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Journal : Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer (BALOK)

Aplikasi Informasi Layanan Terminal Tipe A Dan Pelabuhan Penyeberangan Di Provinsi Gorontalo Berbasis Android: (Studi Kasus : Pelabuhan Penyebrangan Kota Dan Marisa & Terminal Tipe A Dungingi Dan Isimu) Yuliani Fajriah Latjompoh; Rofiq Harun
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 1 No 2 (2022): Edisi November (2022)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (359.957 KB) | DOI: 10.37195/balok.v1i2.278

Abstract

Layanan Informasi Transportasi Darat di Provinsi Gorontalo merupakan salah satu kebutuhan yang sangat dibutuhkan saat ini, khususnya bagi masyarakat diluar Provinsi Gorontalo yang ingin mengunjungi Gorontalo, maupun masyarakatProvinsi Gorontalo itu sendiri yang ingin bepergian ke luar Provinsi Gorontalo, guna mempermudah masyarakat mendapatkan informasi layanan yang mereka butuhkan tentang lokasi ketersediaan sarana transportasi dimaksud, maka aplikasi android dengan menggunakan Java dan Xml sangat tepat untuk memenuhi kebutuhan tersebut. Metode yang digunakan pada penelitian ini yakni metode deskriptif dengan pendekatan kualitatif, yakni dengan melakukan observasi langsung di lokasi penelitian. Penelitian ini menghasilkan sebuah Sistem InformasiLayanan berbasis android yang menjadi pusat informasi mengenai angkutan bus Terminal Dungingi-Terminal Isimu, serta Pelabuhan Penyeberangan Gorontalo dan Pelabuhan Penyeberangan Marisa, Sistem Informasi layanan ini diharapkan nantinya dapat membantu masyarakat dalam melakukan monitoring tarif/biaya angkutan bus di Terminal Dungingi-Isimu dan tarif angkutan Pelabuhan Penyeberangan Gorontalo serta Pelabuhan Penyeberangan Marisa, Sistem juga diharapkan dapat membantu masyarakat dalam mendapatkan informasi jadwal keberangkatan tiap angkutan secara real-time. Kata kunci : Aplikasi, Layanan Terminal, Android  
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37195/balok.v2i1.531

Abstract

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 Least Square Untuk Memprediksi Harga Pangan Di Kota Gorontalo lahabu, sintiya; Sudirman S; Harun, Rofiq
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 2 (2023): November 2023
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37195/balok.v2i2.134

Abstract

  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
Analisis Sentimen Objek Wisata Di Kabupaten Banggai Laut Menggunakan Metode Naive Bayes Fatmawati; Husdi; Kartika Chandra Pelangi; Rofiq Harun
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 3 No 1 (2024): Mei 2024
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37195/balok.v3i1.882

Abstract

Abstract - are carried out and a place to have fun for a long time to achieve satisfaction, enjoy good service, and bring home beautiful memories of the tourist attractions. In Banggai Laut Regency, many tourist attractions are attractive for tourism activities. The number of visitors increases every year. The discussion about tourist attractions in Banggai Laut Regency is interesting to the local community. There are a lot of public comments about the tourist attractions in Banggai Laut. The number of opinions about tourist attractions in Banggai Laut makes it difficult to determine the sentiment of the comments manually. Therefore, sentiment analysis is required to classify the comments and whether or not they tend to be positive. In this case, this study employs the Naïve Bayes algorithm to classify the problems. Based on the sentiment analysis, it is proven that the Naïve Bayes method or algorithm can classify comments with good results. The accuracy generated in this sentiment analysis is 87%, with a division of training data of 90% and test data of 10%. The acquisition of these accuracy results indicates that the proposed algorithm has a Fairly Good diagnostic level. Keywords: sentiment analysis, tourist attraction, Naïve Bayes