Article Per Year (5 Year)
p-Index From 2020 - 2025
0.751
P-Index
This Author published in this journals
All Journal Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika SPIRIT JAMI: Jurnal Ahli Muda Indonesia Jumat Informatika: Jurnal Pengabdian Masyarakat
Muslim Alamsyah
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Social Sciences Other

Published : 5 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 5 Documents
Search

 1 
SISTEM PENILAIAN KINERJA KARYAWAN DENGAN METODE FUZZY MULTICRITERIA DECISION MAKING (Studi Kasus : PT. PANCA ARNYS) Muslim Alamsyah

Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Karyawan merupakan salah satu faktor utama dalam sebuah perusahaan. Untuk itu Dalam hal ini Fuzzy Multicriteria Decision Making (FMCDM) merupakan salah satumetode yang paling banyak digunakan dalam pengambilan keputusan. Tujuannya memilihalternatif terbaik dari beberapa alternatif eksklusif yang paling baik atas dasar performansiumum dalam bermacam kriteria atau atribut yang ditentukan oleh perusahaan ataupengambil keputusan. dalam kegiatan oprasionalnya, diperlukan karyawam yang mempuyai kinerja yang baik,sehingga dapat mempengaruhi berkualitas atau tidaknya perusahaan tersebut dalammencapai tujuannya. Salah satu proses Manajemen Sumber Daya Manusia yaitu penilaiankinerja karyawan.
PERANCANGAN SISTEM PENGAMBILAN KEPUTUSAN DALAM MENENTUKAN KUALITAS PRODUK DETERJEN BU KRIM MENGGUNAKAN METODE ANALYTICAL HIERARCHY PROCESS (STUDY KASUS: PT. MANDIRI INVESTAMA SEJATI ) Muslim Alamsyah

Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Investama PT Mandiri Sejati is a company engaged in the industry is one of them producing detergent. There are so many factors to be considered in determining the quality of production to be produced per day which will be targeted in starting a business. The problem faced is determining product quality detergent which is still manual calculations. Has developed a new system that is implemented in a decision support system. This system is used to help facilitate the processing of data in determining the quality of the detergent. The entire data collection related in determining the quality of the data detergents include color, texture, scent and cleaning power. The method used for data processing using AHP (Analytic Hierarchy Process). Stages in AHP begins the process of defining the problem, the manufacture of structural hierarchy that begins with a general purpose, followed by the criteria and alternatives options, Test consistency hierarchy. If it does not comply with CR <0.100 then the assessment should be repeated again. The results showed that application of decision support systems are used to determine the quality of this detergen, it can perform calculations with AHP (Analytic Hierarchy Process) is faster than manual calculation so that it can be more efficient and the accuracy of the data is close to perfect.
Implementasi Metode K-Nearest Neighbor dalam Mengklasifikasikan Kesegaran Ikan Kuro Menggunakan Citra Muslim Alamsyah; Muhammad Ainun Nadjib
SPIRIT Vol 14, No 2 (2022): Spirit
Publisher : LPPM ITB Yadika Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53567/spirit.v14i2.246

Abstract

Kurofish (Eleutheronematetradactylum) is a type of fish that spreads throughout Indonesian waters, with different local names in each region. On the east coast of Sumatra it is known by the name of sukain fish while on the north coast of Java it is known as kuro fish. Freshness of fish is one of the benchmarks for consumers in choosing quality or good fish for consumption, because fresh fish is rich in protein and nutrients. Fish is also known to contain omega 3 fatty acids which are beneficial for brain growth, as well as calcium, vitamin D and phosphorus which are good for bones. However, the nutritional content contained in the fish may not be optimal anymore if it is consumed in a condition that is not fresh. Not only that, consumption of fish that is not fresh which leads to rotten conditions can make someone poisoned.Fish freshness checks can be done through microbiological and chemical analysis, but this method is less effective because it requires a lot of manpower, is quite expensive, and takes longer. For traders, the level of freshness of fish is determined in the traditional way, namely by observing, holding and smelling the smell of fish, sometimes there is also something that escapes observation so that there are still fish that are not fresh.To reduce these problems, the authors apply the K-Nearest Neighbor method in classifying the freshness of fish using images based on the color of the fish. By using the Kuro Fish type, using Matlab tools and in the results of the study using the K-Nearest Neighbor method with 40 training data and producing an accuracy of 100% and 16 test data with 7 correct data resulting in poor accuracy, which is 43 ,75%
Sosialisasi Cara Pembuatan ID Card Berbasis Barcode di Desa Baujeng Kabupaten Pasuruan Muchammad Firman; Muslim Alamsyah; Cindy Amelia Lestari
Jumat Informatika: Jurnal Pengabdian Masyarakat Vol. 4 No. 3 (2023): Desember
Publisher : LPPM Universitas KH. A. Wahab Hasbullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32764/abdimasif.v4i3.4448

