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All Journal Jurnal Informatika Upgris ILKOM Jurnal Ilmiah Jurnal Tecnoscienza International Journal of Advances in Data and Information Systems Jurnal Indonesia : Manajemen Informatika dan Komunikasi International Journal Software Engineering and Computer Science (IJSECS) Jurnal Nasional Cosphi Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer (BALOK) Jurnal Indonesia : Manajemen Informatika dan Komunikasi
Mohamad Efendi Lasulika
Universitas Ichsan Gorontalo
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Other

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K-Nearest Neighbor for Gorontalo City Chili Price Prediction Using Feature Selection, Backward Elimination, and Forward Selection Labolo, Abdul Yunus; Utiarahman, Siti Andini; Lasulika, Mohamad Efendi; Drajana, Ivo Colanus Rally; Bode, Andi
International Journal Software Engineering and Computer Science (IJSECS) Vol. 3 No. 3 (2023): DECEMBER 2023
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v3i3.1709

Abstract

This study addresses chili price volatility, an important concern that impacts the national economy and societal welfare. Fluctuations in chili prices in the retail market greatly influence market demand, thereby influencing farming decisions, especially chili cultivation. To help make better decisions, Researchers use forecasting, which is defined as the projection of future trends based on the analysis of historical data, using statistical methods. The K-Nearest Neighbor (K-NN) algorithm is used because of its resistance to high noise on large training datasets. However, challenges arise in determining the optimal value of 'k' and selecting related attributes. To overcome this, Feature Selection is applied to refine the model by removing irrelevant features, resulting in a significant reduction in the model error rate. This improvement indicates an increase in the efficiency of the K-NN algorithm with the incorporation of Feature Selection. Our findings show that the model, with backward elimination in Feature Selection, achieves a Root Mean Square Error (RMSE) of 0.202, outperforming the model using forward selection. The prediction accuracy of this model reaches an average of 78.86%, which is much higher than the baseline data of 50%. This shows the success of the proposed method in predicting chili prices.
Analisi Efektivitas Pembelajaran Daring Spada Unisan Dengan Menggunakan Metode System Usability Scale damopolii, muhlis; Lasulika, Mohamad Efendi; Mustofa, Yasil Aril
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.v2i2.627

Abstract

 ABSTRACT ; Online learning is distance learning that is conducted indirectly or through face- to-face communication by video conferencing, uploading, and downloading materials and assignments via the internet. It is not new. It has been widely applied in high schools and universities but is ineffective due to the lack of facilities. It occurs in universities between students and lecturers. To make students and lecturers understand online learning, Universitas Ichsan Gorontalo, especially the Informatics Engineering Study Program, has carried out an online learning system using an application, commonly called SPADA UNISAN. It is provided to meet the needs of the teaching and learning process between students and lecturers to be more flexible, efficient, measurable, and enjoyable. The results of the analysis of online learning using the method of System Usability Scale) indicate that the results of the assessment given to 114 respondents obtain a score of 45%. with the Acceptability Ranges version obtains “Not Acceptable”. The grade scale results in terms of the level of user acceptance are included in the Poor Category, and the score obtained is above the average score. It means that this system cannot be accepted by its users and has been below the standard usability average value setKeywords: fuzzy Tsukamoto, online game addiction, duration, compulsion, Keywords: system analysis, online learning, SUS method
Aplikasi Pencarian Rute Terdekat Tempat Dokter Praktek Fasilitas Bpjs Mengunakan Metode Djikstra Luviani, Luviani; Apriyanto Alhamad; Serwin; Mohamad Efendi Lasulika
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.v3i1.752

