to reduce the growth rate of rice bugs during storage. The results showed that the whole system was running well and the rice bugs on rice were drastically reduced within 36 hours and 18 minutes of storage.","PeriodicalId":33096,"journal":{"name":"Jurnal ELTIKOM Jurnal Teknik Elektro Teknologi Informasi dan Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42849167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chatbot technology uses natural language processing with artificial intelligence that can interact quickly in answering a question and producing relevant answer. ChatGPT is the latest chatbot platform developed by Open AI which allows users to interact with text-based engines. This platform uses the GPT-3 (Generative Pre-trained Transformer) algorithm to help understand the response humans want and generate relevant responses. Using the platform, users can find answers to their questions quickly and relevantly. The method used for OpenAI's research on ChatGPT integrated through Telegram chatbot is using a waterfall method which utilizes open API tokens from Telegram. In this research we develop OpenAI application connected with telegram bot. This application can help provide a wide range of information, especially information related to the Semarang State Polytechnic. By using Telegram chatbot in the program, users can find it easy to ask because it is integrated with OpenAI using the API. Telegram chatbot, which has a chat feature, allows easy communication between users and chatbots. Thus, it may reduce system errors on the bot.
{"title":"Open Artificial Intelligence Analysis using ChatGPT Integrated with Telegram Bot","authors":"Gisnaya Faridatul Avisyah, Ivandi Julatha Putra, Sidiq Hidayat","doi":"10.31961/eltikom.v7i1.724","DOIUrl":"https://doi.org/10.31961/eltikom.v7i1.724","url":null,"abstract":"Chatbot technology uses natural language processing with artificial intelligence that can interact quickly in answering a question and producing relevant answer. ChatGPT is the latest chatbot platform developed by Open AI which allows users to interact with text-based engines. This platform uses the GPT-3 (Generative Pre-trained Transformer) algorithm to help understand the response humans want and generate relevant responses. Using the platform, users can find answers to their questions quickly and relevantly. The method used for OpenAI's research on ChatGPT integrated through Telegram chatbot is using a waterfall method which utilizes open API tokens from Telegram. In this research we develop OpenAI application connected with telegram bot. This application can help provide a wide range of information, especially information related to the Semarang State Polytechnic. By using Telegram chatbot in the program, users can find it easy to ask because it is integrated with OpenAI using the API. Telegram chatbot, which has a chat feature, allows easy communication between users and chatbots. Thus, it may reduce system errors on the bot.","PeriodicalId":33096,"journal":{"name":"Jurnal ELTIKOM Jurnal Teknik Elektro Teknologi Informasi dan Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48870236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.31961/eltikom.v7i1.658
Falentina Lumban Toruan, M. Galina
Aquaculture of Litopenaeus Vannamei shrimp is one of Indonesia's most crucial commodity export shrimp. Aquaculture feed management and environmental management are essential factors in determining shrimp sustainability. To maximize shrimp farming results, proper feeding, water quality control, and con-tinuous monitoring of three critical parameters: temperature, power of hydrogen (pH), and salinity levels in ponds are required. This study aims to feed the shrimp automatically at predetermined times (07.00, 11.00, 16.00 and 20.00). At the same time, it will monitor pond water quality parameters. Temperature, pH and salinity are all factors monitored. Every 10 minutes, monitored data is stored in ThingSpeak using IoT technology. The design goal has a specific threshold to avoid future problems. A Telegram notification is sent every 10 seconds when the water condition exceeds the threshold. The overall accuracy rate of 98.81%, pH of 96.6%, and salinity of 99.17% demonstrate that the system works correctly.