Abstract

This activity is a community service program which aims to provide training to the community in Baujeng Village, Beji District, Pasuruan Regency, East Java. This program includes training in making Barcode-based ID Cards with implementation methods that include initial planning, collection of materials and resources, program implementation, evaluation, follow-up, documentation, reporting and dissemination of results. The partner of this program is Pondok Minhajuttulab, an Islamic boarding school which acts as a place for socialization. Problems to be overcome include a lack of understanding and exposure to modern technological developments in Baujeng Village. This program also includes evaluation through questionnaires and recording the problems faced by participants during the activity. The aim of this program is to increase community participation in digital transformation and serve community needs efficiently using computer technology
PENGGUNAAN METODE ANFIS (ADAPTIVE NEURO FUZZY INFERENCE SYSTEM) UNTUK PREDIKSI BEBAN LISTRIK JANGKA PENDEK Ainun Aziz; Mochammad Firman Arif; Muslim Alamsyah
JAMI: Jurnal Ahli Muda Indonesia Vol. 3 No. 1 (2022): Juni 2022
Publisher : Akademi Komunitas Negeri Putra Sang Fajar Blitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46510/jami.v3i1.45

Abstract

Peningkatan kebutuhan listrik di masyarakat mengharuskan PT. PLN perlu melakukan perencanaan operasi dan perencanaan sistem pengembangan tenaga listrik untuk mengetahui seberapa besar daya listrik yang harus disalurkan ke konsumen agar daya listrik yang ditransmisikan tepat sasaran dan tepat ukuran. Oleh karena itu, dibuatlah metode ANFIS (Adaptive Neuro Fuzzy Inference System) pada penelitian ini. ANFIS (Adaptive Neuro Fuzzy Inference System) adalah suatu penggabungan mekanisme sistem inferensi fuzzy yang digambarkan dalam arsitektur jaringan saraf. Dalam suatu penelitian, membutuhkan program yang dibuat menggunakan bahasa programan Matlab. Dalam hasil Analisis prakiraan konsumsi beban listrik menggunakan software aplikasi Matlab didapatkan perbandingan kesalahan untuk pelatihan (training) yang mampu mengikuti pola beban listrik harian dengan nilai MSE 0,2938 dan nilai MAPE 4,7892% dengan kriteria MAPE <10% yang di nilai ‘sangat baik’. Sedangkan berdasarkan perbandingan pengujian (testing) dengan nilai MSE 0,4361 dan nilai MAPE 14,6062% dengan kriteria MAPE 10% - 20% yang di nilai ‘baik’ atau lebih rendah dari pelatihan. Dengan hasil prediksi beban listrik di tanggal 18 November 2010 sampai dengan 25 November 2010, secara keseluruan baik pelatihan (training) dan pengujian (testing) dengan model metode ANFIS memiliki performansi yang baik untuk meramalkan beban listrik di masa mendatang, untuk dapat sebagai langkah antisipasi permintaan daya listrik di waktu kedepan.
Co-Authors Ainun Aziz Anang Aris Widodo Cindy Amelia Lestari Mochammad Firman Arif Muchammad Firman Muhammad Ainun Nadjib