Abstract

Abstract- Searching for the fastest route while traveling is necessary besides finding the destination. The reason for finding the fastest route is to streamline the trip and save travel costs. Another problem in making an effective trip is a city search carried out by someone who knows, someone who spreads hospitals, health centers, clinics, and pharmacies that serve the Social Insurance Administration Organization in Gorontalo City/Regency, and knows several nearby places. In the implementation of the Social Insurance Administration Organization in Gorontalo City/Regency branch, there are still obstacles faced by the community. The lack of information regarding the distribution of health facilities and information makes people confused when choosing and locating which health facility they will visit for treatment using a card from the Social Insurance Administration Organization. By designing this information system, people can map the health facilities that serve the Social Insurance Administration Organization. The designation of this system uses the DJikstra algorithm to find the fastest route to the health facilities of Social Insurance Administration Organization to obtain a research result of a system that can find the fastest route to the health facilities of the Social Insurance Administration Organization. It is hoped that it can help the public in getting the fastest way to health facilities of the Social Insurance Administration Organization in Gorontalo City/Regency. Keywords: fastest route search system, health facilities, Social Insurance Administration Organization, Djikstra algorithm
K-NEAREST NEIGHBOR MENGGUNAKAN FEATURE SELECTION BACKWARD ELIMINATION UNTUK PREDIKSI JUMLAH PERMINTAAN DARAH PADA PMMI KOTA GORONTALO Lasena, Yulianti; Taliki, Sunarto; Lasulika, Mohamad Efendi; Bode, Andi
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 4 No. 1 (2023): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v4i1.172

Abstract

The importance of the availability of blood at PMI, it is expected that PMI always maintains the amount of blood supply to meet the need for blood transfusions. Prediction of blood supply is needed to overcome problems related to bloodstock supply at PMI Gorontalo. The application of predicting the number of blood requests with the K-Nearest Neighbor Algorithm can be done to overcome the existing problems. K-NN is a non-parametric algorithm that can be used for classification and regression. The last few decades have been used in prediction cases, but the K-NN algorithm is better if feature selection is applied in selecting features that are not relevant to the model, the feature selection used in this study is Backward Selection. This study aims to determine the error value in predicting the number of requests for blood at the PMI in Gorontalo City. Meanwhile, the purpose of this research is to find the error value of the K-Nearest Neighbor Algorithm and Feature Selection which can be used as a reference for PMI in making policies to make various efforts to maintainbloodstockk in the future.
Analisis Perbandingan Performa Jaringan Wlan Menggunakan Metode RMA Dan RSSI Pada Indoor Dan Outdoor: Analisis Perbandingan Performa Jaringan Wlan Menggunakan Metode RMA Dan RSSI Pada Indoor Dan Outdoor Febrilianty Umasugi1; Muis Nanja; Mohamad Efendi Lasulika
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 3 No 2 (2024): November 2024
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37195/balok.v3i2.1192

Abstract

Dalam beberapa tahun terakhir, penggunaan jaringan wireless lan telah mengalami pertumbuhan pesat peningkatan penggunaan ini menyebabakan pertumbuhan hotspot ditempat umum seperti tempat kerja dan lembaga pendidikan lainnya, hotspot memungkinkan masyarakat untuk mengakses internet tanpa perlu menggunakan kabel diarea hotspot dimana pun mereka berada. Keterbatasan jarak sinyal nirkabel disebabkan oleh banyaknya hambatan di sekitarnya, gangguan sinyal, serta kekuatan transmiternya yang terbatas. Hambatan seperti dinding tebal adalah salah satu contoh yang tidak memungkinkan terjadi, terutama ketika beberapa perangkat menggunakan frekuensi yang sama dalam saluran yang bersamaan. Penelitian ini bertujuan untuk memperoleh hasil pengukuran kualitas layanan jaringan menggunakan metode RMA dan RSSI pada indoor dan outdoor. Salah satu metode yang bisa digunakan pada penelitian analisis perbandingan pefroma WLAN yaitu RMA (Realibility, Mantainability and Availability) dan RSSI (Received Signal Strength Indicator). Pada proses ini pra pemrosesan data dilakukan dengan menginstal software PRTG dan Wifi Analyzer yang biasa digunakan untuk kebutuhan dan analisis. Model dilatih pada dataset dengan berbagai fitur dan hasilnya menunjukkan akurasi yang tinggi sebesar 99.54%, yaitu berupa proses menganalisis sekumpulan data untuk meringkas karateristik utamanya agar pengguna lebih memahami data set yang akan digunakan.RMA (Realibility, Mantainability and Availability) dan RSSI (Received Signal Strength Indicator) keduanya efektif dalam mengevaluasi kekuatan sinyal dan kualitas jaringan. RSSI memberikan gambaran yang lebih cepat dan sederhana tentang kekuatan sinyal pada suatu titik tertentu, sementara RMA menyediakan rata-rata kekuatan sinyal yang bisa lebih representatif untuk analisis jangka panjang. Kata Kunci: WLAN, RSSI, RMA, kualitas layanan, indoor, outdoor, jaringan nirkabel
Design of a Watering Control System for Chili Seedlings Using Arduino Uno Ramadhani, Syarifah Fitrah; Lasulika, Mohamad Efendi; Bode, Andi; Djailani, Moh. Adrian; Posumah, Risky Randa
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 3 (2024): DECEMBER 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i3.3225

