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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<![CDATA[Perancangan Game Edukasi Sebagai Media Pelestarian Bahasa Gorontalo Pada Anak Sekolah Dasar ]]>
<![CDATA[Moh. Rifandi R.M]]>;
<![CDATA[Irma Surya Kumala Idris]]>;
<![CDATA[Abd. Rahmat Karim Haba]]>
<![CDATA[ Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 1 (2023): Edisi Mei 2023 ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo ]]>
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DOI: 10.37195/balok.v2i1.499
<![CDATA[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.]]>
<![CDATA[Analisis Sentimen pada Tweets Divisi Humas Polri Dengan Metode Naive Bayes Classifier ]]>
<![CDATA[Caldiyastovan Mohi]]>;
<![CDATA[Haditsah Annur]]>;
<![CDATA[Roys Pakaya]]>
<![CDATA[ Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 1 (2023): Edisi Mei 2023 ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo ]]>
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DOI: 10.37195/balok.v2i1.509
<![CDATA[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.]]>
<![CDATA[Klasifikasi Malware Menggunakan Teknik Machine Learning ]]>
<![CDATA[Evan Valdis Tjahjadi]]>;
<![CDATA[Budi Santoso]]>;
<![CDATA[Serwin]]>
<![CDATA[ Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 1 (2023): Edisi Mei 2023 ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo ]]>
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DOI: 10.37195/balok.v2i1.525
<![CDATA[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.]]>
<![CDATA[Klasifikasi Penerimaan Beras Miskin (RASKIN) Menggunakan Metode K-Nearest Neighbor ]]>
<![CDATA[Mukti Ali Mohammad]]>;
<![CDATA[Asmaul Husnah Nasrullah]]>;
<![CDATA[Rofiq Harun]]>
<![CDATA[ Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 1 (2023): Edisi Mei 2023 ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo ]]>
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DOI: 10.37195/balok.v2i1.531
<![CDATA[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]]>
<![CDATA[Penerapan Metode Simpel Moving Average Untuk Memprediksi Persediaan Tiket Kapal Di Pelabuhan Penyeberangan Gorontalo: Stock up on boat tickets at the Gorontalo crossing port ]]>
<![CDATA[Nuraini Azis]]>;
<![CDATA[Muis Nanja]]>;
<![CDATA[Zohrahayaty]]>
<![CDATA[ Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 1 (2023): Edisi Mei 2023 ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo ]]>
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DOI: 10.37195/balok.v2i1.540
<![CDATA[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%.]]>
<![CDATA[Game Edukasi Pembelajaran Matematika Untuk Anak-Anak Sekolah Dasar ]]>
<![CDATA[Yunan Kalaka]]>;
<![CDATA[Yasin Aril Mustofa]]>;
<![CDATA[Hastuti Dalai]]>
<![CDATA[ Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 1 (2023): Edisi Mei 2023 ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo ]]>
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DOI: 10.37195/balok.v2i1.542
<![CDATA[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.]]>
<![CDATA[Penentuan Pola Penjualan Obat Menggunakan Algoritma Apriori ]]>
<![CDATA[Aldo Aprilio Arifin]]>;
<![CDATA[Husdi]]>;
<![CDATA[Yusrianto Malago]]>
<![CDATA[ Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 1 (2023): Edisi Mei 2023 ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo ]]>
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DOI: 10.37195/balok.v2i1.544
<![CDATA[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.]]>
<![CDATA[Prediksi Jumlah Persediaan Telur Ayam Menggunakan Metode K-Neares Neighbor: - ]]>
<![CDATA[baguna, filda]]>;
<![CDATA[Husdi, Husdi]]>;
<![CDATA[Taliki, Sunarto]]>;
<![CDATA[Kamaruddin, Andi]]>
<![CDATA[ Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 2 (2023): November 2023 ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo ]]>
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DOI: 10.37195/balok.v2i2.119
