cover
Contact Name
Asmaul husnah nasrullah
Contact Email
asmaulhusnel@gmail.com
Phone
+6282193533471
Journal Mail Official
jurnalbalokfikom@unisan.ac.id
Editorial Address
FIKOM UNISAN Jl. Drs. Achmad Nadjamuddin No.17, Dulalowo Tim., Kota Tengah, Kota Gorontalo Gorontalo 96135
Location
Kota gorontalo,
Gorontalo
INDONESIA
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer (BALOK)
ISSN : 28284666     EISSN : 28279425     DOI : https://doi.org/10.37195/balok.v1i1
Core Subject : Science,
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,
Articles 77 Documents
Identifikasi Kualitas Udang Segar Menggunakan Metode Gray Level Co-Occurance Matrix dan Artificial Neural Network : - Wanda Aprilia Pangemanan; Irma Surya Kumala Idris
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 (781.361 KB) | DOI: 10.37195/balok.v1i2.168

Abstract

This study is conducted to know the fresh shrimp quality. In this study, the data collection is through images of shrimp of a variety of sizes and with the number of classes. There are two classes, namely fresh and not fresh. This study is observed independently. The methods used in this study are the Gray Level Co-occurrence Matrix and Artificial Neural Network methods. The performance of using the GLCM and ANN methods in the identification process of fresh shrimp quality indicates a very good performance as proven by the accuracy of 93%, recall of 100%, the precision of 90%, and an F1 score of 95%. Keywords: fresh shrimp quality, GLCM, ANN
Clustering Tingkat Ekonomi Mahasiswa Calon Penerima Kartu Indonesia Pintar (KIP) Kuliah Metode K-Means Maimunsuyatni Sompa; Rezqiwati Ishak
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 (566.483 KB) | DOI: 10.37195/balok.v1i2.175

Abstract

ABSTRACTThe Smart Indonesia Card (KIP) for Higher Education by the government is under the auspices of theMinistry of Education and Culture. The Smart Indonesia Card (KIP) for Higher Education aims to helpprovide tuition assistance, especially for poor students to continue their studies. It prevents children fromdropping out of education. Universitas Ichsan Gorontalo is one of the private universities granted a quotaof the Smart Indonesia Card (KIP) for Higher Education. The limited number of student admissions (quota)of the Smart Indonesia Card (KIP) for Higher Education requires special attention in determining the rightstudents as recipients on target to get the number of quotas that are not commensurate with the number ofapplicants. In seeing that, clusters are carried out based on the economic level of students to get a groupof students prioritized to get the Smart Indonesia Card (KIP) for Higher Education. The K-Means methodgets clustering results using the Elbow technique, namely 5 clusters. The results of clustering for eachcluster indicate that Cluster 1 is a group of students with medium economic level and taken the secondpriority for recipients of assistance. Cluster 2 is a group of students with low economic levels and becomesthe first priority of recipients of assistance. Cluster 3 is a group of students with middle to high economiclevels and becomes the third priority for recipients of assistance. Cluster 4 is a group of students withmiddle economic level and become the fourth priority for recipients of assistance. Cluster 5 is a group ofstudents with middle to upper economic levels and is the fifth priority for recipients of assistance.Keywords: The Smart Indonesia Card (KIP) for Higher Education, Clustering, Elbow, K-Means
Sistem Pendukung Keputusan Penilaian Kinerja Karyawan Kontrak Menggunakan Metode Multy Attribute Utlity Theory (MAUT) (Studi Kasus : PT. Telkom Marisa) Muhammad Isla; Almer Hassan Ali
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 1 No 1 (2022): Edisi Mei 2022
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (774.794 KB) | DOI: 10.37195/balok.v1i1.178

Abstract

Performance appraisal of contract employees at PT. Telkom Marisa has notbeenimplemented optimally, especially in assessing the performance of contract employees. So far, the assessment of contract employees is only determined from the results of their work, there are no clear assessment criteria. Therefore, in this study, a performance appraisal of contract employees will be developed based on competencies that are expected to be able to accommodate the performance of contract employees. Employee performance appraisal consists of 5 (five) competencies, namely Discipline, Cooperation, Integrity, Responsibility, Leadership. by using the multi attribute utility theory (MAUT) method. The aim of this research is to create a decision support system to assess the performance of contract employees at PT. Telkom Marisa using the multi attribute utility theory (MAUT) method so that it can assess the performance of contract employees and display recommendations for employees who have the best performance.Keywords: Performance, Competence, PT. Telkom Marisa, Recommendations, multi attribute utility theory (MAUT)
Pengenalan Alat Musik Tradisional Gorontalo (Polopalo) Berbasis Android Sigit Ramadhan Muda; Yasin Aril Mustofa
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 1 No 1 (2022): Edisi Mei 2022
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (519.877 KB)

