Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer (BALOK)
JOURNAL ILMIAH (Banthayo Lo Komputer) BALOK encompasses all aspects of the latest outstanding research and developments in the field of computer science including; Artificial Intelligence, Software Enginering, Data Mining, Computer Networks, Internet of Things,
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Implementasi Eoip Tunnel Dan Bonding Di Routerboad Mikrotik Untuk Menambah Kapasitas Wireless Link Di Pt Gomeds Network
Dedi Setiawan;
Andi Bode;
Warid Yunus
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 1 (2023): Edisi Mei 2023
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo
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DOI: 10.37195/balok.v2i1.397
Information technology in the world has been experiencing rapid development, and Indonesia is no exception. In Indonesia, internet access is increasingly widespread in remote villages provided by ISPs. Precisely on the island of Sulawesi, there are several ISPs, one of which is PT Gomeds Network. PT Gomeds Network is a company engaged in internet network provider services. It was founded on January 17, 2011, in Gorontalo. It has infrastructure spread throughout the island of Sulawesi. PT Gomeds Network utilizes wireless network technology. Each Base Transceiver Station (BTS) has a different local link capacity. The problem experienced by PT Gomeds Network is the insufficient capacity of the BTS wireless link and the absence of a backup Wireless Link at each BTS when the Wireless Radio device or the main link line connecting the BTS is lost or damaged. The purpose of this study is to increase the wireless link capacity of BTS so that customers connected to BTS can receive services based on the internet package rented and provide benefits in the form of a backup wireless link when one of the wireless link lines is down due to damage. The results of this study explain that the EOIP Tunnel and Bonding methods can run as expected and produce adequate BTS capacity, and backup wireless links for BTS can function without disconnecting wireless links.
Penerapan Metode K-Means Untuk Clustering Penjualan Suku Cadang Kendaraan Viar (Studi Kasus: CV. Gotama Viar Gorontalo)
Iftinan Inayah Mohamad;
Irvan Abraham Salihi;
Kartika Chandra Pelangi
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 1 (2023): Edisi Mei 2023
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo
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DOI: 10.37195/balok.v1i2.399
Until now motorcycles are still one of the most widely used means of transportation by Indonesian people. One of the authorized VIAR dealers in Sulawesi is CV Gotama VIAR Gorontalo. The company sells several VIAR-branded motorcycles and some genuine spare parts. There are stock-outs in several types of VIAR vehicle spare parts that are sold because many consumers buy them. There is a stacking of stock of other types of VIAR vehicle spare parts in the warehouse because they are not well sold. It is caused by the company experiencing confusion in determining what types of spare parts are more and less in-demand. The purpose of this study is to group several types of vehicle spare parts that are more and less in demand. The K-Means method is one of the methods in partitional clustering which works in grouping large data by dividing the data into one or more clusters. Based on the results of this study, it can be concluded that the results obtained explain that there are 373 types of goods categorized as more in-demand and 7 types of goods categorized as less in-demand. The system created can obtain a system that can classify spare parts sales data using the K-Means method which is reliable when applied.
Analisis Sentimen Opini Publik Pengguna Twitter Terhadap Kenaikan Harga BBM Menggunakan Algoritma Naïve Bayes
Rahmad Harun;
Rezqiwati Ishak;
Sudirman Panna
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 1 (2023): Edisi Mei 2023
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo
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DOI: 10.37195/balok.v2i1.414
Fuel oil is needed as a support in life. Local fuel must be adjusted to international fuel prices so that the country's fiscal sustainability remains safe and not threatened. This price adjustment is carried out by the government as an effort to optimize the use and supply of fuel and to overcome the occurrence of a fuel crisis in the future. On the Twitter platform, the discussion about the fuel price increase even has become a trending topic due to the number of tweets discussing the issue. The number of opinions about the fuel price increase makes it difficult to determine the sentiment of the tweet manually. Therefore, sentiment analysis is needed that can classify the tweet whether it tends to be positive or negative. In this case, this analysis is mediated by the Naïve Bayes algorithm to classify the problem. Based on the sentiment analysis made, it can be seen that the Naïve Bayes method or algorithm can analyze tweets with good results. The accuracy generated in this sentiment analysis is 85% with a division of 80% training data and 20% test data. With the acquisition of these accuracy results, it can be said that the proposed algorithm has a fairly good diagnostic level. Keywords: sentiment analysis, Twitter, fuel oil, Naïve Bayes
Perancangan Game Edukasi Sebagai Media Pelestarian Bahasa Gorontalo Pada Anak Sekolah Dasar
Moh. Rifandi R.M;
Irma Surya Kumala Idris;
Abd. Rahmat Karim Haba
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 1 (2023): Edisi Mei 2023
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo
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DOI: 10.37195/balok.v2i1.499
The learning process using conventional methods does not provide optimal learning outcomes. For optimal learning, the selection of the learning model is very important which is accompanied by the selection of the right learning media. The use of games as learning media is not wrong because games can indirectly provide education. Playing games without educational content may negatively impact children. To achieve optimal learning results, this research takes the initiative to make Gorontalo language educational games that can be played through smartphone media based on the Android operating system. In educational game design, there are two main features, namely the play menu and the learning menu. To be able to complete the game on the play menu, players must capture Gorontalo vocabulary words following the available vocabulary images. While in the learning feature players can learn the vocabulary available in the game. Based on the results of black box testing, the features contained in the Gorontalo Language Educational Game can run properly without any errors occurring. Meanwhile, based on user acceptance testing, the game that has been designed can be accepted by students with a total score of 90.5% in the Very Feasible category.