<![CDATA[Abstract - UD. Unggas Karya Mandiri is one of the production areas producing chicken eggs in Banggai Laut Regency, with the existence of UD Unggas Karya Mandiri Banggai Laut which has the aim of increasing the number and types of employment opportunities for Banggai Laut Regency in particular. Based on the results of research at UD Unggaas Karya Mandiri Banggai Laut, this is the result of fluctuating chicken egg production or unstable production which is caused by several things, namely lack of availability of feed ingredients, anti-biotic drugs, vaccinations and so on. The aim of this research is to obtain better accuracy in predicting the number of chicken egg supplies at UD Unggas Karya Mandiri Banggai Laut by applying the K-Nearest Neighbor method. Based on the prediction results with existing data, it was obtained using the K-Nearest Neighbor method. This application was able to predict the number of chicken egg supplies at UD Unggas Karya Mandiri. It can be seen that the prediction application for the number of chicken egg supplies at UD Unggas Karya Mandiri Banggai Laut can be applied with an accuracy of 96.98% of the prediction results obtained.. Keywords: Prediction, Eggs, Accuracy, Inventory, K-Nearest Neighbor]]>
<![CDATA[Implementasi Metode Regresi Linear Sederhana Untuk Prediksi Harga Cabai Rawit ]]>
<![CDATA[Moha Lalapa, Nazarullah]]>;
<![CDATA[Warid]]>;
<![CDATA[Serwin]]>
<![CDATA[ Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 2 (2023): November 2023 ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo ]]>
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DOI: 10.37195/balok.v2i2.121
<![CDATA[Abstract ; The potential for developing cayenne pepper farming is widely open, especially in Gorontalo Province. After being designated as the second leading commodity in Gorontalo province after corn, the total cayenne pepper production in 2020 reached 147,292 tons (Central Bureau of Statistics of Gorontalo Province in 2020). Gorontalo District is one of the centers for cayenne pepper production in Gorontalo Province. The production contribution until 2020 reaches 35.65% of the whole cayenne pepper production in Gorontalo Province. This contribution places Gorontalo District as the second-largest producer of cayenne pepper after Bone Bolango. The high price of cayenne pepper production in Gorontalo District often causes a market price to drop by up to IDR 20,000/kg, while in fact, it is before religious holidays. The cayenne pepper price soars drastically. To cope with the problem, it is necessary to use a prediction technique using the Simple Linear Regression and MAPE method. This research aims to design a system to predict the price of cayenne pepper. The variables used are Production as the value of X and Price as the value of Y. Based on the prediction results, it gains an error rate of 24.00% or an accuracy rate of 76.00%. It means that the system designed is feasible to be used or applied to predict the price of cayenne pepper. Keywords: simple linear regression, mape, cayenne pepper]]>
<![CDATA[Penerapan Metode Least Square Untuk Memprediksi Harga Pangan Di Kota Gorontalo ]]>
<![CDATA[lahabu, sintiya]]>;
<![CDATA[Sudirman S]]>;
<![CDATA[Harun, Rofiq]]>
<![CDATA[ Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 2 (2023): November 2023 ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo ]]>
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DOI: 10.37195/balok.v2i2.134
<![CDATA[ Abstract ; This study aims to predict food prices in Gorontalo city. Food is a basic human need. Garlic (Allium sativum) is a type of food and is one of the commodities to be developed because it has become a community need as a spice almost in every dish. The increase in onion prices is highly dependent on the harvest and planting seasons. It is also affected by weather and pest attacks. In addition, price increases are also related to marketing activities. If compared to consumer areas, onion prices in producer areas are lower. The main problem is the difficulty of predicting food prices, especially garlic which can change at any time due to the unstable availability in the market. It is influenced by several factors such as weather and pest attacks. This study wants to create a system with data mining techniques that will be used to predict food prices in Gorontalo city based on previous food price data and using the Least Square method and finding the level of error using the Mean Absolute Percentage Error (MAPE). The result of the level of accuracy for food prices is 80.59%. The results of this accuracy can be categorized that the application made is feasible to be used in predicting food prices in Gorontalo city. Keywords: Least Square, food price prediction, MAPE]]>
