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Prediksi Penyakit Jantung Menggunakan Metode-Metode Machine Learning Berbasis Ensemble â€“ Weighted Vote Alhamad, Apriyanto; Azis, Azminuddin I. S.; Santoso, Budy; Taliki, Sunarto
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 5, No 3 (2019): Volume 5 No 3
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v5i3.37188

Kematian yang disebabkan penyakit jantung masih sangat tinggi, sehingga perlu peningkatan upaya-upaya pencegahannya, misalnya dengan meningkatkan capaian model prediksinya. Penerapan metode-metode machine learning pada dataset publik (Cleveland, Hungary, Switzerland, VA Long Beach, & Statlog) yang umumnya digunakan oleh para peneliti untuk prediksi penyakit jantung, termasuk pengembangan alat bantunya, masih belum menangani missing value, noisy data, unbalanced class, dan bahkan data validation secara efisien. Oleh karena itu, pendekatan imputasi mean/mode diusulkan untuk menangani missing value replacement, Min-Max Normalization untuk menangani smoothing noisy data, K-Fold Cross Validation untuk menangani data validation, dan pendekatan ensemble menggunakan metode Weighted Vote (WV) yang dapat menyatukan kinerja tiap-tiap metode machine learning untuk mengambil keputusan klasifikasi sekaligus untuk mereduksi unbalanced class. Hasil penelitian ini menunjukkan bahwa metode yang diusulkan tersebut memberikan akurasi sebesar 85,21%, sehingga mampu meningkatkan kinerja akurasi metode-metode machine learning, selisih 7,14% dengan Artificial Neural Network, 2,77% dengan Support Vector Machine, 0,34% dengan C4.5, 2,94% dengan NaÃ¯ve Bayes, dan 3,95% dengan k-Nearest Neighbor.

SUPPORT VECTOR MACHINE BERBASIS CHI SQUARE UNTUK PREDIKSI HARGA BERAS ECER KABUPATEN POHUWATO Sunarto Taliki; Ivo Colanus Rally Drajana; Andi Bode
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 5, No 2 (2022): June 2022
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v5i2.899

One of the staple foods for most Indonesians is rice. Rice is one of the staple foods most consumed by the people of Indonesia, the need for rice is also increasing, considering the very large and scattered population of Indonesia. The ups and downs of rice prices also have an impact on farmers because of their large production. The solution to dealing with uncertain changes in the retail price of rice is to predict prices. One way to find out the estimated retail price of rice is to make predictions using the Support Vector Machine algorithm using Chi Square. The results of the experiments that have been carried out, the prediction of rice prices has been successfully carried out. The smallest error rate in the Support Vector Machine algorithm model is RMSE 733,061. Then the proposed model approaches the value of perfection, because the comparison of the experimental results of rice price predictions produces an average accuracy value of 95.82%. Thus, the proposed method is declared successful.

Aplikasi Diagnosa Penyakit Tanaman Cabai Merah menggunakan Algoritma K-Nearest Neighbor Sunarto Taliki; Serwin Serwin; Jabal Nur; Ivo Colanus Rally Drajana
JURNAL TECNOSCIENZA Vol. 6 No. 2 (2022): TECNOSCIENZA
Publisher : JURNAL TECNOSCIENZA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51158/tecnoscienza.v6i2.712

Tanaman cabai merah merupakan komoditas holtikultura yang begitu sangat penting bagi kebutuhan dan keperluan manusia, seperti, ramuan obat-obatan tradisional, sebagai bumbu untuk makanan, dimakan bersama makanan ringan dan lain-lain. Dilihat dari tingkat serangan dan kondisi pertanian cabai merah di lapangan saat ini masi terkendala dengan belum adanya rekomendasi metode pengendalian yang efektif sehingga petani cenderung menggunakan pastisida kimia yang berdampak negatif terhadap lingkugan. Untuk mendiagnosa berbagai jenis penyakit yang menyerang tanaman cabai merah diperlukan seorang pakar/ahli. Pada peniltian ini akan membangun sebuah aplikasi yang dapat mendiagnosa dan memberikan solusi kepada petani mengenai masalah penyakit tanaman cabai merah. Aplikasi sistem pakar diagnosa penyakit tanaman cabai dapat diimplementasikan dengan melihat hasil pengujian berdasarkan konsultasi diagnosis serta solusi yang diberikan. Hal ini dapat dilihat pada jenis penyakit Busuk Akar dengan gejala kasus G01, G02 nilai Bobot 3.1, Gejala Dipilih (Benar) dan Nilai Kedekatan K-NN (3/4) = 0.75.

K-NEAREST NEIGHBOR MENGGUNAKAN FEATURE SELECTION BACKWARD ELIMINATION UNTUK PREDIKSI JUMLAH PERMINTAAN DARAH PADA PMMI KOTA GORONTALO Yulianti Lasena; Sunarto Taliki; Mohamad Efendi Lasulika; Andi Bode
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 4 No. 1 (2023): Jurnal Indonesia : Manajemen Informatika dan Komunikasi (JIMIK)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) AMIK Indonesia

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

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.