Analisis Sentimen pada Tweets Divisi Humas Polri Dengan Metode Naive Bayes Classifier
Caldiyastovan Mohi;
Haditsah Annur;
Roys Pakaya
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 1 (2023): Edisi Mei 2023
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo
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DOI: 10.37195/balok.v2i1.509
News is a story or information about an event that is hotly discussed. It can be utilized by online media to provide updated news to the public. The use of social media among the public in disseminating information is fast so that distance and time are not an obstacle for social media users to be able to receive and access information developments widely without constraints. Twitter is a social media platform that is widely used by individuals, governments, and organizations, including the police, to publish news about related agencies. By applying one of the functions of text mining, namely the Naïve Bayes Classifier to analyze public sentiment towards tweets from the Indonesian Police Public Relations Division’s Twitter account, manually analyzing sentiment on tweets is no longer effective, so a Naïve Bayes Classifier method is needed to automatically analyze sentiment on tweets into positive and negative opinions. So, by using this algorithm, this study gets a fairly high accuracy value. In this study, a high accuracy value of 76% when splitting 10% of testing data and 90% of training data. But when preprocessing and implementing new data in the streamlit framework, it takes up to 1 minute to process the data.
Klasifikasi Malware Menggunakan Teknik Machine Learning
Evan Valdis Tjahjadi;
Budi Santoso;
Serwin
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 1 (2023): Edisi Mei 2023
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo
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DOI: 10.37195/balok.v2i1.525
Abstract Computer networks connected to the Internet can access information from all over the world very easily. However, the connection between the network and the Internet increases the potential for system failure. One of the methods that can be used in machine learning is the random forest algorithm method. Random forest is one of the methods in machine learning that is used to solve clarification problems. Based on the problems, it is necessary to classify malware where data is taken from malware datasets to make it easier to learn and distinguish the types of malware. The process consists of collecting datasets, pre-processing, training machine learning, and testing model performance. This study aims to find out the performance of Machine Learning using a random forest algorithm for malware- random forest classification. In this process, pre-processing of data is done by installing several Python libraries. Pandas is an open-source Python library that is usually used for data analysis needs. The model is trained on a dataset with various features and the results show a high accuracy of 99%. The random forest model provides excellent results without preprocessing the data. The results are good even if the data is not balanced. There is no need to use any technique to balance it. Scaling is not necessary. The random forest model is a recursive partitioning model that depends on data partitioning as it works on splitting the feature values and does not perform any calculations in it. The results indicate that the model has a precision of 0.99.