Abstract

Technology in agriculture has brought revolutionary changes in the way we view and treat food production. This research is the design of a watering control system because controlling plant watering is an important factor in healthy plant growth. With the use of technology such as Arduino Uno, designing an automatic watering control system that can monitor soil moisture, regulate watering according to plant needs, besides that, another goal is to increase agricultural productivity by optimizing watering of chili plants. The results of research and testing that have been carried out, the Arduino Uno based automatic plant irrigation tool shows success in its design and operation; this tool has been designed and made using an Arduino Uno microcontroller and YL-69 sensor, as well as other supporting devices, which function according to their purpose and function with good performance in automatic watering. This tool can work effectively when the humidity sensor sends data to the Arduino, where if the received data is below the specified limit, the relay automatically activates the water pump to perform watering. During the process, if the sensor detects soil moisture levels above the limit, the relay will turn off the pump and stop watering
Komparasi Algoritma Data Mining Menggunakan Forward selection Pada Prediksi Harga Jagung Lasulika, Mohamad Efendi; Bode, Andi
JURNAL TECNOSCIENZA Vol. 5 No. 2 (2021): TECNOSCIENZA
Publisher : JURNAL TECNOSCIENZA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51158/tecnoscienza.v5i2.392

Abstract

Meningkatnya volume produksi jagung yang diperdagangkan dan kecenderungan harga jagung dipasaran menuntut kebijakan pemerintah dalam mengendalikan stabilasi harga jagung. Sehingga pemerintah kesulitan dalam menentukan atau memprediksi harga komoditi yang akan datang, namun pada penelitian ini hanya fokus pada beberapa algoritma klasifikasi untuk mengetahui algoritma apakah yang mempunyai tingkat akurasi tertinggi dalam hal prediksi harga jagung sehingga dapat digunakan dalam melakukan prediksi harga beberapa hari kedepannya. Dalam data mining ada beberapa algoritma klasifikasi yang dapat digunakan, seperti K-Neural Network, Artificial Neural Network, Naïve Bayes, Regresi Linear, C-45 dll, namun pada penelitian ini hanya fokus pada dua metode saja yaitu Naïve Bayes dan K- Neural Network. Berdasarkan hasil penelitian yang dilakukan metode K-nn merupakan metode yang sangat bagus atau baik dalam melakukan prediksi ataupun klasifikasi, hala ini dapat dilihat dari hasil RMSE yang di hasilkan yaitu 0,05, metode ini mampu menghasilkan nilai terbaik walaupun tanpa adanya penambahan metode lain seperti forward selection, sementara itu untuk naïve bayes metode ini juga merupakan metode terbaik dalam melakukan prediksi ataupun klasifikasi, akan tetapi naïve bayes mempunyai beberapa kekurangan apabila digunakan untuk type data univariate ataupun numerical. Penambahan forward selection kepada pengolahan data dapat membantu menghasilkan akurasi yang baik pula. Walaupun tanpa forward selection K-NN dan Naïve bayes merupakan metode komputasi yang sangat baik dalam prediksi ataupun klasifikasi. Kata kunci: Harga Jagung, Komparasi Metode, K-Neural Network, Naïve bayes, forward selection
Aplikasi Diagnosa Penyakit Hama Tanaman Kakao Menggunakan Metode Certainty Factor Pada Dinas Perkebunan dan Peternakan Provinsi Gorontalo Bode, Andi; Lasulika, Mohamad Efendi; Nur, Muh. Jabal
JURNAL TECNOSCIENZA Vol. 5 No. 2 (2021): TECNOSCIENZA
Publisher : JURNAL TECNOSCIENZA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51158/tecnoscienza.v5i2.403