Abstract

Abstract Polopalo is an idiophone type musical instrument, which is a group of musical instruments whose sound source comes from the body of the instrument itself. The sound that comes out of the polopalo instrument when it is hit or hit, which is caused by vibrations found in the entire Polopalo instrument. Gorontalo traditional musical instrument (polopalo) on an Android-based smartphone. In this way, the process of introducing traditional musical instruments to Gorontalo (Polopalo). The results showed that the introduction of the Gorontalo (polopalo) traditional musical instrument based on Android had fulfilled the programming logic requirements, where CC = V(G) = 8 based on White Box testing, then the system was free from various component errors based on Black Box testing. Thus, the Gorontalo (Polopalo) Android Traditional Musical Instrument Recognition Application was obtained which was reliable and effective so that it could be implemented. Keywords: Traditional musical instruments, Polopalo, Android
Rancang Bangun Prototype Sistem Pendeteksi Banjir Menggunakan Thingspeak Dan Esp8266 Muhammad Adnan Gobel; Abdul Rahmat Karim Haba
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 (624.168 KB) | DOI: 10.37195/balok.v1i2.255

Abstract

Banjir adalah bagian dari permasalahan lingkungan fisik di permukaan bumi yang mengakibatkan kerugian dan dapat diartikan suatu keadaan di mana air sungai melimpah, menggenangi daerah sekitarnya sampai kedalaman tertentu hingga menimbulkan kerugian. Sistem Cerdas merupakan bagian dari bidang Ilmu Komputer/Informatika dan Rekayasa Cerdas untuk pengembangan berbagai metode bekemampuan tinggi yang diilhami oleh fenomena alam untuk menyelesaikan berbagai masalah kompleks di dunia nyata. Dalam penelitian ini sistim cerdas digunakan untuk mendeteksi ketinggian permukaan air sungai dengan menggunakan sensor Ultrasonik, Mikrokontroler ESP8266, dan Thingspeak. Sensor ultrasonik adalah sensor yang bekerja berdasarkan prinsip pantulan gelombang suara dan digunakan untuk mendeteksi keberadaan suatu objek tertentu di depannya. Kata Kunci: pendeteksi banjir, sensor ultrasonik, Mikrokontroler ESP8266, Thingspeak
Pengelompokan Tingkat Kerusakan Hutan Menggunakan Algoritma K-Means Clustering Fadila Badu; Asmaul Husnah Nasrullah
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 (869.663 KB) | DOI: 10.37195/balok.v1i2.276

Abstract

Kerusakan sumber daya hutan mengakibatkan penurunan kemampuan fungsi hutan dalam mendukung segala aspek kehidupan. Faktor yang mengakibatkan terjadinya tingkat kekritisan hutan, salah satunya adalah pertumbuhan penduduk yang begitu cepat, serta aktivitas pembangunan dalam berbagai bidang tentu saja akan menyebabkan ikut meningkatnya permintaan akan lahan. Oleh karenanya Dinas Kehutanan dan pertambangan Kabupaten Bone Bolango sangat memerlukan data yang akurat terhadap data kerusakan hutan yang terjadi setiap saat. Untuk itu penelitian ini bertujuan untuk merealisasikan penggunaan metode K-Means cluster yang mampu memberikan pengelompokan tingkat kerusakan hutan, sehingga dapat menjadi referensi bagi Dinas Kehutanan dan pertambangan Kabupaten Bone Bolango dalam membuat keputusan secara cepat dan tepat.Selaras dengan masalah yang dihadapi, peneliti memandang perlunya suatu tindakan Pengelompokan Tingkat Kerusakan Hutan. pengelompokkan tersebut dilakukan dengan menerapkan sebuah Metode K-Means Clustering. Dari hasil penelitian yang telah dilakukan menunjukkan metode K-Means mampu mengelompokkan tingkat kerusakan hutan dengan baik, hal itu dapat dilihat diperolehnya tiga kelompok kerusakan hutan yakni kerusakan sedang, menengah dan kerusakan tinggi. Kata kunci: Kerusakan, Hutan, K-Means, Clustering
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  
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37195/balok.v2i1.397

Abstract

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37195/balok.v1i2.399

Abstract

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37195/balok.v2i1.414

Abstract

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