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All Journal Conference SENATIK STT Adisutjipto Yogyakarta JUSIM (Jurnal Sistem Informasi Musirawas) JATI (Jurnal Mahasiswa Teknik Informatika) JISA (Jurnal Informatika dan Sains)
Arif, Alfis
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Aerospace Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Implementation of the K-Means Clustering Algorithm in Determining Productive Oil Palm Blocks at Pt Arta Prigel Anggriani, Yesi Pitaloka; Arif, Alfis; Febriansyah, Febriansyah
JISA(Jurnal Informatika dan Sains) Vol 7, No 1 (2024): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v7i1.2008

Abstract

The purpose of this study is to implement the K-Means Clustering method to determine the patterns of productive oil palm production based on their blocks at Pt Arta Prigel. The research is motivated by issues within the oil palm blocks, such as the absence of productive block summaries, insufficient plantation land analysis, and erroneous decision-making. The development method utilizes CRISP-DM, with data spanning 2 years from October 2021 to October 2023. From the 1275 production records, after cleaning, 1015 records remain. Filtering the initial 51 blocks results in 37 blocks for the years 2021 and 2022, and 46 blocks for the year 2023. After clustering, the production outcomes for the year 2021 are as follows: cluster_0 has 34 blocks, cluster_1 has 10 blocks. For the year 2022, cluster_0 has 24 blocks, cluster_1 has 37 blocks. In the year 2023, cluster_0 has 44 blocks, cluster_1 has 27 blocks. The testing method employs the silhouette coefficient, and the silhouette score testing results indicate the formation of 2 clusters (K=2) with a value of 0.62, the results obtained from testing with 2 clusters indicate that the formed clusters are accurate. The findings of this study include patterns, graphs, and production tables generated using the K-Means Clustering method at Pt Arta Prigel.
IMPLEMENTASI METODE WEIGHTED AGGREGATED SUM PRODUCT ASSESMENT DALAM MENENTUKAN KEDELAI TERBAIK PRODUKSI TAHU, TEMPE Anggraini, Inda; Arif, Alfis; Ningrum, Ichda Utami
JUSIM (Jurnal Sistem Informasi Musirawas) Vol 9 No 1 (2024): JUSIM : Jurnal Sistem Informasi Musi Rawas JUNI
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jusim.v9i1.2263

Abstract

This research aims to implement the Weighted Aggregated Sum Product Assessment method in identifying soybeans as raw materials in the production of tofu and tempeh. Tofu and tempeh production often experiences production failures, such as the tofu compaction process being insufficient or the texture being too dense, the tempeh fermentation process being less than optimal and so on. This is influenced by poor soybean raw materials, both in terms of texture and color and the selection of soybeans which is still done directly by looking at the color and brand. Meanwhile, these two things do not necessarily correspond to the right criteria for tofu and tempeh production. In this research, the Weighted Aggregated Sum Product Assessment method was used in making decisions to determine the best soybeans for producing tofu and tempeh based on 4 selection criteria, namely soy color, soy size, soy moisture and soy texture. All these criteria are then processed to obtain the best soybean results that are appropriate for the raw material for making tofu and tempe, namely soybeans from the Ahok supplier with a value of 4.475.
Decision Support System for Determining Website-Based Fruit Quality in Pagar Alam Fruit Farmers Group Muslim, Buhori; Arif, Alfis
SENATIK STT Adisutjipto Vol 5 (2019): Peran Teknologi untuk Revitalisasi Bandara dan Transportasi Udara [ISBN 978-602-52742-
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/senatik.v5i0.306

Abstract

Fruit is a healthy supplement, the biggest consumer of fruit is found in big cities. Pagar Alam is an area that produces various types of fruit. Assessment of fruit quality by farmer groups, still using manual methods so that it has some weaknesses. Weakness in evaluating the quality of fruit manually causes an inaccurate assessment because the assessment system is done by estimating the quality of a sample of fruits based on the experience of quality assessors and not based on standardized aspects of assessment. For this reason, a Decision Support System (SPK) was developed to determine the quality of fruit based on a website that helps assessors of the quality of fruits in farmer groups in determining accurate fruit quality with a quick process. This system uses PHP as its programming language, the method used by RAD is an object oriented approach. The system can be used to support fruit quality assessment decisions, thus providing data on the quality of current fruit yields and can be used as a reference for farmers to improve the quality of fruit production in the next harvest.
IMPLEMENTASI ALGORITMA K-MEANS CLUSTERING DALAM MENENTUKAN BLOK TANAMAN SAWIT PRODUKTIF PADA PT ARTA PRIGEL Pitaloka Anggriani, Yesi; Arif, Alfis; Febriansyah, Febriansyah
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 8 No. 2 (2024): JATI Vol. 8 No. 2
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v8i2.9225

Abstract

Pt Arta Prigel merupakan perusahaan perkebunan kelapa sawit yang telah beroperasi secara komersial sejak tahun 1983 terletak di kota Lahat. Dan memiliki 3 divisi dan 51 blok. Akan tetapi blok blok tanaman sawit tersebut tidak ada rekap bloknya sehingga kurangnya analisis terhadap lahan perkebunan yang mengakibatkan turunnya produksi hasil panen dan salah mengambil keputusan. Tujuan penelitian ini untuk mengimplementasikan metode K-Means Clustering dalam menentukan pola hasil produksi sawit yang produktif berdasarkan bloknya di Pt Arta Prigel Lahat. Menggunakan metode pengembangan CRISP-DM dan metode pengujian silhouette coefficient. Setelah dilakukan proses clustering diketahui cluster_0 dengan tingkat produksi cukup produktif berjumlah 38 blok di tahun 2021 sampai 2023, cluster_1 dengan tingkat produksi produktif berjumlah 15 blok di tahun 2021 sampai 2023, dan cluster_2 dengan tingkat tidak produktif berjumlah 47 blok untuk tahun 2021 sampai 2023. Metode pengujian menggunakan silhouette coefficient dengan menghitung hasil silhouette score. Hasil dari pengujian metode silhouette coefficient pada aplikasi Google Colab dengan Bahasa Pemrograman Python untuk menghitung hasil silhouette score terbentuk 3 cluster (K=3) dengan nilai 0.61.
Co-Authors Anggraini, Inda Anggriani, Yesi Pitaloka Buhori Muslim Febriansyah Febriansyah Ningrum, Ichda Utami Pitaloka Anggriani, Yesi