Prediksi Jumlah Persediaan Telur Ayam Menggunakan Metode K-Neares Neighbor: - baguna, filda; Husdi, Husdi; Taliki, Sunarto; Kamaruddin, Andi
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.v2i2.119

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

Sistem Kendali Pemberian Pakan Ayam Broiler Otomatis Berbasis Mikrokontroler Tongkonoo, Agustian; Salihi, Irvan Abraham; Taliki, Sunarto
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.v2i2.180

ABSTRACT ; A control system is a system that produces a certain value as its output through controlling or changing the provisions of the system input. Feeding is an important element in determining the level of broiler production. Likewise, there is one farmer in Bilungala Village, Bone Pantai Subdistrict producing broiler chickens. Feeding chickens can be made easier by using a mechanical device controlled by equipment. This system uses a microcontroller connected to an Arduino and a timer for feeding chickens with a Real-Time Clock (RTC). This automatic tool has two parts, namely, the main container serves as a place to store food reserves and the second container as a place to feed the chickens. The Real-Time Clock functions to regulate the feeding hours of broilers. A Solenoid Valve functions as a faucet for feeding the broilers carried out from 07.00 through 17.00. It is for the morning, noon, and evening feedings regulated by the Real-Time Clock (RTC).Keywords: control system, chicken feeding, automatic, RTC (Real Time Clock), Solenoid Valve

Analisa Kualitas Layanan Jaringan Internet Pada Wireless Lan Menggunakan Metode Qos (Quality Of Service) Tangahu, Rizqi Adiputera; Andi Bode; Sunarto Taliki
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.v3i1.723

Abstract- The development of the Internet network is now very rapid. The Internet is a source of information that people mostly use to find information they need. It is not only used in big cities but also remote villages. The internet network must have a high access network speed to attract many users, whether or not in public facilities such as terminals or city parks. In other words, the internet network can make a big contribution to society. Currently, the internet has become a trending need, starting from the world of business, education, government, entertainment, and others. Kedai Mako is a coffee shop that uses the internet network as a means to make customers feel at home apart from its delicious coffee. Through internet networks, customers enjoy their coffee while playing games or social media without using their data quota. Kedai Mako customers using the internet network usually only know whether or nonot t the network is good by measuring the network speed via YouTube or online games. Yet, Internet users do not know whether or not the quality of the internet service they receive is good. It has not implemented QoS or measured network quality using QoS. The internet network at Kedai Mako often goes down, making customers uncomfortable with the internet network at Kedai Mako. Therefore, this research manages to analyze the internet network at Kedai Mako, and the results of the analysis can be used as recommendations for the physical implementation of the internet network hoped to be able to support the addition of other supporting services in the future. Based on the results of Quality of Service measurements in 5 experiments, the average value for the Throughput index obtained is 3,4 in the Very Good category, the index value for Packet Loss gained is 3.6 in the Very Good category, the index value for Delay analyzed is 4 in the Very Good category, and the Jitter index value indicates 3, in the Good category. The average index value for Kedai Mako is 3.5 in the Good category. Keywords: QoS, Wireshark, WLAN, Throughput, Packet Loss, Delay, Jitter

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

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.

Aplikasi Diagnosa Penyakit Tanaman Cabai Merah menggunakan Algoritma K-Nearest Neighbor Taliki, Sunarto; Serwin, Serwin; Nur, Jabal; Drajana, Ivo Colanus Rally
JURNAL TECNOSCIENZA Vol. 6 No. 2 (2022): TECNOSCIENZA
Publisher : JURNAL TECNOSCIENZA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51158/tecnoscienza.v6i2.712

Tanaman cabai merah merupakan komoditas holtikultura yang begitu sangat penting bagi kebutuhan dan keperluan manusia, seperti, ramuan obat-obatan tradisional, sebagai bumbu untuk makanan, dimakan bersama makanan ringan dan lain-lain. Dilihat dari tingkat serangan dan kondisi pertanian cabai merah di lapangan saat ini masi terkendala dengan belum adanya rekomendasi metode pengendalian yang efektif sehingga petani cenderung menggunakan pastisida kimia yang berdampak negatif terhadap lingkugan. Untuk mendiagnosa berbagai jenis penyakit yang menyerang tanaman cabai merah diperlukan seorang pakar/ahli. Pada peniltian ini akan membangun sebuah aplikasi yang dapat mendiagnosa dan memberikan solusi kepada petani mengenai masalah penyakit tanaman cabai merah. Aplikasi sistem pakar diagnosa penyakit tanaman cabai dapat diimplementasikan dengan melihat hasil pengujian berdasarkan konsultasi diagnosis serta solusi yang diberikan. Hal ini dapat dilihat pada jenis penyakit Busuk Akar dengan gejala kasus G01, G02 nilai Bobot 3.1, Gejala Dipilih (Benar) dan Nilai Kedekatan K-NN (3/4) = 0.75.

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