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All Journal AKUNTANSI DEWANTARA Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) JURNAL FLYWHEEL
Pratama, Adhi
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Computer Science & IT Economics, Econometrics & Finance Energy Industrial & Manufacturing Engineering Mechanical Engineering

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Analisa Perancangan Desalinasi Air Laut Dengan Variasi Filter Tempurung Kelapa Dan Variasi Temperatur Pemanasan Pratama, Adhi; Rahmadianto, Febi
JURNAL FLYWHEEL Vol 12 No 2 (2021): Jurnal Flywheel
Publisher : Teknik Mesin S1 ITN Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/flywheel.v12i2.4279

Abstract

Dalam penyusunan jurnal ini peneliti bermaksud untuk memberikan informasi tentang proses desalinasi air laut dengan variasi filter tempurung kelapa dan variasi temperatur pemanasan. Dengan proses desalinasi air laut dengan filter tempurung kelapa sangat menguntungkan karena mampu memberikan penurunan nilai TDS pada air laut dengan satuan PPM mg/l. Namun tidak hanya itu, desalinasi air laut sangat memberikan kontribusi untuk peningkatan nilai pH air laut untuk kelayakan minum. Dalam proses desalinasi dengan filter tempurung kelapa menggunakan 3 filter tempurung kelapa yang memiliki ketebalan, suhu dan holding waktu yang berbeda-beda. Dalam pengolahan data penelitian ini menggunakan metode taguchi. Selama proses pengujian ini batasannya adalah untuk mengetahui dampak filter tempurung kelapa terhadap nilai TDS dan pH. Maka dari itu peneliti sungguh mendapatkan temuan menakjubkan dimana filter tempurung kelapa ini mampu mengurangi zat yang terkandung dalam air laut melalui uji TDS. Sehingga penulis menyimpulkan bahwa tempurung kelapa sangat penting untuk proses desalinasi air laut dalam mengurangi kadar zat yang bisa saja berbahaya dalam air laut.
Pengaruh literasi keuangan dan perilaku menabung terhadap kesiapan pensiun pada pekerja di Kota Timika Pratama, Adhi; Srimindarti, Ceacili; Hendrian
AKUNTANSI DEWANTARA Vol 7 No 2 (2023): AKUNTANSI DEWANTARA VOL. 7 NO. 2 OKTOBER 2023
Publisher : Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30738/ad.v7i2.15778

Abstract

Workers need to prepare provisions in order to have readiness to undergo retirement. The retirement provisions in question include financial literacy and saving behavior, both of which can be a solution to dealing with financial needs in retirement. This study aims to determine the effect of financial literacy and saving behavior on retirement readiness. The object of this research is active workers who work and are in the Timika City area. The approach used is quantitative, the type of data used in this study is primary data which is the respondent's answer through a questionnaire distributed using google form. The number of samples in this study were 100 respondents with an age range between 20-40 years. The scale used in measuring variables is a Likert scale. Data analysis using the PLS (Partial Least Square) method processed with Smart PLS 3.0 software. The results obtained in this study indicate that financial literacy and saving behavior have a significant positive effect on retirement readiness. In this study, the proposed model can explain retirement readiness with a percentage of 54.7%, while the rest is explained by other variables outside this study
Determining The Loan Feasiblity of Bank Customers Using Naïve Bayes, K-Nearest Neighbors And Linear Regression Algorithms Pratiwi, Aniec Anafisah; Saraswati, Wahyuning Tyas; Ardiansyah, Rizky Firman; Rouf, Erik Halma; Pratama, Adhi
Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Vol. 6 No. 3 (2023): Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI)
Publisher : Utility Project Solution

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

Abstract

In the financial industry, lending to customers is one of the core activities in the financial sector which has a significant impact on the economy and business growth. Credit is the provision of money or bills that can be equated with it, based on a loan agreement between banks and other parties that requires the agreement to repay the debt after a certain period of time by providing interest. However, the process within these financial institutions needs to assess the feasibility of granting credit to customers who apply for credit. To facilitate the determination of eligibility for granting credit to customers, an accurate and effective analytical method is needed to help solve problems in determining the eligibility classification for granting credit to customers by applying the Naive Bayes, K-Nearest Neighbors (K-NN) and Linear Regression algorithms. Based on the results of the tests that have been carried out using the three algorithms obtained, the results show an accuracy value on K-NN of 87.837%, calculations using the Naïve Bayes algorithm have an accuracy value of 88.917%, while calculations using the Linear Regression algorithm produce a Mean absolute error value of 6.703. It can be concluded that in bank creditworthiness fraud using the Naïve Bayes algorithm method is more accurate when compared to the K-NN and Linear Regression algorithms
Co-Authors Ardiansyah, Rizky Firman Febi Rahmadianto Hendrian Pratiwi, Aniec Anafisah Rouf, Erik Halma Saraswati, Wahyuning Tyas Srimindarti, Ceacili