{"title":"Internet of Things- Based Automatic Feeder and Monitoring of Water Temperature, PH, and Salinity for Litopenaeus Vannamei Shrimp","authors":"Falentina Lumban Toruan, M. Galina","doi":"10.31961/eltikom.v7i1.658","DOIUrl":"https://doi.org/10.31961/eltikom.v7i1.658","url":null,"abstract":"Aquaculture of Litopenaeus Vannamei shrimp is one of Indonesia's most crucial commodity export shrimp. Aquaculture feed management and environmental management are essential factors in determining shrimp sustainability. To maximize shrimp farming results, proper feeding, water quality control, and con-tinuous monitoring of three critical parameters: temperature, power of hydrogen (pH), and salinity levels in ponds are required. This study aims to feed the shrimp automatically at predetermined times (07.00, 11.00, 16.00 and 20.00). At the same time, it will monitor pond water quality parameters. Temperature, pH and salinity are all factors monitored. Every 10 minutes, monitored data is stored in ThingSpeak using IoT technology. The design goal has a specific threshold to avoid future problems. A Telegram notification is sent every 10 seconds when the water condition exceeds the threshold. The overall accuracy rate of 98.81%, pH of 96.6%, and salinity of 99.17% demonstrate that the system works correctly.","PeriodicalId":33096,"journal":{"name":"Jurnal ELTIKOM Jurnal Teknik Elektro Teknologi Informasi dan Komputer","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41574543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.31961/eltikom.v7i1.621
Lela Nurpulaela, Ridwan Satrio Hadikusumo
This study aims to provide recommendations regarding frequency and channel settings for machine-to-machine (M2M) communication in preparation for the 5G era in Indonesia. In the rapid development of the Internet of Things (IoT), M2M communication is becoming increasingly important to support efficient and reliable connectivity between IoT devices. In this study, we conduct an in-depth analysis of the available frequency spectrum in Indonesia, considering existing regulatory constraints and technical requirements. The results of this study show that the frequency bands 920-925 MHz and 925-928 MHz suit M2M communication in Indonesia with the suggested channel settings. These recommendations are based on spectrum availability, M2M communication needs, and relevant technical requirements. Implementing these recommendations is expected to increase the efficiency and reliability of M2M communications in Indonesia, facilitate the further development of IoT technology, and prepare Indonesia well to face the 5G era. This study contributes to designing a regulatory framework and optimal spectrum use to support successful M2M communications in Indonesia.
{"title":"IoT Frequency Band Channelization in Indonesia as A Recommendation for Machine-To-Machine Communication Preparation in the 5G Era","authors":"Lela Nurpulaela, Ridwan Satrio Hadikusumo","doi":"10.31961/eltikom.v7i1.621","DOIUrl":"https://doi.org/10.31961/eltikom.v7i1.621","url":null,"abstract":"This study aims to provide recommendations regarding frequency and channel settings for machine-to-machine (M2M) communication in preparation for the 5G era in Indonesia. In the rapid development of the Internet of Things (IoT), M2M communication is becoming increasingly important to support efficient and reliable connectivity between IoT devices. In this study, we conduct an in-depth analysis of the available frequency spectrum in Indonesia, considering existing regulatory constraints and technical requirements. The results of this study show that the frequency bands 920-925 MHz and 925-928 MHz suit M2M communication in Indonesia with the suggested channel settings. These recommendations are based on spectrum availability, M2M communication needs, and relevant technical requirements. Implementing these recommendations is expected to increase the efficiency and reliability of M2M communications in Indonesia, facilitate the further development of IoT technology, and prepare Indonesia well to face the 5G era. This study contributes to designing a regulatory framework and optimal spectrum use to support successful M2M communications in Indonesia.","PeriodicalId":33096,"journal":{"name":"Jurnal ELTIKOM Jurnal Teknik Elektro Teknologi Informasi dan Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49221373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.31961/eltikom.v7i1.725
Dzhillan Dzhalila, D. Siahaan, Reza Fauzan, Raka Asyrofi, Muhammad Ihsan Karimi
Blockchain technology is gaining increasing interest among software developers as a distributed and decentralized ledger for tracking the origin of digital assets. However, the application of blockchain in software engineering requires further attention. In this study, we aim to address the current challenges and explore the need for specialized blockchain practices in software engineering. Through a systematic literature review, we identify the various applications of blockchain technology in software engineering. Additionally, we conduct a thorough analysis of existing obstacles and propose potential solutions. Gathering and evaluating requirements using blockchain-based requirements engineering approaches will enhance the quality and reliability of data in software development projects. This, in turn, will improve the overall quality and dependability of software, as well as increase user interest and productivity.
{"title":"A Systematic Literature Review on Blockchain Technology in Software Engineering","authors":"Dzhillan Dzhalila, D. Siahaan, Reza Fauzan, Raka Asyrofi, Muhammad Ihsan Karimi","doi":"10.31961/eltikom.v7i1.725","DOIUrl":"https://doi.org/10.31961/eltikom.v7i1.725","url":null,"abstract":"Blockchain technology is gaining increasing interest among software developers as a distributed and decentralized ledger for tracking the origin of digital assets. However, the application of blockchain in software engineering requires further attention. In this study, we aim to address the current challenges and explore the need for specialized blockchain practices in software engineering. Through a systematic literature review, we identify the various applications of blockchain technology in software engineering. Additionally, we conduct a thorough analysis of existing obstacles and propose potential solutions. Gathering and evaluating requirements using blockchain-based requirements engineering approaches will enhance the quality and reliability of data in software development projects. This, in turn, will improve the overall quality and dependability of software, as well as increase user interest and productivity.","PeriodicalId":33096,"journal":{"name":"Jurnal ELTIKOM Jurnal Teknik Elektro Teknologi Informasi dan Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46347889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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