Klasifikasi Penerimaan Beras Miskin (RASKIN) Menggunakan Metode K-Nearest Neighbor
Mukti Ali Mohammad;
Asmaul Husnah Nasrullah;
Rofiq Harun
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 1 (2023): Edisi Mei 2023
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo
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DOI: 10.37195/balok.v2i1.531
Rice is the staple food of most of Indonesia's population. Rice for the poor is a staple food subsidy in the form of rice intended for poor families as an effort from the government to improve food security and provide protection to poor families. Therefore, in 2002 the Indonesian government launched the rice for the poor program as an implementation of the government's consistency. The rice for the poor program is stipulated in the Presidential Regulation of the Republic of Indonesia No. 15 of 2010 on the Acceleration of Poverty Reduction and Presidential Instruction No. 3 of 2010 on Equitable Development Programs. This program aims to reduce the expenditure burden of target households by meeting some of their basic needs in the form of rice. In addition, the program, rice for the poor, aims to increase and open access to family food through the sale of rice to beneficiary families with a predetermined amount. One of the efforts to overcome these problems is to implement one of the methods in data mining, namely classification, which can group data more accurately following the level of similarity of the data characteristics. In this research, data mining analysis is carried out with classification techniques using the K-Nearest Neighbor method. The variables applied in this study are government, education, income, housing conditions, employment, and government assistance card holders
Penerapan Metode Simpel Moving Average Untuk Memprediksi Persediaan Tiket Kapal Di Pelabuhan Penyeberangan Gorontalo: Stock up on boat tickets at the Gorontalo crossing port
Nuraini Azis;
Muis Nanja;
Zohrahayaty
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 1 (2023): Edisi Mei 2023
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo
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DOI: 10.37195/balok.v2i1.540
Transportation is one of the basic needs of society, both by air, land and sea. Sea shipping at the Gorontalo Ferry Port is the main means of advancing the national economy. Many people choose executive boats to travel because they are fast, comfortable and safe. Before traveling, prospective passengers on executive ships must first book tickets with an agent who determines where they will go and when the ship will depart [2]. Tickets are tools/media that are used by certain companies as a direct substitute for gold. Tickets are usually in the form of paper containing certain items that show value. According to the Big Indonesian Dictionary, ticket "means what is considered as a method of payment used by existing means of transportation"[3]. when commuting. At the port several classes are available for purchasing tickets, namely economy, business and VIP/executive classes. When purchasing tickets, counters are often confused when separating which classes sell more. This results in a slow process of inputting data. In this case the researcher will classify tickets based on the class that sold the most so that it can be seen how many classes are obtained and can make it easier for the ticket counter to input data on tickets sold. Prediction (forecasting) is an attempt to predict or estimate something that will happen in the future by utilizing various relevant information at previous times (historical) through a scientific method. Prediction methods can be carried out qualitatively through expert opinions or quantitatively by calculating mathematically. One of the quantitative prediction methods is using time series analysis [4]. The Simple Moving Average(SMA) is the simplest moving average and does not use its weights to calculate closing price movements. Although simple, SMA is very effective in determining market trends in terms of forecasting. Based on the data processing used by applying the SMA data method that has been tested into the system, each obtains a mape value for the type of business, obtaining a mape of 1.07% for the type economy by 0.28% and VIP type by 0.22%.
Game Edukasi Pembelajaran Matematika Untuk Anak-Anak Sekolah Dasar
Yunan Kalaka;
Yasin Aril Mustofa;
Hastuti Dalai
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 1 (2023): Edisi Mei 2023
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo
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DOI: 10.37195/balok.v2i1.542
Abstrak - Game saat ini telah menjadi sarana hiburan yang paling banyak disukai masyarakat dari yang muda hingga yang tua. Itulah alasan mengapa pengembang game saat ini berlomba-lomba untuk berinovasi merancang sebuah game. Seiring dengan kebanyakan sekolah dasar masi menggunakan cara manual seperti buku dan alat tulis, maka penelitian ini bertujuan memeberikan sedikit kontribusi dalam dunia game, khususnya game yang bersifat edukasi. Sifat edukasi dalam game ini berupa pembelajaran matematika yang asik dan menarik. Di dalam game ini pemain bisa menikmati animasi dan juga bisa menambah pengetahuan berhitung dengan menjawab quis yang ada di dalam game ini. Kelebihan game ini yaitu bisa dijalankan secara offline sehingga tidak mempersulit anak dan orang tua untuk mengeluarkan uang. Hasil yang dicapai dari penelitian ini yaitu berhasil membuat sebuah aplikasi game edukasi pembelajaran berhitung. Game ini diharapkan dapat menambah pengetahuan anak dan juga diharapkan mampu meningkatkan minat belajar anak khususnya dibidang berhitung.
Penentuan Pola Penjualan Obat Menggunakan Algoritma Apriori
Aldo Aprilio Arifin;
Husdi;
Yusrianto Malago
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 1 (2023): Edisi Mei 2023
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo
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DOI: 10.37195/balok.v2i1.544
Piramid Mulia Pharmacy is a health facility where a place to sell drugs and concoct drugs based on a doctor's prescription, as well as trade medical goods. Piramid Mulia Pharmacy is still difficult in analyzing drug sales, because there is no system to analyze. The results showed that the Drug Sales Pattern Determination System Using the Apriori Algorithm has met the requirements of programming logic and is not complex, where CC = V (G) = 4 based on White Box testing, then the system has been free from various component errors based on Black Box testing. Thus, an efficient Drug Sales Pattern Determination System using the Apriori Algorithm is obtained so that it can be implemented.