Abstract

Kakao merupakan komoditas yang diperdagangkan yang memiliki peluang untuk berkembang dan dapat berkembang serta menambah devisa negara. Tanaman kakao terserang berbagai hama dan penyakit, Hama dan penyakit tersebut dapat dilihat dari gejala yang ditimbulkannya, namun untuk mengetahui secara pasti jenis hama dan penyakit yang menyerang kakao diperlukan tenaga ahli / ahli pertanian. Sedangkan tenaga ahli pertanian yang jumlahnya terbatas dan tidak dapat sekaligus menyelesaikan permasalahan petani, sehingga diperlukan suatu aplikasi dengan kemampuan ahli yang berisi keahlian ahli pertanian tentang penyakit dan gejala tanaman kakao. Pada penelitian ini dirancang aplikasi diagnostik dengan menggunakan metode kepastian Certainty Factor dan metode inferensi Backward Chaining, dengan bantuan bahasa pemrograman PHP (PHP: Hypertext Preprocessor) dan Basi Data MySQL. Aplikasi ini dirancang untuk membantu petani dalam mendiagnosis penyakit tanaman kakao. Kata kunci: Certainty Factor, Hama dan Penyakit, Tanaman Kakao
PENERAPAN REGRESI LINIER UNTUK PREDIKSI DAYA BELI PELANGGAN PADA ACE HARDWARE GORONTALO Juliyanto Giu; Husdi; Zufrianto Y. Lamasigi; Moh. Efendi Lasulika
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 4 No 1 (2025): Mei 2025
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37195/balok.v4i1.1478

Abstract

Abstrak - Penelitian ini bertujuan untuk memprediksi Daya Beli Pelanggan pada Ace Hadware. Ace Hardware Indonesia pertama kali dibuka di Supermal Karawaci, Tangerang pada tahun 1995, disusul sejumlah toko lain di berbagai daerah. Dimana upaya-upaya yang telah dilakukan oleh pengelola dan merupakan salah satu cara untuk menciptakan rasa puas Pelanggan terhadap store sehingga tentunya Pelanggan tersebut tidak ingin mencari store yang lain. Dalam penelitian ini ingin membuat sistem dengan teknik data mining yang akan digunakan untuk memprediksikan Daya Beli Pelanggan berdasarkan data Daya Beli Pelanggan serta menggunakan metode Regresi Linier Sederhana dengan variabel X adalah jumlah pengunjung dan Y adalah daya beli. Dengan mencari tingkat error menggunakan Mean Absolute Persentage Eror (MAPE) dengan nilai hasil sebesar 814.309 metode regresi Linier agar menghasilkan hasil yang lebih tepat dan akurat. Kata Kunci: Regresi Linier, Prediksi Daya Beli Pelanggan, MAPE
Co-Authors Andi Bode Apriyanto Alhamad damopolii, muhlis Djailani, Moh. Adrian Drajana, Ivo Colanus Rally Febrilianty Umasugi1 Haditsah Annur Husdi Juliyanto Giu Labolo, Abdul Yunus Luviani, Luviani Muis Nanja Nur, Muh Jabal Nur, Muh. Jabal Posumah, Risky Randa Ramadhani, Syarifah Fitrah Serwin Sri Rahayu Hidiya Sunarto Taliki Utiarahman, Siti Andini Warid Yunus Yasin Aril Mustofa Yulianti Lasena Zufrianto Y. Lamasigi